astro-ph.EP - 地球与行星天体

    cs.AI - 人工智能 cs.CG - 计算几何学 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DS - 数据结构与算法 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.LO - 计算逻辑 cs.MA - 多代理系统 cs.MM - 多媒体 cs.MS - 数学软件 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 hep-ex - 高能物理实验 hep-lat - 高能物理晶格 math.NA - 数值分析 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 physics.soc-ph - 物理学与社会 q-bio.GN - 基因组学 q-bio.NC - 神经元与认知 q-fin.MF - 数学金融 q-fin.ST - 统计金融学 q-fin.TR - 贸易与市场微观结构 quant-ph - 量子物理 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [astro-ph.EP]Artificial Neural Network classification of asteroids in the M1:2 mean-motion resonance with Mars
    • [cs.AI]”Weak AI” is Likely to Never Become “Strong AI”, So What is its Greatest Value for us?
    • [cs.AI]A Bayesian Approach to Identifying Representational Errors
    • [cs.AI]A Comprehensive Survey on Knowledge Graph Entity Alignment via Representation Learning
    • [cs.AI]Alignment of Language Agents
    • [cs.AI]Automation: An Essential Component Of Ethical AI?
    • [cs.AI]Boosting the Speed of Entity Alignment 10*: Dual Attention Matching Network with Normalized Hard Sample Mining
    • [cs.AI]Contrastive Explanations of Plans Through Model Restrictions
    • [cs.AI]Enhancing the Transferability of Adversarial Attacks through Variance Tuning
    • [cs.AI]Generating Negations of Probability Distributions
    • [cs.AI]High-efficiency Euclidean-based Models for Low-dimensional Knowledge Graph Embeddings
    • [cs.AI]Joint Resource Management for MC-NOMA: A Deep Reinforcement Learning Approach
    • [cs.AI]KnowRU: Knowledge Reusing via Knowledge Distillation in Multi-agent Reinforcement Learning
    • [cs.AI]Monitoring Object Detection Abnormalities via Data-Label and Post-Algorithm Abstractions
    • [cs.AI]Playing Against the Board: Rolling Horizon Evolutionary Algorithms Against Pandemic
    • [cs.AI]Retraining DistilBERT for a Voice Shopping Assistant by Using Universal Dependencies
    • [cs.AI]Scaling the weight parameters in Markov logic networks and relational logistic regression models
    • [cs.AI]The AI Settlement Generation Challenge in Minecraft: First Year Report
    • [cs.AI]The General Theory of General Intelligence: A Pragmatic Patternist Perspective
    • [cs.AI]Towards An Ethics-Audit Bot
    • [cs.AI]eDarkTrends: Harnessing Social Media Trends in Substance use disorders for Opioid Listings on Cryptomarket
    • [cs.AI]eXtended Artificial Intelligence: New Prospects of Human-AI Interaction Research
    • [cs.CG]Computing Coordinated Motion Plans for Robot Swarms: The CG:SHOP Challenge 2021
    • [cs.CG]Coordinated Motion Planning Through Randomized k-Opt
    • [cs.CL]’Just because you are right, doesn’t mean I am wrong’: Overcoming a Bottleneck in the Development and Evaluation of Open-Ended Visual Question Answering (VQA) Tasks
    • [cs.CL]A More Fine-Grained Aspect-Sentiment-Opinion Triplet Extraction Task
    • [cs.CL]Abuse is Contextual, What about NLP? The Role of Context in Abusive Language Annotation and Detection
    • [cs.CL]An Automated Multiple-Choice Question Generation Using Natural Language Processing Techniques
    • [cs.CL]Annotating Hate and Offenses on Social Media
    • [cs.CL]Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP Models
    • [cs.CL]CaSiNo: A Corpus of Campsite Negotiation Dialogues for Automatic Negotiation Systems
    • [cs.CL]Centrality Meets Centroid: A Graph-based Approach for Unsupervised Document Summarization
    • [cs.CL]Changing the Mind of Transformers for Topically-Controllable Language Generation
    • [cs.CL]English-Twi Parallel Corpus for Machine Translation
    • [cs.CL]Explaining the Road Not Taken
    • [cs.CL]Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications
    • [cs.CL]InsertGNN: Can Graph Neural Networks Outperform Humans in TOEFL Sentence Insertion Problem?
    • [cs.CL]LSTM Based Sentiment Analysis for Cryptocurrency Prediction
    • [cs.CL]Multi-facet Universal Schema
    • [cs.CL]Multiple-hypothesis CTC-based semi-supervised adaptation of end-to-end speech recognition
    • [cs.CL]NLP for Ghanaian Languages
    • [cs.CL]On Hallucination and Predictive Uncertainty in Conditional Language Generation
    • [cs.CL]PENELOPIE: Enabling Open Information Extraction for the Greek Language through Machine Translation
    • [cs.CL]PnG BERT: Augmented BERT on Phonemes and Graphemes for Neural TTS
    • [cs.CL]Retrieving Event-related Human Brain Dynamics from Natural Sentence Reading
    • [cs.CL]Shrinking Bigfoot: Reducing wav2vec 2.0 footprint
    • [cs.CL]Supersense and Sensibility: Proxy Tasks for Semantic Annotation of Prepositions
    • [cs.CL]Unsupervised Self-Training for Sentiment Analysis of Code-Switched Data
    • [cs.CL]Whitening Sentence Representations for Better Semantics and Faster Retrieval
    • [cs.CL]You Can Do Better! If You Elaborate the Reason When Making Prediction
    • [cs.CR]Leaky Nets: Recovering Embedded Neural Network Models and Inputs through Simple Power and Timing Side-Channels — Attacks and Defenses
    • [cs.CR]Privacy and Trust Redefined in Federated Machine Learning
    • [cs.CR]Secure Platform for Processing Sensitive Data on Shared HPC Systems
    • [cs.CV]A Dataset and Benchmark Towards Multi-Modal Face Anti-Spoofing Under Surveillance Scenarios
    • [cs.CV]A Hierarchical Approach to Remote Sensing Scene Classification
    • [cs.CV]A Model-Based Approach to Synthetic Data Set Generation for Patient-Ventilator Waveforms for Machine Learning and Educational Use
    • [cs.CV]A Survey of Orthogonal Moments for Image Representation: Theory, Implementation, and Evaluation
    • [cs.CV]ACSNet: Action-Context Separation Network for Weakly Supervised Temporal Action Localization
    • [cs.CV]AR Mapping: Accurate and Efficient Mapping for Augmented Reality
    • [cs.CV]Adaptive Boosting for Domain Adaptation: Towards Robust Predictions in Scene Segmentation
    • [cs.CV]Adaptive Methods for Real-World Domain Generalization
    • [cs.CV]Adaptive Surface Normal Constraint for Depth Estimation
    • [cs.CV]Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Framework
    • [cs.CV]AlignMix: Improving representation by interpolating aligned features
    • [cs.CV]An Adversarial Human Pose Estimation Network Injected with Graph Structure
    • [cs.CV]An Efficiently Coupled Shape and Appearance Prior for Active Contour Segmentation
    • [cs.CV]Attention to Warp: Deep Metric Learning for Multivariate Time Series
    • [cs.CV]Attention-guided Image Compression by Deep Reconstruction of Compressive Sensed Saliency Skeleton
    • [cs.CV]Automated Backend-Aware Post-Training Quantization
    • [cs.CV]Automated freezing of gait assessment with marker-based motion capture and deep learning approaches expert-level detection
    • [cs.CV]BA^2M: A Batch Aware Attention Module for Image Classification
    • [cs.CV]Bayesian Deep Basis Fitting for Depth Completion with Uncertainty
    • [cs.CV]Bridging Vision and Language from the Video-to-Text Perspective: A Comprehensive Review
    • [cs.CV]Bridging the Visual Gap: Wide-Range Image Blending
    • [cs.CV]CNN-based search model underestimates attention guidance by simple visual features
    • [cs.CV]COVID-19 personal protective equipment detection using real-time deep learning methods
    • [cs.CV]CalibDNN: Multimodal Sensor Calibration for Perception Using Deep Neural Networks
    • [cs.CV]Capsule Network is Not More Robust than Convolutional Network
    • [cs.CV]Classification of Seeds using Domain Randomization on Self-Supervised Learning Frameworks
    • [cs.CV]Classifying Video based on Automatic Content Detection Overview
    • [cs.CV]Cloth-Changing Person Re-identification from A Single Image with Gait Prediction and Regularization
    • [cs.CV]Cloud2Curve: Generation and Vectorization of Parametric Sketches
    • [cs.CV]Context Modeling in 3D Human Pose Estimation: A Unified Perspective
    • [cs.CV]Contextual Scene Augmentation and Synthesis via GSACNet
    • [cs.CV]CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification
    • [cs.CV]CvT: Introducing Convolutions to Vision Transformers
    • [cs.CV]Deep Ensemble Collaborative Learning by using Knowledge-transfer Graph for Fine-grained Object Classification
    • [cs.CV]Deep Image Compositing
    • [cs.CV]Deep Learning Techniques for In-Crop Weed Identification: A Review
    • [cs.CV]Defect-GAN: High-Fidelity Defect Synthesis for Automated Defect Inspection
    • [cs.CV]Distilling Virtual Examples for Long-tailed Recognition
    • [cs.CV]Drop the GAN: In Defense of Patches Nearest Neighbors as Single Image Generative Models
    • [cs.CV]Elsa: Energy-based learning for semi-supervised anomaly detection
    • [cs.CV]Embedding Transfer with Label Relaxation for Improved Metric Learning
    • [cs.CV]Enhanced Boundary Learning for Glass-like Object Segmentation
    • [cs.CV]Equivariant Imaging: Learning Beyond the Range Space
    • [cs.CV]Evaluation of Correctness in Unsupervised Many-to-Many Image Translation
    • [cs.CV]Exploiting Local Geometry for Feature and Graph Construction for Better 3D Point Cloud Processing with Graph Neural Networks
    • [cs.CV]Face Recognition as a Method of Authentication in a Web-Based System
    • [cs.CV]Face Transformer for Recognition
    • [cs.CV]Few-Shot Learning for Video Object Detection in a Transfer-Learning Scheme
    • [cs.CV]Few-shot Semantic Image Synthesis Using StyleGAN Prior
    • [cs.CV]FocusedDropout for Convolutional Neural Network
    • [cs.CV]Fooling LiDAR Perception via Adversarial Trajectory Perturbation
    • [cs.CV]Friends and Foes in Learning from Noisy Labels
    • [cs.CV]From Synthetic to Real: Unsupervised Domain Adaptation for Animal Pose Estimation
    • [cs.CV]GNeRF: GAN-based Neural Radiance Field without Posed Camera
    • [cs.CV]Generalizing to the Open World: Deep Visual Odometry with Online Adaptation
    • [cs.CV]Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers
    • [cs.CV]Get away from Style: Category-Guided Domain Adaptation for Semantic Segmentation
    • [cs.CV]Going Deeper Into Face Detection: A Survey
    • [cs.CV]Graph-based Facial Affect Analysis: A Review of Methods, Applications and Challenges
    • [cs.CV]H-GAN: the power of GANs in your Hands
    • [cs.CV]HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset
    • [cs.CV]HiT: Hierarchical Transformer with Momentum Contrast for Video-Text Retrieval
    • [cs.CV]High-Fidelity and Arbitrary Face Editing
    • [cs.CV]HumanGPS: Geodesic PreServing Feature for Dense Human Correspondences
    • [cs.CV]IA-GCN: Interpretable Attention based Graph Convolutional Network for Disease prediction
    • [cs.CV]Image Processing Techniques for identifying tumors in an MRI image
    • [cs.CV]Imponderous Net for Facial Expression Recognition in the Wild
    • [cs.CV]Instance segmentation with the number of clusters incorporated in embedding learning
    • [cs.CV]IoU Attack: Towards Temporally Coherent Black-Box Adversarial Attack for Visual Object Tracking
    • [cs.CV]Knowing What VQA Does Not: Pointing to Error-Inducing Regions to Improve Explanation Helpfulness
    • [cs.CV]LSG-CPD: Coherent Point Drift with Local Surface Geometry for Point Cloud Registration
    • [cs.CV]Labels4Free: Unsupervised Segmentation using StyleGAN
    • [cs.CV]LatentKeypointGAN: Controlling GANs via Latent Keypoints
    • [cs.CV]LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis
    • [cs.CV]Lear
    1000
    ning Placeholders for Open-Set Recognition
    • [cs.CV]Learning Efficient Photometric Feature Transform for Multi-view Stereo
    • [cs.CV]Learning Generative Models of Textured 3D Meshes from Real-World Images
    • [cs.CV]Learning a Sketch Tensor Space for Image Inpainting of Man-made Scenes
    • [cs.CV]Learning to Predict Salient Faces: A Novel Visual-Audio Saliency Model
    • [cs.CV]LiDAR R-CNN: An Efficient and Universal 3D Object Detector
    • [cs.CV]Looking Beyond Two Frames: End-to-End Multi-Object Tracking Using Spatial and Temporal Transformers
    • [cs.CV]Low-Fidelity End-to-End Video Encoder Pre-training for Temporal ActionLocalization
    • [cs.CV]MVSNeRF: Fast Generalizable Radiance Field Reconstruction from Multi-View Stereo
    • [cs.CV]ManhattanSLAM: Robust Planar Tracking and Mapping Leveraging Mixture of Manhattan Frames
    • [cs.CV]Memory Enhanced Embedding Learning for Cross-Modal Video-Text Retrieval
    • [cs.CV]Meta-Mining Discriminative Samples for Kinship Verification
    • [cs.CV]Mining Latent Classes for Few-shot Segmentation
    • [cs.CV]Monocular 3D Vehicle Detection Using Uncalibrated Traffic Cameras through Homography
    • [cs.CV]Motion Basis Learning for Unsupervised Deep Homography Estimation with Subspace Projection
    • [cs.CV]Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image Encoding
    • [cs.CV]NeMI: Unifying Neural Radiance Fields with Multiplane Images for Novel View Synthesis
    • [cs.CV]No frame left behind: Full Video Action Recognition
    • [cs.CV]Noise Injection-based Regularization for Point Cloud Processing
    • [cs.CV]OLED: One-Class Learned Encoder-Decoder Network with Adversarial Context Masking for Novelty Detection
    • [cs.CV]On Development and Evaluation of Retargeting Human Motion and Appearance in Monocular Videos
    • [cs.CV]On the Adversarial Robustness of Visual Transformers
    • [cs.CV]Onfocus Detection: Identifying Individual-Camera Eye Contact from Unconstrained Images
    • [cs.CV]POSEFusion: Pose-guided Selective Fusion for Single-view Human Volumetric Capture
    • [cs.CV]Panoptic-PolarNet: Proposal-free LiDAR Point Cloud Panoptic Segmentation
    • [cs.CV]PeaceGAN: A GAN-based Multi-Task Learning Method for SAR Target Image Generation with a Pose Estimator and an Auxiliary Classifier
    • [cs.CV]Picasso: A CUDA-based Library for Deep Learning over 3D Meshes
    • [cs.CV]PixelTransformer: Sample Conditioned Signal Generation
    • [cs.CV]PlaneSegNet: Fast and Robust Plane Estimation Using a Single-stage Instance Segmentation CNN
    • [cs.CV]Proxy Synthesis: Learning with Synthetic Classes for Deep Metric Learning
    • [cs.CV]ReAgent: Point Cloud Registration using Imitation and Reinforcement Learning
    • [cs.CV]Realistic face animation generation from videos
    • [cs.CV]Remote Sensing Image Translation via Style-Based Recalibration Module and Improved Style Discriminator
    • [cs.CV]Representation, Analysis of Bayesian Refinement Approximation Network: A Survey
    • [cs.CV]Rethinking ResNets: Improved Stacking Strategies With High Order Schemes
    • [cs.CV]RobustNet: Improving Domain Generalization in Urban-Scene Segmentation via Instance Selective Whitening
    • [cs.CV]SIENet: Spatial Information Enhancement Network for 3D Object Detection from Point Cloud
    • [cs.CV]SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences
    • [cs.CV]Selective Output Smoothing Regularization: Regularize Neural Networks by Softening Output Distributions
    • [cs.CV]Self-Supervised Visibility Learning for Novel View Synthesis
    • [cs.CV]SelfGait: A Spatiotemporal Representation Learning Method for Self-supervised Gait Recognition
    • [cs.CV]Single Object Tracking through a Fast and Effective Single-Multiple Model Convolutional Neural Network
    • [cs.CV]Structure of Multiple Mirror System from Kaleidoscopic Projections of Single 3D Point
    • [cs.CV]StyleMeUp: Towards Style-Agnostic Sketch-Based Image Retrieval
    • [cs.CV]TFPose: Direct Human Pose Estimation with Transformers
    • [cs.CV]TS-CAM: Token Semantic Coupled Attention Map for Weakly Supervised Object Localization
    • [cs.CV]Towards High Fidelity Monocular Face Reconstruction with Rich Reflectance using Self-supervised Learning and Ray Tracing
    • [cs.CV]Tracking 6-DoF Object Motion from Events and Frames
    • [cs.CV]Tracking Based Semi-Automatic Annotation for Scene Text Videos
    • [cs.CV]TrafficQA: A Question Answering Benchmark and an Efficient Network for Video Reasoning over Traffic Events
    • [cs.CV]TransCenter: Transformers with Dense Queries for Multiple-Object Tracking
    • [cs.CV]Transformer Tracking
    • [cs.CV]Transitive Learning: Exploring the Transitivity of Degradations for Blind Super-Resolution
    • [cs.CV]Unified Graph Structured Models for Video Understanding
    • [cs.CV]Unified Shape and SVBRDF Recovery using Differentiable Monte Carlo Rendering
    • [cs.CV]ViViT: A Video Vision Transformer
    • [cs.CV]Video Classification with FineCoarse Networks
    • [cs.CV]Video Rescaling Networks with Joint Optimization Strategies for Downscaling and Upscaling
    • [cs.CV]Visual Distant Supervision for Scene Graph Generation
    • [cs.CV]Zero-shot Adversarial Quantization
    • [cs.CY]A trustable and interoperable decentralized solution for citizen-centric and cross-border eGovernance: A conceptual approach
    • [cs.CY]Acceptance of COVID-19 Vaccine and Its Determinants in Bangladesh
    • [cs.CY]Should College Dropout Prediction Models Include Protected Attributes?
    • [cs.DB]Cache-Efficient Fork-Processing Patterns on Large Graphs
    • [cs.DC]A cooperative partial snapshot algorithm for checkpoint-rollback recovery of large-scale and dynamic distributed systems and experimental evaluations
    • [cs.DC]Effective GPU Parallelization of Distributed and Localized Model Predictive Control
    • [cs.DC]Extending Classic Paxos for High-performance Read-Modify-Write Registers
    • [cs.DC]Large-Scale Approximate k-NN Graph Construction on GPU
    • [cs.DC]Loosely-self-stabilizing Byzantine-tolerant Binary Consensus for Signature-free Message-passing Systems
    • [cs.DC]MT-lib: A Topology-aware Message Transfer Library for Graph500 on Supercomputers
    • [cs.DC]MergeComp: A Compression Scheduler for Scalable Communication-Efficient Distributed Training
    • [cs.DS]Euler Meets GPU: Practical Graph Algorithms with Theoretical Guarantees
    • [cs.HC]Hand tracking for immersive virtual reality: opportunities and challenges
    • [cs.HC]Personalized Affect-Aware Socially Assistive Robot Tutors Aimed at Fostering Social Grit in Children with Autism
    • [cs.HC]Towards Tool-Support for Interactive-Machine Learning Applications in the Android Ecosystem
    • [cs.IR]Community-based Cyberreading for Information Understanding
    • [cs.IR]Context-aware short-term interest first model for session-based recommendation
    • [cs.IR]Multi-Facet Recommender Networks with Spherical Optimization
    • [cs.IR]Supporting verification of news articles with automated search for semantically similar articles
    • [cs.IT]A Short Introduction to Information-Theoretic Cost-Benefit Analysis
    • [cs.IT]A function field approach toward good polynomials for optimal LRC codes
    • [cs.IT]Active RIS vs. Passive RIS: Which Will Prevail in 6G?
    • [cs.IT]Asymptotically Optimal Massey-Like Inequality on Guessing Entropy With Application to Side-Channel Attack Evaluations
    • [cs.IT]Explicit Construction of Minimum Storage Rack-Aware Regenerating Codes for All Parameters
    • [cs.IT]Hybrid Beamforming Optimization for DOA Estimation Based on the CRB Analysis
    • [cs.IT]Performance Analysis of I/Q Imbalance with Hardware Impairments over Fox’s H-Fading Channels
    • [cs.IT]Private and Resource-Bounded Locally Decodable Codes for Insertions and Deletions
    • [cs.IT]Spatial Characterization of Electromagnetic Random Channels
    • [cs.IT]The DoF Region of Order-(K-1) Messages for the K-user MIMO Broadcast Channel with Delayed CSIT
    • [cs.IT]Uplink Channel Impulse Response Based Secondary Carrier Prediction
    • [cs.LG]A Temporal Kernel Approach for Deep Learning with Continuous-time Information
    • [cs.LG]A nonlinear diffusion method for semi-supervised learning on hypergraphs
    • [cs.LG]Accurate and Reliable Forecasting using Stochastic Differential Equations
    • [cs.LG]An Introduction to Robust Graph Convolutional Networks
    • [cs.LG]Bayesian Attention Networks for Data Compression
    • [cs.LG]Categorical Representation Learning: Morphism is All You Need
    • [cs.LG]ClaRe: Practical Class Incremental Learning By Remembering Previous Class Representations
    • [cs.LG]Co-Imitation Learning without Expert Demonstration
    • [cs.LG]Continuous Conditional Generative Adversarial Networks (cGAN) with Generator Regularization
    • [cs.LG]Deep reinforcement learning of event-triggered communication and control for multi-agent cooperative transport
    • [cs.LG]Efficient Explanations from Empirical Explainers
    • [cs.LG]Ensemble-in-One: Learning Ensemble within Random Gated Networks for Enhanced Adversarial Robustness
    • [cs.LG]Explaining Representation by Mutual Information
    • [cs.LG]Exploiting Adam-like Optimization Algorithms to Improve the Performance of Convolutional Neural Networks
    • [cs.LG]FixNorm: Dissecting Weight Decay for Training Deep Neural Networks
    • [cs.LG]Generalization over different cellular automata rules learned by a deep feed-forward neural network
    • [cs.LG]Graph Classification by Mixture of Diverse Experts
    • [cs.LG]Graph Unlearning
    • [cs.LG]Hierarchical Relationship Alignment Metric Learning
    • [cs.LG]Human-in-the-loop Handling of Knowledge Drift
    • [cs.LG]IUP: An Intelligent Utility Prediction Scheme for Solid-State Fermentation in 5G IoT
    • [cs.LG]Improved Autoregressive Modeling with Distribution Smoothing
    • [cs.LG]Improving Model Robustness by Adaptively Correcting Perturbation Levels with Active Queries
    • [cs.LG]Increasing the Efficiency of Policy Learning for Autonomous Vehicles by Multi-Task Representation Learning
    • [cs.LG]KNN, An Underestimated Model for Regional Rainfall Forecasting
    • [cs.LG]Lagrangian Objective Function Leads to Improved Unforeseen Attack Generalization in Adversarial Training
    • [cs.LG]LiBRe: A Practical Bayesian Approach to Adversarial Detection
    • [cs.LG]Local Explanations via Necessity and Sufficiency: Unifying Theory and Practice
    • [cs.LG]Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark
    • [cs.LG]Modeling the Nonsmoothness of Modern Neural Networks
    • [cs.LG]Multiscale Clustering of Hyperspectral Images Through Spectral-Spatial Diffusion Geometry
    • [cs.LG]On the limits of algorithmic prediction across the globe
    • [cs.LG]One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks
    • [cs.LG]Pairing Character Classes in a Deathmatch Shooter Game via a Deep-Learning Surrogate Model
    • [cs.LG]Performance Analysis of Out-of-Distribution Detection on Various Trained Neural Networks
    • [cs.LG]Private Non-smooth Empirical Risk Minimization and Stochastic Convex Optimization in Subquadratic Steps
    • [cs.LG]RAN-GNNs: breaking the capacity limits of graph neural networks
    • [cs.LG]Rapid Risk Minimization with Bayesian Models Through Deep Learning Approximation
    • [cs.LG]Regular Polytope Networks
    • [cs.LG]Representation Learning by Ranking under multiple tasks
    • [cs.LG]Rethinking Neural Operations for Diverse Tasks
    • [cs.LG]Risk Bounds for Learning via Hilbert Coresets
    • [cs.LG]Robust Reinforcement Learning under model misspecification
    • [cs.LG]Score-oriented loss (SOL) functions
    • [cs.LG]Self-supervised Discriminative Feature Learning for Multi-view Clustering
    • [cs.LG]Self-supervised Graph Neural Networks without explicit negative sampling
    • [cs.LG]SetVAE: Learning Hierarchical Composition for Generative Modeling of Set-Structured Data
    • [cs.LG]Symbolic regression outperforms other models for small data sets
    • [cs.LG]Tensor Networks for Multi-Modal Non-Euclidean Data
    • [cs.LG]The Sample Complexity of Distribution-Free Parity Learning in the Robust Shuffle Model
    • [cs.LG]Thermal transmittance prediction based on the application of artificial neural networks on heat flux method results
    • [cs.LG]Understanding the role of importance weighting for deep learning
    • [cs.LG]Variational Rejection Particle Filtering
    • [cs.LG]ZeroGrad : Mitigating and Explaining Catastrophic Overfitting in FGSM Adversarial Training
    • [cs.LG][Reproducibility Report] Rigging the Lottery: Making All Tickets Winners
    • [cs.LG]von Mises—Fisher Loss: An Exploration of Embedding Geometries for Supervised Learning
    • [cs.LO]On Symmetry and Quantification: A New Approach to Verify Distributed Protocols
    • [cs.MA]Competing Adaptive Networks
    • [cs.MM]Product semantics translation from brain activity via adversarial learning
    • [cs.MS]Mathematics of Digital Hyperspace
    • [cs.NE]Collocation Polynomial Neural Forms and Domain Fragmentation for Initial Value Problems
    • [cs.NE]Determination of weight coefficients for additive fitness function of genetic algorithm
    • [cs.NE]Hybrid Evolutionary Optimization Approach for Oilfield Well Control Optimization
    • [cs.NE]Self-Constructing Neural Networks Through Random Mutation
    • [cs.NE]Shape-constrained Symbolic Regression — Improving Extrapolation with Prior Knowledge
    • [cs.NI]Joint Sampling and Transmission Policies for Minimizing Cost under AoI Constraints
    • [cs.NI]Joint User Association and Power Allocation in Heterogeneous Ultra Dense Network via Semi-Supervised Representation Learning
    • [cs.RO]A hybrid controller for safe and efficient collision avoidance control
    • [cs.RO]Autonomous Overtaking in Gran Turismo Sport Using Curriculum Reinforcement Learning
    • [cs.RO]Compact 3D Map-Based Monocular Localization Using Semantic Edge Alignment
    • [cs.RO]Equivariant Filtering Framework for Inertial-Integrated Navigation
    • [cs.RO]Fundamental Challenges in Deep Learning for Stiff Contact Dynamics
    • [cs.RO]Ground Encoding: Learned Factor Graph-based Models for Localizing Ground Penetrating Radar
    • [cs.RO]LASER: Learning a Latent Action Space for Efficient Reinforcement Learning
    • [cs.RO]Lessons Learned Developing an Assembly System for WRS 2020 Assembly Challenge
    • [cs.RO]Minimum directed information: A design principle for compliant robots
    • [cs.RO]Multi-Robot Distributed Semantic Mapping in Unfamiliar Environments through Online Matching of Learned Representations
    • [cs.RO]Online Flocking Control of UAVs with Mean-Field Approximation
    • [cs.RO]Pursuer Assignment and Control Strategies in Multi-agent Pursuit-Evasion Under Uncertainties
    • [cs.RO]Range-Visual-Inertial Odometry: Scale Observability Without Excitation
    • [cs.RO]Refractive Light-Field Features for Curved Transparent Objects in Structure from Motion
    • [cs.RO]Robust Feedback Motion Policy Design Using Reinforcement Learning on a 3D Digit Bipedal Robot
    • [cs.RO]Set-Valued Rigid Body Dynamics for Simultaneous Frictional Impact
    • [cs.RO]Towards Robust State Estimation by Boosting the Maximum Correntropy Criterion Kalman Filter with Adaptive Behaviors
    • [cs.RO]Transmitter Discovery through Radio-Visual Probabilistic Active Sensing
    • [cs.RO]Two-Stage Clustering of Human Preferences for Action Prediction in Assembly Tasks
    • [cs.RO]Wall Detection Via IMU Data Classification In Autonomous Quadcopters
    • [cs.SD]Feature-based Representation for Violin Bridge Admittances
    • [cs.SD]Transformer-based end-to-end speech recognition with residual Gaussian-based self-attention
    • [cs.SE]Adaptive Autonomy in Human-on-the-Loop Vision-Based Robotics Systems
    • [cs.SE]Embedding API Dependency Graph for Neural Code Generation
    • [cs.SI]A Systematic Survey on Multilayer Community Detection
    • [cs.SI]ABOME: A Multi-platform Data Repository of Artificially Boosted Online Media Entities
    • [cs.SI]Analysing the Effect of Recommendation Algorithms on the Amplification of Misinformation
    • [cs.SI]Beyond the adjacency matrix: random line graphs and inference for networks with edge attributes
    • [cs.SI]Dynamic Network Embedding Survey
    • [cs.SI]Exploring, browsing and interacting with multi-scale structures of knowledge
    • [cs.SI]Post-mortem memory of public figures in news and social media
    • [eess.AS]Quantifying Bias in Automatic Speech Recognition
    • [eess.AS]Scalable and Efficient Neural Speech Coding
    • [eess.AS]Scaling sparsemax based channel selection for speech recognition with ad-hoc microphone arrays
    • [eess.IV]Best-Buddy GANs for Highly Detailed Image Super-Resolution
    • [eess.IV]Catalyzing Clinical Diagnostic Pipelines Through Volumetric Medical Image Segmentation Using Deep Neural Networks: Past, Present, & Future
    • [eess.IV]Checkerboard Context Model for Efficient Learned Image Compression
    • [eess.IV]Data-driven generation of plausible tissue geometries for realistic photoacoustic image synthesis
    • [eess.IV]Fully Automated 2D and 3D Convolutional Neural Networks Pipeline for Video Segmentation and Myocardial Infarction Detection in Echocardiography
    • [eess.IV]Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse Problems
    • [eess.IV]Improving prostate whole gland segmentation in t2-weighted MRI with synthetically generated data
    • [eess.IV]Invertible Image Signal Processing
    • [eess.IV]Multi-Disease Detection in Retinal Imaging based on Ensembling Heterogeneous Deep Learning Models
    • [eess.IV]Omniscient Video Super-Resolution
    • [eess.IV]Physical model simulator-trained neural network for computational 3D phase imaging of multiple-scattering samples
    • [eess.IV]Slimmable Compressive Autoencoders for Practical Neural Image Compression
    • [eess.IV]Tuning IR-cut Filter for Illumination-aware Spectral Reconstruction from RGB
    • [eess.SP]MIMO-OFDM Joint Radar-Communications: Is ICI Friend or Foe?
    • [eess.SP]On the benefits of robust models in modulation recognition
    • [eess.SY]Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative-Entropy Trust Regions
    • [eess.SY]Risk-Averse Stochastic Shortest Path Planning
    • [eess.SY]Self-adaptive Torque Vectoring Controller Using Reinforcement Learning
    • [eess.SY]Tuning of extended state observer with neural network-based control performance assessment
    • [hep-ex]Porting HEP Parameterized Calorimeter Simulation Code to GPUs
    • [hep-lat]Generalization capabilities of translationally equivariant neural networks
    • [math.NA]A bandit-learning approach to multifidelity approximation
    • [math.NA]Stiff Neural Ordinary Differential Equations
    • [math.NA]Translating Numerical Concepts for PDEs into Neural Architectures
    • [math.OC]Automatic differentiation for Riemannian optimization on low-rank matrix and tensor-train manifolds
    • [math.OC]Learning to Solve the AC-OPF using Sensitivity-Informed Deep Neural Networks
    • [math.OC]On the Stability of Nonlinear Receding Horizon Control: A Geometric Perspective
    • [math.OC]Ridesharing Evacuation Model of Disaster Response
    • [math.PR]Exact converses to a reverse AM—GM inequality, with applications to sums of independent random variables and (super)martingales
    • [math.PR]Phase transition in noisy high-dimensional random geometric graphs
    • [math.ST]Convergence of Griddy Gibbs Sampling and other perturbed Markov chains
    • [math.ST]Estimation of ergodic square-root diffusion under high-frequency sampling
    • [math.ST]Inference of Random Effects for Linear Mixed-Effects Models with a Fixed Number of Clusters
    • [math.ST]The EM Algorithm is Adaptively-Optimal for Unbalanced Symmetric Gaussian Mixtures
    • [math.ST]Variational inference of the drift function for stochastic differential equations driven by Lévy processes
    • [physics.soc-ph]A stochastic model for the influence of social distancing on loneliness
    • [q-bio.GN]GateKeeper-GPU: Fast and Accurate Pre-Alignment Filtering in Short Read Mapping
    • [q-bio.NC]Frequency-specific segregation and integration of human cerebral cortex: an intrinsic functional atlas
    • [q-bio.NC]Quantum Bose-Einstein Statistics for Indistinguishable Concepts in Human Language
    • [q-fin.MF]Monte Carlo algorithm for the extrema of tempered stable processes
    • [q-fin.ST]Accurate Stock Price Forecasting Using Robust and Optimized Deep Learning Models
    • [q-fin.TR]A Comparative Evaluation of Predominant Deep Learning Quantified Stock Trading Strategies
    • [quant-ph]Dual-Parameterized Quantum Circuit GAN Model in High Energy Physics
    • [stat.AP]Accurate Assessment via Process Data
    • [stat.AP]Are Multilevel functional models the next step in sports biomechanics and wearable technology? A case study of Knee Biomechanics patterns in typical training sessions of recreational runners
    • [stat.AP]Bayesian model averaging for mortality forecasting using leave-future-out validation
    • [stat.AP]Confidence Intervals for Seroprevalence
    • [stat.AP]External Correlates of Adult Digital Problem-Solving Behavior: Log Data Analysis of a Large-Scale Assessment
    • [stat.AP]Modeling Bivariate Geyser Eruption System with Covariate-Adjusted Recurrent Event Process
    • [stat.AP]Multivariate Gaussian Process Incorporated Predictive Model for Stream Turbine Power Plant
    • [stat.AP]NesPrInDT: Nested undersampling in PrInDT
    • [stat.AP]The study of variability in engineering design, an appreciation and a retrospective
    • [stat.ME]Accurate directional inference in Gaussian graphical models
    • [stat.ME]Bayesian Optimal Experimental Design for Inferring Causal Structure
    • [stat.ME]Comment on “Statistical Modeling: The Two Cultures” by Leo Breiman
    • [stat.ME]Data Integration through outcome adaptive LASSO and a collaborative propensity score approach
    • [stat.ME]Identifiability of Latent Class Models with Covariates
    • [stat.ME]Inapplicability of the TVOR method to USHMM Data Outlier Identification
    • [stat.ME]Inference in the stochastic Cox-Ingersol-Ross diffusion process with continuous sampling: Computational aspects and simulation
    • [stat.ME]Is it who you are or where you are? Accounting for compositional differences in cross-site treatment variation
    • [stat.ME]Martingale Posterior Distributions
    • [stat.ME]Multimodal Data Integration via Mediation Analysis with High-Dimensional Exposures and Mediators
    • [stat.ME]Nonparametric tests for treatment effect heterogeneity in observational studies
    • [stat.ME]Optimal False Discovery Rate Control for Large Scale Multiple Testing with Auxiliary Information
    • [stat.ME]Sparse and Smooth Functional Data Clustering
    • [stat.ME]Statistical Inference of Auto-correlated Eigenvalues with Applications to Diffusion Tensor Imaging
    • [stat.ME]Structure Learning of Contextual Markov Networks using Marginal Pseudo-likelihood
    • [stat.ME]Testing For a Parametric Baseline-Intensity in Dynamic Interaction Networks
    • [stat.ME]The Statistics of Circular Optimal Transport
    • [stat.ML]Community Detection in General Hypergraph via Graph Embedding
    • [stat.ML]Compositional Abstraction Error and a Category of Causal Models
    • [stat.ML]Deconfounded Score Method: Scoring DAGs with Dense Unobserved Confounding
    • [stat.ML]Entropy methods for the confidence assessment of probabilistic classification models
    • [stat.ML]Learning on heterogeneous graphs using high-order relations
    • [stat.ML]Lower Bounds on the Generalization Error of Nonlinear Learning Models
    • [stat.ML]Machine learning based digital twin for stochastic nonlinear multi-degree of freedom dynamical system
    • [stat.ML]Particle Filter Bridge Interpolation
    • [stat.ML]Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks
    • [stat.ML]Time-to-event regression using partially monotonic neural networks

    ·····································

    • [astro-ph.EP]Artificial Neural Network classification of asteroids in the M1:2 mean-motion resonance with Mars
    V. Carruba, S. Aljbaae, R. C. Domingos, W. Barletta
    http://arxiv.org/abs/2103.15586v1

    • [cs.AI]“Weak AI” is Likely to Never Become “Strong AI”, So What is its Greatest Value for us?
    Bin Liu
    http://arxiv.org/abs/2103.15294v1

    • [cs.AI]A Bayesian Approach to Identifying Representational Errors
    Ramya Ramakrishnan, Vaibhav Unhelkar, Ece Kamar, Julie Shah
    http://arxiv.org/abs/2103.15171v1

    • [cs.AI]A Comprehensive Survey on Knowledge Graph Entity Alignment via Representation Learning
    Rui Zhang, Bayu Distiawan Trisedy, Miao Li, Yong Jiang, Jianzhong Qi
    http://arxiv.org/abs/2103.15059v1

    • [cs.AI]Alignment of Language Agents
    Zachary Kenton, Tom Everitt, Laura Weidinger, Iason Gabriel, Vladimir Mikulik, Geoffrey Irving
    http://arxiv.org/abs/2103.14659v1

    • [cs.AI]Automation: An Essential Component Of Ethical AI?
    Vivek Nallur, Martin Lloyd, Siani Pearson
    http://arxiv.org/abs/2103.15739v1

    • [cs.AI]**Boosting the Speed of Entity Alignment 10: Dual Attention Matching Network with Normalized Hard Sample Mining
    Xin Mao, Wenting Wang, Yuanbin Wu, Man Lan
    http://arxiv.org/abs/2103.15452v1

    • [cs.AI]Contrastive Explanations of Plans Through Model Restrictions
    Benjamin Krarup, Senka Krivic, Daniele Magazzeni, Derek Long, Michael Cashmore, David E. Smith
    http://arxiv.org/abs/2103.15575v1

    • [cs.AI]Enhancing the Transferability of Adversarial Attacks through Variance Tuning
    Xiaosen Wang, Kun He
    http://arxiv.org/abs/2103.15571v1

    • [cs.AI]Generating Negations of Probability Distributions
    Ildar Batyrshin, Luis Alfonso Villa-Vargas, Marco Antonio Ramirez-Salinas, Moises Salinas-Rosales, Nailya Kubysheva
    http://arxiv.org/abs/2103.14986v1

    • [cs.AI]High-efficiency Euclidean-based Models for Low-dimensional Knowledge Graph Embeddings
    Kai Wang, Yu Liu, Quan Z. Sheng
    http://arxiv.org/abs/2103.14930v1

    • [cs.AI]Joint Resource Management for MC-NOMA: A Deep Reinforcement Learning Approach
    Shaoyang Wang, Tiejun Lv, Wei Ni, Norman C. Beaulieu, Y. Jay Guo
    http://arxiv.org/abs/2103.15371v1

    • [cs.AI]KnowRU: Knowledge Reusing via Knowledge Distillation in Multi-agent Reinforcement Learning
    Zijian Gao, Kele Xu, Bo Ding, Huaimin Wang, Yiying Li, Hongda Jia
    http://arxiv.org/abs/2103.14891v1

    • [cs.AI]Monitoring Object Detection Abnormalities via Data-Label and Post-Algorithm Abstractions
    Yuhang Chen, Chih-Hong Cheng, Jun Yan, Rongjie Yan
    http://arxiv.org/abs/2103.15456v1

    • [cs.AI]Playing Against the Board: Rolling Horizon Evolutionary Algorithms Against Pandemic
    Konstantinos Sfikas, Antonios Liapis
    http://arxiv.org/abs/2103.15090v1

    • [cs.AI]Retraining DistilBERT for a Voice Shopping Assistant by Using Universal Dependencies
    Pratik Jayarao, Arpit Sharma
    http://arxiv.org/abs/2103.15737v1

    • [cs.AI]Scaling the weight parameters in Markov logic networks and relational logistic regression models
    Felix Weitkämper
    http://arxiv.org/abs/2103.15140v1

    • [cs.AI]The AI Settlement Generation Challenge in Minecraft: First Year Report
    Christoph Salge, Michael Cerny Green, Rodrigo Canaan, Filip Skwarski, Rafael Fritsch, Adrian Brightmoore, Shaofang Ye, Changxing Cao, Julian Togelius
    http://arxiv.org/abs/2103.14950v1

    • [cs.AI]The General Theory of General Intelligence: A Pragmatic Patternist Perspective
    Ben Goertzel
    http://arxiv.org/abs/2103.15100v1

    • [cs.AI]Towards An Ethics-Audit Bot
    Siani Pearson, Martin Lloyd, Vivek Nallur
    http://arxiv.org/abs/2103.15746v1

    • [cs.AI]eDarkTrends: Harnessing Social Media Trends in Substance use disorders for Opioid Listings on Cryptomarket
    Usha Lokala, Francois Lamy, Triyasha Ghosh Dastidar, Kaushik Roy, Raminta Daniulaityte, Srinivasan Parthasarathy, Amit Sheth
    http://arxiv.org/abs/2103.15764v1

    • [cs.AI]eXtended Artificial Intelligence: New Prospects of Human-AI Interaction Research
    Carolin Wienrich, Marc Erich Latoschik
    http://arxiv.org/abs/2103.15004v1

    • [cs.CG]Computing Coordinated Motion Plans for Robot Swarms: The CG:SHOP Challenge 2021
    Sándor P. Fekete, Phillip Keldenich, Dominik Krupke, Joseph S. B. Mitchell
    http://arxiv.org/abs/2103.15381v1

    • [cs.CG]Coordinated Motion Planning Through Randomized k-Opt
    Paul Liu, Jack Spalding-Jamieson, Brandon Zhang, Da Wei Zheng
    http://arxiv.org/abs/2103.15062v1

    • [cs.CL]‘Just because you are right, doesn’t mean I am wrong’: Overcoming a Bottleneck in the Development and Evaluation of Open-Ended Visual Question Answering (VQA) Tasks
    Man Luo, Shailaja Keyur Sampat, Riley Tallman, Yankai Zeng, Manuha Vancha, Akarshan Sajja, Chitta Baral
    http://arxiv.org/abs/2103.15022v1

    • [cs.CL]A More Fine-Grained Aspect-Sentiment-Opinion Triplet Extraction Task
    Fang Wang, Yuncong Li, Wenjun Zhang, Sheng-hua Zhong
    http://arxiv.org/abs/2103.15255v1

    • [cs.CL]Abuse is Contextual, What about NLP? The Role of Context in Abusive Language Annotation and Detection
    Stefano Menini, Alessio Palmero Aprosio, Sara Tonelli
    http://arxiv.org/abs/2103.14916v1

    • [cs.CL]An Automated Multiple-Choice Question Generation Using Natural Language Processing Techniques
    Chidinma A. Nwafor, Ikechukwu E. Onyenwe
    http://arxiv.org/abs/2103.14757v1

    • [cs.CL]Annotating Hate and Offenses on Social Media
    Francielle Alves Vargas, Isabelle Carvalho, Fabiana Rodrigues de Góes, Fabrício Benevenuto de Souza, Thiago Alexandre Salgueiro Pardo
    http://arxiv.org/abs/2103.14972v1

    • [cs.CL]Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP Models
    Wenkai Yang, Lei Li, Zhiyuan Zhang, Xuancheng Ren, Xu Sun, Bin He
    http://arxiv.org/abs/2103.15543v1

    • [cs.CL]CaSiNo: A Corpus of Campsite Negotiation Dialogues for Automatic Negotiation Systems
    Kushal Chawla, Jaysa Ramirez, Rene Clever, Gale Lucas, Jonathan May, Jonathan Gratch
    http://arxiv.org/abs/2103.15721v1

    • [cs.CL]Centrality Meets Centroid: A Graph-based Approach for Unsupervised Document Summarization
    Haopeng Zhang, Jiawei Zhang
    http://arxiv.org/abs/2103.15327v1

    • [cs.CL]Changing the Mind of Transformers for Topically-Controllable Language Generation
    Haw-Shiuan Chang, Jiaming Yuan, Mohit Iyyer, Andrew McCallum
    http://arxiv.org/abs/2103.15335v1

    • [cs.CL]English-Twi Parallel Corpus for Machine Translation
    Paul Azunre, Salomey Osei, Salomey Addo, Lawrence Asamoah Adu-Gyamfi, Stephen Moore, Bernard Adabankah, Bernard Opoku, Clara Asare-Nyarko, Samuel Nyarko, Cynthia Amoaba, Esther Dansoa Appiah, Felix Akwerh, Richard Nii Lante Lawson, Joel Budu, Emmanuel Debrah, Nana Boateng, Wisdom Ofori, Edwin Buabeng-Munkoh, Franklin Adjei, Isaac Kojo Essel Ampomah, Joseph Otoo, Reindorf Borkor, Standylove Birago Mensah, Lucien Mensah, Mark Amoako Marcel, Anokye Acheampong Amponsah, James Ben Hayfron-Acquah
    http://arxiv.org/abs/2103.15625v1

    • [cs.CL]Explaining the Road Not Taken
    Hua Shen, Ting-Hao, Huang
    http://arxiv.org/abs/2103.14973v1

    • [cs.CL]Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications
    Haw-Shiuan Chang, Amol Agrawal, Andrew McCallum
    http://arxiv.org/abs/2103.15330v1

    • [cs.CL]InsertGNN: Can Graph Neural Networks Outperform Humans in TOEFL Sentence Insertion Problem?
    Fang Wu, Xiang Bai
    http://arxiv.org/abs/2103.15066v1

    • [cs.CL]LSTM Based Sentiment Analysis for Cryptocurrency Prediction
    Xin Huang, Wenbin Zhang, Yiyi Huang, Xuejiao Tang, Mingli Zhang, Jayachander Surbiryala, Vasileios Iosifidis, Zhen Liu, Ji Zhang
    http://arxiv.org/abs/2103.14804v1

    • [cs.CL]Multi-facet Universal Schema
    Rohan Paul, Haw-Shiuan Chang, Andrew McCallum
    http://arxiv.org/abs/2103.15339v1

    • [cs.CL]Multiple-hypothesis CTC-based semi-supervised adaptation of end-to-end speech recognition
    Cong-Thanh Do, Rama Doddipatla, Thomas Hain
    http://arxiv.org/abs/2103.15515v1

    • [cs.CL]NLP for Ghanaian Languages
    Paul Azunre, Salomey Osei, Salomey Addo, Lawrence Asamoah Adu-Gyamfi, Stephen Moore, Bernard Adabankah, Bernard Opoku, Clara Asare-Nyarko, Samuel Nyarko, Cynthia Amoaba, Esther Dansoa Appiah, Felix Akwerh, Richard Nii Lante Lawson, Joel Budu, Emmanuel Debrah, Nana Boateng, Wisdom Ofori, Edwin Buabeng-Munkoh, Franklin Adjei, Isaac Kojo Essel Ampomah, Joseph Otoo, Reindorf Borkor, Standylove Birago Mensah, Lucien Mensah, Mark Amoako Marcel, Anokye Acheampong Amponsah, James Ben Hayfron-Acquah
    http://arxiv.org/abs/2103.15475v1

    • [cs.CL]On Hallucination and Predictive Uncertainty in Conditional Language Generation
    Yijun Xiao, William Yang Wang
    http://arxiv.org/abs/2103.15025v1

    • [cs.CL]PENELOPIE: Enabling Open Information Extraction for the Greek Language through Machine Translation
    Dimitris Papadopoulos, Nikolaos Papadakis, Nikolaos Matsatsinis
    http://arxiv.org/abs/2103.15075v1

    • [cs.CL]PnG BERT: Augmented BERT on Phonemes and Graphemes for Neural TTS
    Ye Jia, Heiga Zen, Jonathan Shen, Yu Zhang, Yonghui Wu
    http://arxiv.org/abs/2103.15060v1

    • [cs.CL]Retrieving Event-related Human Brain Dynamics from Natural Sentence Reading
    Xinping Liu, Zehong Cao
    http://arxiv.org/abs/2103.15500v1

    • [cs.CL]Shrinking Bigfoot: Reducing wav2vec 2.0 footprint
    Zilun Peng, Akshay Budhkar, Ilana Tuil, Jason Levy, Parinaz Sobhani, Raphael Cohen, Jumana Nassour
    http://arxiv.org/abs/2103.15760v1

    • [cs.CL]Supersense and Sensibility: Proxy Tasks for Semantic Annotation of Prepositions
    Luke Gessler, Shira Wein, Nathan Schneider
    http://arxiv.org/abs/2103.14961v1

    • [cs.CL]Unsupervised Self-Training for Sentiment Analysis of Code-Switched Data
    Akshat Gupta, Sargam Menghani, Sai Krishna Rallabandi, Alan W Black
    http://arxiv.org/abs/2103.14797v1

    • [cs.CL]Whitening Sentence Representations for Better Semantics and Faster Retrieval
    Jianlin Su, Jiarun Cao, Weijie Liu, Yangyiwen Ou
    http://arxiv.org/abs/2103.15316v1

    • [cs.CL]You Can Do Better! If You Elaborate the Reason When Making Prediction
    Dongfang Li, Jingcong Tao, Qingcai Chen, Baotian Hu
    http://arxiv.org/abs/2103.14919v1

    • [cs.CR]Leaky Nets: Recovering Embedded Neural Network Models and Inputs through Simple Power and Timing Side-Channels — Attacks and Defenses
    Saurav Maji, Utsav Banerjee, Anantha P. Chandrakasan
    http://arxiv.org/abs/2103.14739v1

    • [cs.CR]Privacy and Trust Redefined in Federated Machine Learning
    Pavlos Papadopoulos, Will Abramson, Adam J. Hall, Nikolaos Pitropakis, William J. Buchanan
    http://arxiv.org/abs/2103.15753v1

    • [cs.CR]Secure Platform for Processing Sensitive Data on Shared HPC Systems
    Michel Scheerman, Narges Zarrabi, Martijn Kruiten, Maxime Mogé, Lykle Voort, Annette Langedijk, Ruurd Schoonhoven, Tom Emery
    http://arxiv.org/abs/2103.14679v1

    • [cs.CV]A Dataset and Benchmark Towards Multi-Modal Face Anti-Spoofing Under Surveillance Scenarios
    Xudong Chen, Shugong Xu, Qiaobin Ji, Shan Cao
    http://arxiv.org/abs/2103.15409v1

    • [cs.CV]A Hierarchical Approach to Remote Sensing Scene Classification
    Ozlem Sen, Hacer Yalim Keles
    http://arxiv.org/abs/2103.15463v1

    • [cs.CV]A Model-Based Approach to Synthetic Data Set Generation for Patient-Ventilator Waveforms for Machine Learning and Educational Use
    A. van Diepen, T. H. G. F. Bakkes, A. J. R. De Bie, S. Turco, R. A. Bouwman, P. H. Woerlee, M. Mischi
    http://arxiv.org/abs/2103.15684v1

    • [cs.CV]A Survey of Orthogonal Moments for Image Representation: Theory, Implementation, and Evaluation
    Shuren Qi, Yushu Zhang, Chao Wang, Jiantao Zhou, Xiaochun Cao
    http://arxiv.org/abs/2103.14799v1

    • [cs.CV]ACSNet: Action-Context Separation Network for Weakly Supervised Temporal Action Localization
    Ziyi Liu, Le Wang, Qilin Zhang, Wei Tang, Junsong Yuan, Nanning Zheng, Gang Hua
    http://arxiv.org/abs/2103.15088v1

    • [cs.CV]AR Mapping: Accurate and Efficient Mapping for Augmented Reality
    Rui Huang, Chuan Fang, Kejie Qiu, Le Cui, Zilong Dong, Siyu Zhu, Ping Tan
    http://arxiv.org/abs/2103.14846v1

    • [cs.CV]Adaptive Boosting for Domain Adaptation: Towards Robust Predictions in Scene Segmentation
    Zhedong Zheng, Yi Yang
    http://arxiv.org/abs/2103.15685v1

    • [cs.CV]Adaptive Methods for Real-World Domain Generalization
    Abhimanyu Dubey, Vignesh Ramanathan, Alex Pentland, Dhruv Mahajan
    http://arxiv.org/abs/2103.15796v1

    • [cs.CV]Adaptive Surface Normal Constraint for Depth Estimation
    Xiaoxiao Long, Cheng Lin, Lingjie Liu, Wei Li, Christian Theobalt, Ruigang Yang, Wenping Wang
    http://arxiv.org/abs/2103.15483v1

    • [cs.CV]Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Framework
    Dimitrios Kollias, Stefanos Zafeiriou
    http://arxiv.org/abs/2103.15792v1

    • [cs.CV]AlignMix: Improving representation by interpolating aligned features
    Shashanka Venkataramanan, Yannis Avrithis, Ewa Kijak, Laurent Amsaleg
    http://arxiv.org/abs/2103.15375v1

    • [cs.CV]An Adversarial Human Pose Estimation Network Injected with Graph Structure
    Lei Tian, Guoqiang Liang, Peng Wang, Chunhua Shen
    http://arxiv.org/abs/2103.15534v1

    • [cs.CV]An Efficiently Coupled Shape and Appearance Prior for Active Contour Segmentation
    Martin Mueller, Navdeep Dahiya, Anthony Yezzi
    http://arxiv.org/abs/2103.14887v1

    • [cs.CV]Attention to Warp: Deep Metric Learning for Multivariate Time Series
    Shinnosuke Matsuo, Xiaomeng Wu, Gantugs Atarsaikhan, Akisato Kimura, Kunio Kashino, Brian Kenji Iwana, Seiichi Uchida
    http://arxiv.org/abs/2103.15074v1

    • [cs.CV]Attention-guided Image Compression by Deep Reconstruction of Compressive Sensed Saliency Skeleton
    Xi Zhang, Xiaolin Wu
    http://arxiv.org/abs/2103.15368v1

    • [cs.CV]Automated Backend-Aware Post-Training Quantization
    Ziheng Jiang, Animesh Jain, Andrew Liu, Josh Fromm, Chengqian Ma, Tianqi Chen, Luis Ceze
    http://arxiv.org/abs/2103.14949v1

    • [cs.CV]Automated freezing of gait assessment with marker-based motion capture and deep learning approaches expert-level detection
    Benjamin Filtjens, Pieter Ginis, Alice Nieuwboer, Peter Slaets, Bart Vanrumste
    http://arxiv.org/abs/2103.15449v1

    • [cs.CV]BA^2M: A Batch Aware Attention Module for Image Classification
    Qishang Cheng, Hongliang Li, Qingbo Wu, King Ngi Ngan
    http://arxiv.org/abs/2103.15099v1

    • [cs.CV]Bayesian Deep Basis Fitting for Depth Completion with Uncertainty
    Chao Qu, Wenxin Liu, Camillo J. Taylor
    http://arxiv.org/abs/2103.15254v1

    • [cs.CV]Bridging Vision and Language from the Video-to-Text Perspective: A Comprehensive Review
    Jesus Perez-Martin, Benjamin Bustos, Silvio Jamil F. Guimarães, Ivan Sipiran, Jorge Pérez, Grethel Coello Said
    http://arxiv.org/abs/2103.14785v1

    • [cs.CV]Bridging the Visual Gap: Wide-Range Image Blending
    Chia-Ni Lu, Ya-Chu Chang, Wei-Chen Chiu
    http://arxiv.org/abs/2103.15149v1

    • [cs.CV]CNN-based search model underestimates attention guidance by simple visual features
    Endel Poder
    http://arxiv.org/abs/2103.15439v1

    • [cs.CV]COVID-19 personal protective equipment detection using real-time deep learning methods
    Shayan Khosravipour, Erfan Taghvaei, Nasrollah Moghadam Charkari
    http://arxiv.org/abs/2103.14878v1

    • [cs.CV]CalibDNN: Multimodal Sensor Calibration for Perception Using Deep Neural Networks
    Ganning Zhao, Jiesi Hu, Suya You, C. -C. Jay Kuo
    http://arxiv.org/abs/2103.14793v1

    • [cs.CV]Capsule Network is Not More Robust than Convolutional Network
    Jindong Gu, Volker Tresp, Han Hu
    http://arxiv.org/abs/2103.15459v1

    • [cs.CV]Classification of Seeds using Domain Randomization on Self-Supervised Learning Frameworks
    Venkat Margapuri, Mitchell Neilsen
    http://arxiv.org/abs/2103.15578v1

    • [cs.CV]Classifying Video based on Automatic Content Detection Overview
    Yilin Wang, Jiayi Ye
    http://arxiv.org/abs/2103.15323v1

    • [cs.CV]Cloth-Changing Person Re-identification from A Single Image with Gait Prediction and Regularization
    Xin Jin, Tianyu He, Kecheng Zheng, Zhiheng Yin, Xu Shen, Zhen Huang, Ruoyu Feng, Jianqiang Huang, Xian-Sheng Hua, Zhibo Chen
    http://arxiv.org/abs/2103.15537v1

    • [cs.CV]Cloud2Curve: Generation and Vectorization of Parametric Sketches
    Ayan Das, Yongxin Yang, Timothy Hospedales, Tao Xiang, Yi-Zhe Song
    http://arxiv.org/abs/2103.15536v1

    • [cs.CV]Context Modeling in 3D Human Pose Estimation: A Unified Perspective
    Xiaoxuan Ma, Jiajun Su, Chunyu Wang, Hai Ci, Yizhou Wang
    http://arxiv.org/abs/2103.15507v1

    • [cs.CV]Contextual Scene Augmentation and Synthesis via GSACNet
    Mohammad Keshavarzi, Flaviano Christian Reyes, Ritika Shrivastava, Oladapo Afolabi, Luisa Caldas, Allen Y. Yang
    http://arxiv.org/abs/2103.15369v1

    • [cs.CV]CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification
    Chun-Fu Chen, Quanfu Fan, Rameswar Panda
    http://arxiv.org/abs/2103.14899v1

    • [cs.CV]CvT: Introducing Convolutions to Vision Transformers
    Haiping Wu, Bin Xiao, Noel Codella, Mengchen Liu, Xiyang Dai, Lu Yuan, Lei Zhang
    http://arxiv.org/abs/2103.15808v1

    • [cs.CV]Deep Ensemble Collaborative Learning by using Knowledge-transfer Graph for Fine-grained Object Classification
    Naoki Okamoto, Soma Minami, Tsubasa Hirakawa, Takayoshi Yamashita, Hironobu Fujiyoshi
    http://arxiv.org/abs/2103.14845v1

    • [cs.CV]Deep Image Compositing
    Shivangi Aneja, Soham Mazumder
    http://arxiv.org/abs/2103.15446v1

    • [cs.CV]Deep Learning Techniques for In-Crop Weed Identification: A Review
    Kun Hu, Zhiyong Wang, Guy Coleman, Asher Bender, Tingting Yao, Shan Zeng, Dezhen Song, Arnold Schumann, Michael Walsh
    http://arxiv.org/abs/2103.14872v1

    • [cs.CV]Defect-GAN: High-Fidelity Defect Synthesis for Automated Defect Inspection
    Gongjie Zhang, Kaiwen Cui, Tzu-Yi Hung, Shijian Lu
    http://arxiv.org/abs/2103.15158v1

    • [cs.CV]Distilling Virtual Examples for Long-tailed Recognition
    Yin-Yin He, Jianxin Wu, Xiu-Shen Wei
    http://arxiv.org/abs/2103.15042v1

    • [cs.CV]Drop the GAN: In Defense of Patches Nearest Neighbors as Single Image Generative Models
    Niv Granot, Assaf Shocher, Ben Feinstein, Shai Bagon, Michal Irani
    http://arxiv.org/abs/2103.15545v1

    • [cs.CV]Elsa: Energy-based learning for semi-supervised anomaly detection
    Sungwon Han, Hyeonho Song, Seungeon Lee, Sungwon Park, Meeyoung Cha
    http://arxiv.org/abs/2103.15296v1

    • [cs.CV]Embedding Transfer with Label Relaxation for Improved Metric Learning
    Sungyeon Kim, Dongwon Kim, Minsu Cho, Suha Kwak
    http://arxiv.org/abs/2103.14908v1

    • [cs.CV]Enhanced Boundary Learning for Glass-like Object Segmentation
    Hao He, Xiangtai Li, Guangliang Cheng, Jianping Shi, Yunhai Tong, Gaofeng Meng, Véronique Prinet, Lubin Weng
    http://arxiv.org/abs/2103.15734v1

    • [cs.CV]Equivariant Imaging: Learning Beyond the Range Space
    Dongdong Chen, Julián Tachella, Mike E. Davies
    http://arxiv.org/abs/2103.14756v1

    • [cs.CV]Evaluation of Correctness in Unsupervised Many-to-Many Image Translation
    Dina Bashkirova, Ben Usman, Kate Saenko
    http://arxiv.org/abs/2103.15727v1

    • [cs.CV]Exploiting Local Geometry for Feature and Graph Construction for Better 3D Point Cloud Processing with Graph Neural Networks
    Siddharth Srivastava, Gaurav Sharma
    http://arxiv.org/abs/2103.15226v1

    • [cs.CV]Face Recognition as a Method of Authentication in a Web-Based System
    Ben Wycliff Mugalu, Rodrick Calvin Wamala, Jonathan Serugunda, Andrew Katumba
    http://arxiv.org/abs/2103.15144v1

    • [cs.CV]Face Transformer for Recognition
    Yaoyao Zhong, Weihong Deng
    http://arxiv.org/abs/2103.14803v1

    • [cs.CV]Few-Shot Learning for Video Object Detection in a Transfer-Learning Scheme
    Zhongjie Yu, Gaoang Wang, Lin Chen, Sebastian Raschka, Jiebo Luo
    http://arxiv.org/abs/2103.14724v1

    • [cs.CV]Few-shot Semantic Image Synthesis Using StyleGAN Prior
    Yuki Endo, Yoshihiro Kanamori
    http://arxiv.org/abs/2103.14877v1

    • [cs.CV]FocusedDropout for Convolutional Neural Network
    Tianshu Xie, Minghui Liu, Jiali Deng, Xuan Cheng, Xiaomin Wang, Ming Liu
    http://arxiv.org/abs/2103.15425v1

    • [cs.CV]Fooling LiDAR Perception via Adversarial Trajectory Perturbation
    Yiming Li, Congcong Wen, Felix Juefei-Xu, Chen Feng
    http://arxiv.org/abs/2103.15326v1

    • [cs.CV]Friends and Foes in Learning from Noisy Labels
    Yifan Zhou, Yifan Ge, Jianxin Wu
    http://arxiv.org/abs/2103.15055v1

    • [cs.CV]From Synthetic to Real: Unsupervised Domain Adaptation for Animal Pose Estimation
    Chen Li, Gim Hee Lee
    http://arxiv.org/abs/2103.14843v1

    • [cs.CV]GNeRF: GAN-based Neural Radiance Field without Posed Camera
    Quan Meng, Anpei Chen, Haimin Luo, Minye Wu, Hao Su, Lan Xu, Xuming He, Jingyi Yu
    http://arxiv.org/abs/2103.15606v1

    • [cs.CV]Generalizing to the Open World: Deep Visual Odometry with Online Adaptation
    Shunkai Li, Xin Wu, Yingdian Cao, Hongbin Zha
    http://arxiv.org/abs/2103.15279v1

    • [cs.CV]Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers
    Hila Chefer, Shir Gur, Lior Wolf
    http://arxiv.org/abs/2103.15679v1

    • [cs.CV]Get away from Style: Category-Guided Domain Adaptation for Semantic Segmentation
    Yantian Luo, Zhiming Wang, Danlan Huang, Ning Ge, Jianhua Lu
    http://arxiv.org/abs/2103.15467v1

    • [cs.CV]Going Deeper Into Face Detection: A Survey
    Shervin Minaee, Ping Luo, Zhe Lin, Kevin Bowyer
    http://arxiv.org/abs/2103.14983v1

    • [cs.CV]Graph-based Facial Affect Analysis: A Review of Methods, Applications and Challenges
    Yang Liu, Jinzhao Zhou, Xin Li, Xingming Zhang, Guoying Zhao
    http://arxiv.org/abs/2103.15599v1

    • [cs.CV]H-GAN: the power of GANs in your Hands
    Sergiu Oprea, Giorgos Karvounas, Pablo Martinez-Gonzalez, Nikolaos Kyriazis, Sergio Orts-Escolano, Iason Oikonomidis, Alberto Garcia-Garcia, Aggeliki Tsoli, Jose Garcia-Rodriguez, Antonis Argyros
    http://arxiv.org/abs/2103.15017v1

    • [cs.CV]HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset
    Guanying Chen, Chaofeng Chen, Shi Guo, Zhetong Liang, Kwan-Yee K. Wong, Lei Zhang
    http://arxiv.org/abs/2103.14943v1

    • [cs.CV]HiT: Hierarchical Transformer with Momentum Contrast for Video-Text Retrieval
    Song Liu, Haoqi Fan, Shengsheng Qian, Yiru Chen, Wenkui Ding, Zhongyuan Wang
    http://arxiv.org/abs/2103.15049v1

    • [cs.CV]High-Fidelity and Arbitrary Face Editing
    Yue Gao, Fangyun Wei, Jianmin Bao, Shuyang Gu, Dong Chen, Fang Wen, Zhouhui Lian
    http://arxiv.org/abs/2103.15814v1

    • [cs.CV]HumanGPS: Geodesic PreServing Feature for Dense Human Correspondences
    Feitong Tan, Danhang Tang, Mingsong Dou, Kaiwen Guo, Rohit Pandey, Cem Keskin, Ruofei Du, Deqing Sun, Sofien Bouaziz, Sean Fanello, Ping Tan, Yinda Zhang
    http://arxiv.org/abs/2103.15573v1

    • [cs.CV]IA-GCN: Interpretable Attention based Graph Convolutional Network for Disease prediction
    Anees Kazi, Soroush Farghadani, Nassir Navab
    http://arxiv.org/abs/2103.15587v1

    • [cs.CV]Image Processing Techniques for identifying tumors in an MRI image
    Jacob John
    http://arxiv.org/abs/2103.15152v1

    • [cs.CV]Imponderous Net for Facial Expression Recognition in the Wild
    Darshan Gera, S. Balasubramanian
    http://arxiv.org/abs/2103.15136v1

    • [cs.CV]Instance segmentation with the number of clusters incorporated in embedding learning
    Jianfeng Cao, Hong Yan
    http://arxiv.org/abs/2103.14869v1

    • [cs.CV]IoU Attack: Towards Temporally Coherent Black-Box Adversarial Attack for Visual Object Tracking
    Shuai Jia, Yibing Song, Chao Ma, Xiaokang Yang
    http://arxiv.org/abs/2103.14938v1

    • [cs.CV]Knowing What VQA Does Not: Pointing to Error-Inducing Regions to Improve Explanation Helpfulness
    Arijit Ray, Michael Cogswell, Xiao Lin, Kamran Alipour, Ajay Divakaran, Yi Yao, Giedrius Burachas
    http://arxiv.org/abs/2103.14712v1

    • [cs.CV]LSG-CPD: Coherent Point Drift with Local Surface Geometry for Point Cloud Registration
    Weixiao Liu, Hongtao Wu, Gregory Chirikjian
    http://arxiv.org/abs/2103.15039v1

    • [cs.CV]Labels4Free: Unsupervised Segmentation using StyleGAN
    Rameen Abdal, Peihao Zhu, Niloy Mitra, Peter Wonka
    http://arxiv.org/abs/2103.14968v1

    • [cs.CV]LatentKeypointGAN: Controlling GANs via Latent Keypoints
    Xingzhe He, Bastian Wandt, Helge Rhodin
    http://arxiv.org/abs/2103.15812v1

    • [cs.CV]LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis
    Zejiang Shen, Ruochen Zhang, Melissa Dell, Benjamin Charles Germain Lee, Jacob Carlson, Weining Li
    http://arxiv.org/abs/2103.15348v1

    • [cs.CV]Lear
    1000
    ning Placeholders for Open-Set Recognition
    Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan
    http://arxiv.org/abs/2103.15086v1

    • [cs.CV]Learning Efficient Photometric Feature Transform for Multi-view Stereo
    Kaizhang Kang, Cihui Xie, Ruisheng Zhu, Xiaohe Ma, Ping Tan, Hongzhi Wu, Kun Zhou
    http://arxiv.org/abs/2103.14794v1

    • [cs.CV]Learning Generative Models of Textured 3D Meshes from Real-World Images
    Dario Pavllo, Jonas Kohler, Thomas Hofmann, Aurelien Lucchi
    http://arxiv.org/abs/2103.15627v1

    • [cs.CV]Learning a Sketch Tensor Space for Image Inpainting of Man-made Scenes
    Chenjie Cao, Yanwei Fu
    http://arxiv.org/abs/2103.15087v1

    • [cs.CV]Learning to Predict Salient Faces: A Novel Visual-Audio Saliency Model
    Yufan Liu, Minglang Qiao, Mai Xu, Bing Li, Weiming Hu, Ali Borji
    http://arxiv.org/abs/2103.15438v1

    • [cs.CV]LiDAR R-CNN: An Efficient and Universal 3D Object Detector
    Zhichao Li, Feng Wang, Naiyan Wang
    http://arxiv.org/abs/2103.15297v1

    • [cs.CV]Looking Beyond Two Frames: End-to-End Multi-Object Tracking Using Spatial and Temporal Transformers
    Tianyu Zhu, Markus Hiller, Mahsa Ehsanpour, Rongkai Ma, Tom Drummond, Hamid Rezatofighi
    http://arxiv.org/abs/2103.14829v1

    • [cs.CV]Low-Fidelity End-to-End Video Encoder Pre-training for Temporal ActionLocalization
    Mengmeng Xu, Juan-Manuel Perez-Ru, Xiatian Zhu, Bernard Ghanem, Brais Martinez
    http://arxiv.org/abs/2103.15233v1

    • [cs.CV]MVSNeRF: Fast Generalizable Radiance Field Reconstruction from Multi-View Stereo
    Anpei Chen, Zexiang Xu, Fuqiang Zhao, Xiaoshuai Zhang, Fanbo Xiang, Jingyi Yu, Hao Su
    http://arxiv.org/abs/2103.15595v1

    • [cs.CV]ManhattanSLAM: Robust Planar Tracking and Mapping Leveraging Mixture of Manhattan Frames
    Raza Yunus, Yanyan Li, Federico Tombari
    http://arxiv.org/abs/2103.15068v1

    • [cs.CV]Memory Enhanced Embedding Learning for Cross-Modal Video-Text Retrieval
    Rui Zhao, Kecheng Zheng, Zheng-Jun Zha, Hongtao Xie, Jiebo Luo
    http://arxiv.org/abs/2103.15686v1

    • [cs.CV]Meta-Mining Discriminative Samples for Kinship Verification
    Wanhua Li, Shiwei Wang, Jiwen Lu, Jianjiang Feng, Jie Zhou
    http://arxiv.org/abs/2103.15108v1

    • [cs.CV]Mining Latent Classes for Few-shot Segmentation
    Lihe Yang, Wei Zhuo, Lei Qi, Yinghuan Shi, Yang Gao
    http://arxiv.org/abs/2103.15402v1

    • [cs.CV]Monocular 3D Vehicle Detection Using Uncalibrated Traffic Cameras through Homography
    Minghan Zhu, Songan Zhang, Yuanxin Zhong, Pingping Lu, Huei Peng, John Lenneman
    http://arxiv.org/abs/2103.15293v1

    • [cs.CV]Motion Basis Learning for Unsupervised Deep Homography Estimation with Subspace Projection
    Nianjin Ye, Chuan Wang, Haoqiang Fan, Shuaicheng Liu
    http://arxiv.org/abs/2103.15346v1

    • [cs.CV]Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image Encoding
    Pengchuan Zhang, Xiyang Dai, Jianwei Yang, Bin Xiao, Lu Yuan, Lei Zhang, Jianfeng Gao
    http://arxiv.org/abs/2103.15358v1

    • [cs.CV]NeMI: Unifying Neural Radiance Fields with Multiplane Images for Novel View Synthesis
    Jiaxin Li, Zijian Feng, Qi She, Henghui Ding, Changhu Wang, Gim Hee Lee
    http://arxiv.org/abs/2103.14910v1

    • [cs.CV]No frame left behind: Full Video Action Recognition
    Xin Liu, Silvia L. Pintea, Fatemeh Karimi Nejadasl, Olaf Booij, Jan C. van Gemert
    http://arxiv.org/abs/2103.15395v1

    • [cs.CV]Noise Injection-based Regularization for Point Cloud Processing
    Xiao Zang, Yi Xie, Siyu Liao, Jie Chen, Bo Yuan
    http://arxiv.org/abs/2103.15027v1

    • [cs.CV]OLED: One-Class Learned Encoder-Decoder Network with Adversarial Context Masking for Novelty Detection
    John Taylor Jewell, Vahid Reza Khazaie, Yalda Mohsenzadeh
    http://arxiv.org/abs/2103.14953v1

    • [cs.CV]On Development and Evaluation of Retargeting Human Motion and Appearance in Monocular Videos
    Thiago L. Gomes, Renato Martins, João Ferreira, Rafael Azevedo, Guilherme Torres, Erickson R. Nascimento
    http://arxiv.org/abs/2103.15596v1

    • [cs.CV]On the Adversarial Robustness of Visual Transformers
    Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh
    http://arxiv.org/abs/2103.15670v1

    • [cs.CV]Onfocus Detection: Identifying Individual-Camera Eye Contact from Unconstrained Images
    Dingwen Zhang, Bo Wang, Gerong Wang, Qiang Zhang, Jiajia Zhang, Jungong Han, Zheng You
    http://arxiv.org/abs/2103.15307v1

    • [cs.CV]POSEFusion: Pose-guided Selective Fusion for Single-view Human Volumetric Capture
    Zhe Li, Tao Yu, Zerong Zheng, Kaiwen Guo, Yebin Liu
    http://arxiv.org/abs/2103.15331v1

    • [cs.CV]Panoptic-PolarNet: Proposal-free LiDAR Point Cloud Panoptic Segmentation
    Zixiang Zhou, Yang Zhang, Hassan Foroosh
    http://arxiv.org/abs/2103.14962v1

    • [cs.CV]PeaceGAN: A GAN-based Multi-Task Learning Method for SAR Target Image Generation with a Pose Estimator and an Auxiliary Classifier
    Jihyong Oh, Munchurl Kim
    http://arxiv.org/abs/2103.15469v1

    • [cs.CV]Picasso: A CUDA-based Library for Deep Learning over 3D Meshes
    Huan Lei, Naveed Akhtar, Ajmal Mian
    http://arxiv.org/abs/2103.15076v1

    • [cs.CV]PixelTransformer: Sample Conditioned Signal Generation
    Shubham Tulsiani, Abhinav Gupta
    http://arxiv.org/abs/2103.15813v1

    • [cs.CV]PlaneSegNet: Fast and Robust Plane Estimation Using a Single-stage Instance Segmentation CNN
    Yaxu Xie, Jason Rambach, Fangwen Shu, Didier Stricker
    http://arxiv.org/abs/2103.15428v1

    • [cs.CV]Proxy Synthesis: Learning with Synthetic Classes for Deep Metric Learning
    Geonmo Gu, Byungsoo Ko, Han-Gyu Kim
    http://arxiv.org/abs/2103.15454v1

    • [cs.CV]ReAgent: Point Cloud Registration using Imitation and Reinforcement Learning
    Dominik Bauer, Timothy Patten, Markus Vincze
    http://arxiv.org/abs/2103.15231v1

    • [cs.CV]Realistic face animation generation from videos
    Zihao Jian, Minshan Xie
    http://arxiv.org/abs/2103.14984v1

    • [cs.CV]Remote Sensing Image Translation via Style-Based Recalibration Module and Improved Style Discriminator
    Tiange Zhang, Feng Gao, Junyu Dong, Qian Du
    http://arxiv.org/abs/2103.15502v1

    • [cs.CV]Representation, Analysis of Bayesian Refinement Approximation Network: A Survey
    Ningbo Zhu, Fei Yang
    http://arxiv.org/abs/2103.14896v1

    • [cs.CV]Rethinking ResNets: Improved Stacking Strategies With High Order Schemes
    Zhengbo Luo, Zitang Sun, Weilian Zhou, Sei-ichiro Kamata
    http://arxiv.org/abs/2103.15244v1

    • [cs.CV]RobustNet: Improving Domain Generalization in Urban-Scene Segmentation via Instance Selective Whitening
    Sungha Choi, Sanghun Jung, Huiwon Yun, Joanne Kim, Seungryong Kim, Jaegul Choo
    http://arxiv.org/abs/2103.15597v1

    • [cs.CV]SIENet: Spatial Information Enhancement Network for 3D Object Detection from Point Cloud
    Ziyu Li, Yuncong Yao, Zhibin Quan, Wankou Yang, Jin Xie
    http://arxiv.org/abs/2103.15396v1

    • [cs.CV]SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences
    Shun-Cheng Wu, Johanna Wald, Keisuke Tateno, Nassir Navab, Federico Tombari
    http://arxiv.org/abs/2103.14898v1

    • [cs.CV]Selective Output Smoothing Regularization: Regularize Neural Networks by Softening Output Distributions
    Xuan Cheng, Tianshu Xie, Xiaomin Wang, Qifeng Weng, Minghui Liu, Jiali Deng, Ming Liu
    http://arxiv.org/abs/2103.15383v1

    • [cs.CV]Self-Supervised Visibility Learning for Novel View Synthesis
    Yujiao Shi, Hongdong Li, Xin Yu
    http://arxiv.org/abs/2103.15407v1

    • [cs.CV]SelfGait: A Spatiotemporal Representation Learning Method for Self-supervised Gait Recognition
    Yiqun Liu, Yi Zeng, Jian Pu, Hongming Shan, Peiyang He, Junping Zhang
    http://arxiv.org/abs/2103.14811v1

    • [cs.CV]Single Object Tracking through a Fast and Effective Single-Multiple Model Convolutional Neural Network
    Faraz Lotfi, Hamid D. Taghirad
    http://arxiv.org/abs/2103.15105v1

    • [cs.CV]Structure of Multiple Mirror System from Kaleidoscopic Projections of Single 3D Point
    Kosuke Takahashi, Shohei Nobuhara
    http://arxiv.org/abs/2103.15501v1

    • [cs.CV]StyleMeUp: Towards Style-Agnostic Sketch-Based Image Retrieval
    Aneeshan Sain, Ayan Kumar Bhunia, Yongxin Yang and, Tao Xiang, Yi-Zhe Song
    http://arxiv.org/abs/2103.15706v1

    • [cs.CV]TFPose: Direct Human Pose Estimation with Transformers
    Weian Mao, Yongtao Ge, Chunhua Shen, Zhi Tian, Xinlong Wang, Zhibin Wang
    http://arxiv.org/abs/2103.15320v1

    • [cs.CV]TS-CAM: Token Semantic Coupled Attention Map for Weakly Supervised Object Localization
    Wei Gao, Fang Wan, Xingjia Pan, Zhiliang Peng, Qi Tian, Zhenjun Han, Bolei Zhou, Qixiang Ye
    http://arxiv.org/abs/2103.14862v1

    • [cs.CV]Towards High Fidelity Monocular Face Reconstruction with Rich Reflectance using Self-supervised Learning and Ray Tracing
    Abdallah Dib, Cedric Thebault, Junghyun Ahn, Philippe-Henri Gosselin, Christian Theobalt, Louis Chevallier
    http://arxiv.org/abs/2103.15432v1

    • [cs.CV]Tracking 6-DoF Object Motion from Events and Frames
    Haolong Li, Joerg Stueckler
    http://arxiv.org/abs/2103.15568v1

    • [cs.CV]Tracking Based Semi-Automatic Annotation for Scene Text Videos
    Jiajun Zhu, Xiufeng Jiang, Zhiwei Jia, Shugong Xu, Shan Cao
    http://arxiv.org/abs/2103.15488v1

    • [cs.CV]TrafficQA: A Question Answering Benchmark and an Efficient Network for Video Reasoning over Traffic Events
    Li Xu, He Huang, Jun Liu
    http://arxiv.org/abs/2103.15538v1

    • [cs.CV]TransCenter: Transformers with Dense Queries for Multiple-Object Tracking
    Yihong Xu, Yutong Ban, Guillaume Delorme, Chuang Gan, Daniela Rus, Xavier Alameda-Pineda
    http://arxiv.org/abs/2103.15145v1

    • [cs.CV]Transformer Tracking
    Xin Chen, Bin Yan, Jiawen Zhu, Dong Wang, Xiaoyun Yang, Huchuan Lu
    http://arxiv.org/abs/2103.15436v1

    • [cs.CV]Transitive Learning: Exploring the Transitivity of Degradations for Blind Super-Resolution
    Yuanfei Huang, Jie Li, Yanting Hu, Xinbo Gao, Wen Lu
    http://arxiv.org/abs/2103.15290v1

    • [cs.CV]Unified Graph Structured Models for Video Understanding
    Anurag Arnab, Chen Sun, Cordelia Schmid
    http://arxiv.org/abs/2103.15662v1

    • [cs.CV]Unified Shape and SVBRDF Recovery using Differentiable Monte Carlo Rendering
    Fujun Luan, Shuang Zhao, Kavita Bala, Zhao Dong
    http://arxiv.org/abs/2103.15208v1

    • [cs.CV]ViViT: A Video Vision Transformer
    Anurag Arnab, Mostafa Dehghani, Georg Heigold, Chen Sun, Mario Lučić, Cordelia Schmid
    http://arxiv.org/abs/2103.15691v1

    • [cs.CV]Video Classification with FineCoarse Networks
    Guoxi Huang, Adrian G. Bors
    http://arxiv.org/abs/2103.15584v1

    • [cs.CV]Video Rescaling Networks with Joint Optimization Strategies for Downscaling and Upscaling
    Yan-Cheng Huang, Yi-Hsin Chen, Cheng-You Lu, Hui-Po Wang, Wen-Hsiao Peng, Ching-Chun Huang
    http://arxiv.org/abs/2103.14858v1

    • [cs.CV]Visual Distant Supervision for Scene Graph Generation
    Yuan Yao, Ao Zhang, Xu Han, Mengdi Li, Cornelius Weber, Zhiyuan Liu, Stefan Wermter, Maosong Sun
    http://arxiv.org/abs/2103.15365v1

    • [cs.CV]Zero-shot Adversarial Quantization
    Yuang Liu, Wei Zhang, Jun Wang
    http://arxiv.org/abs/2103.15263v1

    • [cs.CY]A trustable and interoperable decentralized solution for citizen-centric and cross-border eGovernance: A conceptual approach
    George Domalis, Nikos Karacapilidis, Dimitris Tsakalidis, Anastasios Giannaros
    http://arxiv.org/abs/2103.15458v1

    • [cs.CY]Acceptance of COVID-19 Vaccine and Its Determinants in Bangladesh
    Sultan Mahmud, Md. Mohsin, Ijaz Ahmed Khan, Ashraf Uddin Mian, Miah Akib Zaman
    http://arxiv.org/abs/2103.15206v1

    • [cs.CY]Should College Dropout Prediction Models Include Protected Attributes?
    Renzhe Yu, Hansol Lee, René F. Kizilcec
    http://arxiv.org/abs/2103.15237v1

    • [cs.DB]Cache-Efficient Fork-Processing Patterns on Large Graphs
    Shengliang Lu, Shixuan Sun, Johns Paul, Yuchen Li, Bingsheng He
    http://arxiv.org/abs/2103.14915v1

    • [cs.DC]A cooperative partial snapshot algorithm for checkpoint-rollback recovery of large-scale and dynamic distributed systems and experimental evaluations
    Junya Nakamura, Yonghwan Kim, Yoshiaki Katayama, Toshimitsu Masuzawa
    http://arxiv.org/abs/2103.15285v1

    • [cs.DC]Effective GPU Parallelization of Distributed and Localized Model Predictive Control
    Carmen Amo Alonso, Shih-Hao Tseng
    http://arxiv.org/abs/2103.14990v1

    • [cs.DC]Extending Classic Paxos for High-performance Read-Modify-Write Registers
    Vasilis Gavrielatos, Antonios Katsarakis, Vijay Nagarajan
    http://arxiv.org/abs/2103.14701v1

    • [cs.DC]Large-Scale Approximate k-NN Graph Construction on GPU
    Hui Wang, Wan-Lei Zhao, Xiangxiang Zeng
    http://arxiv.org/abs/2103.15386v1

    • [cs.DC]Loosely-self-stabilizing Byzantine-tolerant Binary Consensus for Signature-free Message-passing Systems
    Chryssis Georgiou, Ioannis Marcoullis, Michel Raynal, Elad Michael Schiller
    http://arxiv.org/abs/2103.14649v1

    • [cs.DC]MT-lib: A Topology-aware Message Transfer Library for Graph500 on Supercomputers
    Xinbiao Gan, Wen Tan
    http://arxiv.org/abs/2103.15024v1

    • [cs.DC]MergeComp: A Compression Scheduler for Scalable Communication-Efficient Distributed Training
    Zhuang Wang, Xinyu Wu, T. S. Eugene Ng
    http://arxiv.org/abs/2103.15195v1

    • [cs.DS]Euler Meets GPU: Practical Graph Algorithms with Theoretical Guarantees
    Adam Polak, Adrian Siwiec, Michał Stobierski
    http://arxiv.org/abs/2103.15217v1

    • [cs.HC]Hand tracking for immersive virtual reality: opportunities and challenges
    Gavin Buckingham
    http://arxiv.org/abs/2103.14853v1

    • [cs.HC]Personalized Affect-Aware Socially Assistive Robot Tutors Aimed at Fostering Social Grit in Children with Autism
    Zhonghao Shi, Manwei Cao, Sophia Pei, Xiaoyang Qiao, Thomas R Groechel, Maja J Matarić
    http://arxiv.org/abs/2103.15256v1

    • [cs.HC]Towards Tool-Support for Interactive-Machine Learning Applications in the Android Ecosystem
    Muhammad Mehran Sunny, Moritz Berghofer, Ilhan Aslan
    http://arxiv.org/abs/2103.14852v1

    • [cs.IR]Community-based Cyberreading for Information Understanding
    Zhuoren Jiang, Xiaozhong Liu, Liangcai Gao, Zhi Tang
    http://arxiv.org/abs/2103.14934v1

    • [cs.IR]Context-aware short-term interest first model for session-based recommendation
    Haomei Duan, Jinghua Zhu
    http://arxiv.org/abs/2103.15514v1

    • [cs.IR]Multi-Facet Recommender Networks with Spherical Optimization
    Yanchao Tan, Carl Yang, Xiangyu Wei, Yun Ma, Xiaolin Zheng
    http://arxiv.org/abs/2103.14866v1

    • [cs.IR]Supporting verification of news articles with automated search for semantically similar articles
    Vishwani Gupta, Katharina Beckh, Sven Giesselbach, Dennis Wegener, Tim Wirtz
    http://arxiv.org/abs/2103.15581v1

    • [cs.IT]A Short Introduction to Information-Theoretic Cost-Benefit Analysis
    Min Chen
    http://arxiv.org/abs/2103.15113v1

    • [cs.IT]A function field approach toward good polynomials for optimal LRC codes
    Ruikai Chen, Sihem Mesnager
    http://arxiv.org/abs/2103.15443v1

    • [cs.IT]Active RIS vs. Passive RIS: Which Will Prevail in 6G?
    Zijian Zhang, Linglong Dai, Xibi Chen, Changhao Liu, Fan Yang, Robert Schober, H. Vincent Poor
    http://arxiv.org/abs/2103.15154v1

    • [cs.IT]Asymptotically Optimal Massey-Like Inequality on Guessing Entropy With Application to Side-Channel Attack Evaluations
    Andrei Tănăsescu, Marios O. Choudary, Olivier Rioul, Pantelimon George Popescu
    http://arxiv.org/abs/2103.15620v1

    • [cs.IT]Explicit Construction of Minimum Storage Rack-Aware Regenerating Codes for All Parameters
    Liyang Zhou, Zhifang Zhang
    http://arxiv.org/abs/2103.15471v1

    • [cs.IT]Hybrid Beamforming Optimization for DOA Estimation Based on the CRB Analysis
    Tian Lin, Xuemeng Zhou, Yu Zhu, Yi Jiang
    http://arxiv.org/abs/2103.15357v1

    • [cs.IT]Performance Analysis of I/Q Imbalance with Hardware Impairments over Fox’s H-Fading Channels
    Yassine Mouchtak, Faissal El Bouanani
    http://arxiv.org/abs/2103.15511v1

    • [cs.IT]Private and Resource-Bounded Locally Decodable Codes for Insertions and Deletions
    Alexander R. Block, Jeremiah Blocki
    http://arxiv.org/abs/2103.14122v2

    • [cs.IT]Spatial Characterization of Electromagnetic Random Channels
    Andrea Pizzo, Luca Sanguinetti, Thomas L. Marzetta
    http://arxiv.org/abs/2103.15666v1

    • [cs.IT]The DoF Region of Order-(K-1) Messages for the K-user MIMO Broadcast Channel with Delayed CSIT
    Tong Zhang, Shuai Wang, Taotao Wang, Rui Wang
    http://arxiv.org/abs/2103.15181v1

    • [cs.IT]Uplink Channel Impulse Response Based Secondary Carrier Prediction
    Prayag Gowgi, Vijaya Yajnanarayana
    http://arxiv.org/abs/2103.15318v1

    • [cs.LG]A Temporal Kernel Approach for Deep Learning with Continuous-time Information
    Da Xu, Chuanwei Ruan, Evren Korpeoglu, Sushant Kumar, Kannan Achan
    http://arxiv.org/abs/2103.15213v1

    • [cs.LG]A nonlinear diffusion method for semi-supervised learning on hypergraphs
    Francesco Tudisco, Konstantin Prokopchik, Austin R. Benson
    http://arxiv.org/abs/2103.14867v1

    • [cs.LG]Accurate and Reliable Forecasting using Stochastic Differential Equations
    Peng Cui, Zhijie Deng, Wenbo Hu, Jun Zhu
    http://arxiv.org/abs/2103.15041v1

    • [cs.LG]An Introduction to Robust Graph Convolutional Networks
    Mehrnaz Najafi, Philip S. Yu
    http://arxiv.org/abs/2103.14807v1

    • [cs.LG]Bayesian Attention Networks for Data Compression
    Michael Tetelman
    http://arxiv.org/abs/2103.15319v1

    • [cs.LG]Categorical Representation Learning: Morphism is All You Need
    Artan Sheshmani, Yizhuang You
    http://arxiv.org/abs/2103.14770v1

    • [cs.LG]ClaRe: Practical Class Incremental Learning By Remembering Previous Class Representations
    Bahram Mohammadi, Mohammad Sabokrou
    http://arxiv.org/abs/2103.15486v1

    • [cs.LG]Co-Imitation Learning without Expert Demonstration
    Kun-Peng Ning, Hu Xu, Kun Zhu, Sheng-Jun Huang
    http://arxiv.org/abs/2103.14823v1

    • [cs.LG]Continuous Conditional Generative Adversarial Networks (cGAN) with Generator Regularization
    Yufeng Zheng, Yunkai Zhang, Zeyu Zheng
    http://arxiv.org/abs/2103.14884v1

    • [cs.LG]Deep reinforcement learning of event-triggered communication and control for multi-agent cooperative transport
    Kazuki Shibata, Tomohiko Jimbo, Takamitsu Matsubara
    http://arxiv.org/abs/2103.15260v1

    • [cs.LG]Efficient Explanations from Empirical Explainers
    Robert Schwarzenberg, Nils Feldhus, Sebastian Möller
    http://arxiv.org/abs/2103.15429v1

    • [cs.LG]Ensemble-in-One: Learning Ensemble within Random Gated Networks for Enhanced Adversarial Robustness
    Yi Cai, Xuefei Ning, Huazhong Yang, Yu Wang
    http://arxiv.org/abs/2103.14795v1

    • [cs.LG]Explaining Representation by Mutual Information
    Lifeng Gu
    http://arxiv.org/abs/2103.15114v1

    • [cs.LG]Exploiting Adam-like Optimization Algorithms to Improve the Performance of Convolutional Neural Networks
    Loris Nanni, Gianluca Maguolo, Alessandra Lumini
    http://arxiv.org/abs/2103.14689v1

    • [cs.LG]FixNorm: Dissecting Weight Decay for Training Deep Neural Networks
    Yucong Zhou, Yunxiao Sun, Zhao Zhong
    http://arxiv.org/abs/2103.15345v1

    • [cs.LG]Generalization over different cellular automata rules learned by a deep feed-forward neural network
    Marcel Aach, Jens Henrik Goebbert, Jenia Jitsev
    http://arxiv.org/abs/2103.14886v1

    • [cs.LG]Graph Classification by Mixture of Diverse Experts
    Fenyu Hu, Liping Wang, Shu Wu, Liang Wang, Tieniu Tan
    http://arxiv.org/abs/2103.15622v1

    • [cs.LG]Graph Unlearning
    Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang
    http://arxiv.org/abs/2103.14991v1

    • [cs.LG]Hierarchical Relationship Alignment Metric Learning
    Lifeng Gu
    http://arxiv.org/abs/2103.15107v1

    • [cs.LG]Human-in-the-loop Handling of Knowledge Drift
    Andrea Bontempelli, Fausto Giunchiglia, Andrea Passerini, Stefano Teso
    http://arxiv.org/abs/2103.14874v1

    • [cs.LG]IUP: An Intelligent Utility Prediction Scheme for Solid-State Fermentation in 5G IoT
    Min Wang, Shanchen Pang, Tong Ding, Sibo Qiao, Xue Zhai, Shuo Wang, Neal N. Xiong, Zhengwen Huang
    http://arxiv.org/abs/2103.15073v1

    • [cs.LG]Improved Autoregressive Modeling with Distribution Smoothing
    Chenlin Meng, Jiaming Song, Yang Song, Shengjia Zhao, Stefano Ermon
    http://arxiv.org/abs/2103.15089v1

    • [cs.LG]Improving Model Robustness by Adaptively Correcting Perturbation Levels with Active Queries
    Kun-Peng Ning, Lue Tao, Songcan Chen, Sheng-Jun Huang
    http://arxiv.org/abs/2103.14824v1

    • [cs.LG]Increasing the Efficiency of Policy Learning for Autonomous Vehicles by Multi-Task Representation Learning
    Eshagh Kargar, Ville Kyrki
    http://arxiv.org/abs/2103.14718v1

    • [cs.LG]KNN, An Underestimated Model for Regional Rainfall Forecasting
    Ning Yu, Timothy Haskins
    http://arxiv.org/abs/2103.15235v1

    • [cs.LG]Lagrangian Objective Function Leads to Improved Unforeseen Attack Generalization in Adversarial Training
    Mohammad Azizmalayeri, Mohammad Hossein Rohban
    http://arxiv.org/abs/2103.15385v1

    • [cs.LG]LiBRe: A Practical Bayesian Approach to Adversarial Detection
    Zhijie Deng, Xiao Yang, Shizhen Xu, Hang Su, Jun Zhu
    http://arxiv.org/abs/2103.14835v1

    • [cs.LG]Local Explanations via Necessity and Sufficiency: Unifying Theory and Practice
    David Watson, Limor Gultchin, Ankur Taly, Luciano Floridi
    http://arxiv.org/abs/2103.14651v1

    • [cs.LG]Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark
    Sharada Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Gražvydas Šemetulskis, João Schapke, Jonas Kubilius, Jurgis Pašukonis, Linas Klimas, Matthew Hausknecht, Patrick MacAlpine, Quang Nhat Tran, Thomas Tumiel, Xiaocheng Tang, Xinwei Chen, Christopher Hesse, Jacob Hilton, William Hebgen Guss, Sahika Genc, John Schulman, Karl Cobbe
    http://arxiv.org/abs/2103.15332v1

    • [cs.LG]Modeling the Nonsmoothness of Modern Neural Networks
    Runze Liu, Chau-Wai Wong, Huaiyu Dai
    http://arxiv.org/abs/2103.14731v1

    • [cs.LG]Multiscale Clustering of Hyperspectral Images Through Spectral-Spatial Diffusion Geometry
    Sam L. Polk, James M. Murphy
    http://arxiv.org/abs/2103.15783v1

    • [cs.LG]On the limits of algorithmic prediction across the globe
    Xingyu Li, Difan Song, Miaozhe Han, Yu Zhang, Rene F. Kizilcec
    http://arxiv.org/abs/2103.15212v1

    • [cs.LG]One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks
    Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang
    http://arxiv.org/abs/2103.15261v1

    • [cs.LG]Pairing Character Classes in a Deathmatch Shooter Game via a Deep-Learning Surrogate Model
    Daniel Karavolos, Antonios Liapis, Georgios N. Yannakakis
    http://arxiv.org/abs/2103.15451v1

    • [cs.LG]Performance Analysis of Out-of-Distribution Detection on Various Trained Neural Networks
    Jens Henriksson, Christian Berger, Markus Borg, Lars Tornberg, Sankar Raman Sathyamoorthy, Cristofer Englund
    http://arxiv.org/abs/2103.15580v1

    • [cs.LG]Private Non-smooth Empirical Risk Minimization and Stochastic Convex Optimization in Subquadratic Steps
    Janardhan Kulkarni, Yin Tat Lee, Daogao Liu
    http://arxiv.org/abs/2103.15352v1

    • [cs.LG]RAN-GNNs: breaking the capacity limits of graph neural networks
    Diego Valsesia, Giulia Fracastoro, Enrico Magli
    http://arxiv.org/abs/2103.15565v1

    • [cs.LG]Rapid Risk Minimization with Bayesian Models Through Deep Learning Approximation
    Mathias Löwe, Jes Frellsen, Per Lunnemann Hansen, Sebastian Risi
    http://arxiv.org/abs/2103.15682v1

    • [cs.LG]Regular Polytope Networks
    Federico Pernici, Matteo Bruni, Claudio Baecchi, Alberto Del Bimbo
    http://arxiv.org/abs/2103.15632v1

    • [cs.LG]Representation Learning by Ranking under multiple tasks
    Lifeng Gu
    http://arxiv.org/abs/2103.15093v1

    • [cs.LG]Rethinking Neural Operations for Diverse Tasks
    Nicholas Roberts, Mikhail Khodak, Tri Dao, Liam Li, Christopher Ré, Ameet Talwalkar
    http://arxiv.org/abs/2103.15798v1

    • [cs.LG]Risk Bounds for Learning via Hilbert Coresets
    Spencer Douglas, Piyush Kumar, R. K. Prasanth
    http://arxiv.org/abs/2103.15569v1

    • [cs.LG]Robust Reinforcement Learning under model misspecification
    Lebin Yu, Jian Wang, Xudong Zhang
    http://arxiv.org/abs/2103.15370v1

    • [cs.LG]Score-oriented loss (SOL) functions
    Francesco Marchetti, Sabrina Guastavino, Michele Piana, Cristina Campi
    http://arxiv.org/abs/2103.15522v1

    • [cs.LG]Self-supervised Discriminative Feature Learning for Multi-view Clustering
    Jie Xu, Yazhou Ren, Huayi Tang, Zhimeng Yang, Lili Pan, Yang Yang, Xiaorong Pu
    http://arxiv.org/abs/2103.15069v1

    • [cs.LG]Self-supervised Graph Neural Networks without explicit negative sampling
    Zekarias T. Kefato, Sarunas Girdzijauskas
    http://arxiv.org/abs/2103.14958v1

    • [cs.LG]SetVAE: Learning Hierarchical Composition for Generative Modeling of Set-Structured Data
    Jinwoo Kim, Jaehoon Yoo, Juho Lee, Seunghoon Hong
    http://arxiv.org/abs/2103.15619v1

    • [cs.LG]Symbolic regression outperforms other models for small data sets
    Casper Wilstrup, Jaan Kasak
    http://arxiv.org/abs/2103.15147v1

    • [cs.LG]Tensor Networks for Multi-Modal Non-Euclidean Data
    Yao Lei Xu, Kriton Konstantinidis, Danilo P. Mandic
    http://arxiv.org/abs/2103.14998v1

    • [cs.LG]The Sample Complexity of Distribution-Free Parity Learning in the Robust Shuffle Model
    Kobbi Nissim, Chao Yan
    http://arxiv.org/abs/2103.15690v1

    • [cs.LG]Thermal transmittance prediction based on the application of artificial neural networks on heat flux method results
    Sanjin Gumbarević, Bojan Milovanović, Mergim Gaši, Marina Bagarić
    http://arxiv.org/abs/2103.14995v1

    • [cs.LG]Understanding the role of importance weighting for deep learning
    Da Xu, Yuting Ye, Chuanwei Ruan
    http://arxiv.org/abs/2103.15209v1

    • [cs.LG]Variational Rejection Particle Filtering
    Rahul Sharma, Soumya Banerjee, Dootika Vats, Piyush Rai
    http://arxiv.org/abs/2103.15343v1

    • [cs.LG]ZeroGrad : Mitigating and Explaining Catastrophic Overfitting in FGSM Adversarial Training
    Zeinab Golgooni, Mehrdad Saberi, Masih Eskandar, Mohammad Hossein Rohban
    http://arxiv.org/abs/2103.15476v1

    • [cs.LG][Reproducibility Report] Rigging the Lottery: Making All Tickets Winners**
    Varun Sundar, Rajat Vadiraj Dwaraknath
    http://arxiv.org/abs/2103.15767v1

    • [cs.LG]von Mises—Fisher Loss: An Exploration of Embedding Geometries for Supervised Learning
    Tyler R. Scott, Andrew C. Gallagher, Michael C. Mozer
    http://arxiv.org/abs/2103.15718v1

    • [cs.LO]On Symmetry and Quantification: A New Approach to Verify Distributed Protocols
    Aman Goel, Karem A. Sakallah
    http://arxiv.org/abs/2103.14831v1

    • [cs.MA]Competing Adaptive Networks
    Stefan Vlaski, Ali H. Sayed
    http://arxiv.org/abs/2103.15664v1

    • [cs.MM]Product semantics translation from brain activity via adversarial learning
    Pan Wang, Zhifeng Gong, Shuo Wang, Hao Dong, Jialu Fan, Ling Li, Peter Childs, Yike Guo
    http://arxiv.org/abs/2103.15602v1

    • [cs.MS]Mathematics of Digital Hyperspace
    Jeremy Kepner, Timothy Davis, Vijay Gadepally, Hayden Jananthan, Lauren Milechin
    http://arxiv.org/abs/2103.15203v1

    • [cs.NE]Collocation Polynomial Neural Forms and Domain Fragmentation for Initial Value Problems
    Toni Schneidereit, Michael Breuß
    http://arxiv.org/abs/2103.15413v1

    • [cs.NE]Determination of weight coefficients for additive fitness function of genetic algorithm
    V. K. Ivanov, D. S. Dumina, N. A. Semenov
    http://arxiv.org/abs/2103.14833v1

    • [cs.NE]Hybrid Evolutionary Optimization Approach for Oilfield Well Control Optimization
    Ajitabh Kumar
    http://arxiv.org/abs/2103.15608v1

    • [cs.NE]Self-Constructing Neural Networks Through Random Mutation
    Samuel Schmidgall
    http://arxiv.org/abs/2103.15692v1

    • [cs.NE]Shape-constrained Symbolic Regression — Improving Extrapolation with Prior Knowledge
    Gabriel Kronberger, Fabricio Olivetti de França, Bogdan Burlacu, Christian Haider, Michael Kommenda
    http://arxiv.org/abs/2103.15624v1

    • [cs.NI]Joint Sampling and Transmission Policies for Minimizing Cost under AoI Constraints
    Emmanouil Fountoulakis, Marian Codreanu, Anthony Ephremides, Nikolaos Pappas
    http://arxiv.org/abs/2103.15450v1

    • [cs.NI]Joint User Association and Power Allocation in Heterogeneous Ultra Dense Network via Semi-Supervised Representation Learning
    Xiangyu Zhang, Zhengming Zhang, Luxi Yang
    http://arxiv.org/abs/2103.15367v1

    • [cs.RO]A hybrid controller for safe and efficient collision avoidance control
    Qiang Wang, Xinlei Zheng, Jiyong Zhang, Joseph Sifakis
    http://arxiv.org/abs/2103.15484v1

    • [cs.RO]Autonomous Overtaking in Gran Turismo Sport Using Curriculum Reinforcement Learning
    Yunlong Song, HaoChih Lin, Elia Kaufmann, Peter Duerr, Davide Scaramuzza
    http://arxiv.org/abs/2103.14666v1

    • [cs.RO]Compact 3D Map-Based Monocular Localization Using Semantic Edge Alignment
    Kejie Qiu, Shenzhou Chen, Jiahui Zhang, Rui Huang, Le Cui, Siyu Zhu, Ping Tan
    http://arxiv.org/abs/2103.14826v1

    • [cs.RO]Equivariant Filtering Framework for Inertial-Integrated Navigation
    Yarong Luo, Chi Guo, Jingnan Liu
    http://arxiv.org/abs/2103.14873v1

    • [cs.RO]Fundamental Challenges in Deep Learning for Stiff Contact Dynamics
    Mihir Parmar, Mathew Halm, Michael Posa
    http://arxiv.org/abs/2103.15406v1

    • [cs.RO]Ground Encoding: Learned Factor Graph-based Models for Localizing Ground Penetrating Radar
    Alexander Baikovitz, Paloma Sodhi, Michael Dille, Michael Kaess
    http://arxiv.org/abs/2103.15317v1

    • [cs.RO]LASER: Learning a Latent Action Space for Efficient Reinforcement Learning
    Arthur Allshire, Roberto Martín-Martín, Charles Lin, Shawn Manuel, Silvio Savarese, Animesh Garg
    http://arxiv.org/abs/2103.15793v1

    • [cs.RO]Lessons Learned Developing an Assembly System for WRS 2020 Assembly Challenge
    Aayush Naik, Priyam Parashar, Jiaming Hu, Henrik I. Christensen
    http://arxiv.org/abs/2103.15236v1

    • [cs.RO]Minimum directed information: A design principle for compliant robots
    Kevin Haninger
    http://arxiv.org/abs/2103.14830v1

    • [cs.RO]Multi-Robot Distributed Semantic Mapping in Unfamiliar Environments through Online Matching of Learned Representations
    Stewart Jamieson, Kaveh Fathian, Kasra Khosoussi, Jonathan P. How, Yogesh Girdhar
    http://arxiv.org/abs/2103.14805v1

    • [cs.RO]Online Flocking Control of UAVs with Mean-Field Approximation
    Malintha Fernando
    http://arxiv.org/abs/2103.15241v1

    • [cs.RO]Pursuer Assignment and Control Strategies in Multi-agent Pursuit-Evasion Under Uncertainties
    Leiming Zhang, Amanda Prorok, Subhrajit Bhattacharya
    http://arxiv.org/abs/2103.15660v1

    • [cs.RO]Range-Visual-Inertial Odometry: Scale Observability Without Excitation
    Jeff Delaune, David S. Bayard, Roland Brockers
    http://arxiv.org/abs/2103.15215v1

    • [cs.RO]Refractive Light-Field Features for Curved Transparent Objects in Structure from Motion
    Dorian Tsai, Peter Corke, Thierry Peynot, Donald G. Dansereau
    http://arxiv.org/abs/2103.15349v1

    • [cs.RO]Robust Feedback Motion Policy Design Using Reinforcement Learning on a 3D Digit Bipedal Robot
    Guillermo A. Castillo, Bowen Weng, Wei Zhang, Ayonga Hereid
    http://arxiv.org/abs/2103.15309v1

    • [cs.RO]Set-Valued Rigid Body Dynamics for Simultaneous Frictional Impact
    Mathew Halm, Michael Posa
    http://arxiv.org/abs/2103.15714v1

    • [cs.RO]Towards Robust State Estimation by Boosting the Maximum Correntropy Criterion Kalman Filter with Adaptive Behaviors
    Seyed Fakoorian, Angel Santamaria-Navarro, Brett T. Lopez, Dan Simon, Ali-akbar Agha-mohammadi
    http://arxiv.org/abs/2103.15354v1

    • [cs.RO]Transmitter Discovery through Radio-Visual Probabilistic Active Sensing
    Luca Varotto, Angelo Cenedese
    http://arxiv.org/abs/2103.14965v1

    • [cs.RO]Two-Stage Clustering of Human Preferences for Action Prediction in Assembly Tasks
    Heramb Nemlekar, Jignesh Modi, Satyandra K. Gupta, Stefanos Nikolaidis
    http://arxiv.org/abs/2103.14994v1

    • [cs.RO]Wall Detection Via IMU Data Classification In Autonomous Quadcopters
    Jason Hughes, Damian Lyons
    http://arxiv.org/abs/2103.15680v1

    • [cs.SD]Feature-based Representation for Violin Bridge Admittances
    R. Malvermi, S. Gonzalez, M. Quintavalla, F. Antonacci, A. Sarti, J. A. Torres, R. Corradi
    http://arxiv.org/abs/2103.14895v1

    • [cs.SD]Transformer-based end-to-end speech recognition with residual Gaussian-based self-attention
    Chengdong Liang, Menglong Xu, Xiao-Lei Zhang
    http://arxiv.org/abs/2103.15722v1

    • [cs.SE]Adaptive Autonomy in Human-on-the-Loop Vision-Based Robotics Systems
    Sophia Abraham, Zachariah Carmichael, Sreya Banerjee, Rosaura VidalMata, Ankit Agrawal, Md Nafee Al Islam, Walter Scheirer, Jane Cleland-Huang
    http://arxiv.org/abs/2103.15053v1

    • [cs.SE]Embedding API Dependency Graph for Neural Code Generation
    Chen Lyu, Ruyun Wang, Hongyu Zhang, Hanwen Zhang, Songlin Hu
    http://arxiv.org/abs/2103.15361v1

    • [cs.SI]A Systematic Survey on Multilayer Community Detection
    Zahra Roozbahani, Hanif Emamgholizadeh, Jalal Rezaeenour, Mahshid Hajialikhani
    http://arxiv.org/abs/2103.15698v1

    • [cs.SI]ABOME: A Multi-platform Data Repository of Artificially Boosted Online Media Entities
    Hridoy Sankar Dutta, Udit Arora, Tanmoy Chakraborty
    http://arxiv.org/abs/2103.15250v1

    • [cs.SI]Analysing the Effect of Recommendation Algorithms on the Amplification of Misinformation
    Miriam Fernández, Alejandro Bellogín, Iván Cantador
    http://arxiv.org/abs/2103.14748v1

    • [cs.SI]Beyond the adjacency matrix: random line graphs and inference for networks with edge attributes
    Zachary Lubberts, Avanti Athreya, Youngser Park, Carey E. Priebe
    http://arxiv.org/abs/2103.14726v1

    • [cs.SI]Dynamic Network Embedding Survey
    Guotong Xue, Ming Zhong, Jianxin Li, Jia Chen, Chengshuai Zhai, Ruochen Kong
    http://arxiv.org/abs/2103.15447v1

    • [cs.SI]Exploring, browsing and interacting with multi-scale structures of knowledge
    Quentin Lobbé, Alexandre Delanoë, David Chavalarias
    http://arxiv.org/abs/2103.15448v1

    • [cs.SI]Post-mortem memory of public figures in news and social media
    Robert West, Jure Leskovec, Christopher Potts
    http://arxiv.org/abs/2103.15497v1

    • [eess.AS]Quantifying Bias in Automatic Speech Recognition
    Siyuan Feng, Olya Kudina, Bence Mark Halpern, Odette Scharenborg
    http://arxiv.org/abs/2103.15122v1

    • [eess.AS]Scalable and Efficient Neural Speech Coding
    Kai Zhen, Jongmo Sung, Mi Suk Lee, Seungkwon Beak, Minje Kim
    http://arxiv.org/abs/2103.14776v1

    • [eess.AS]Scaling sparsemax based channel selection for speech recognition with ad-hoc microphone arrays
    Junqi Chen, Xiao-Lei Zhang
    http://arxiv.org/abs/2103.15305v1

    • [eess.IV]Best-Buddy GANs for Highly Detailed Image Super-Resolution
    Wenbo Li, Kun Zhou, Lu Qi, Liying Lu, Nianjuan Jiang, Jiangbo Lu, Jiaya Jia
    http://arxiv.org/abs/2103.15295v1

    • [eess.IV]Catalyzing Clinical Diagnostic Pipelines Through Volumetric Medical Image Segmentation Using Deep Neural Networks: Past, Present, & Future
    Teofilo E. Zosa
    http://arxiv.org/abs/2103.14969v1

    • [eess.IV]Checkerboard Context Model for Efficient Learned Image Compression
    Dailan He, Yaoyan Zheng, Baocheng Sun, Yan Wang, Hongwei Qin
    http://arxiv.org/abs/2103.15306v1

    • [eess.IV]Data-driven generation of plausible tissue geometries for realistic photoacoustic image synthesis
    Melanie Schellenberg, Janek Gröhl, Kris Dreher, Niklas Holzwarth, Minu D. Tizabi, Alexander Seitel, Lena Maier-Hein
    http://arxiv.org/abs/2103.15510v1

    • [eess.IV]Fully Automated 2D and 3D Convolutional Neural Networks Pipeline for Video Segmentation and Myocardial Infarction Detection in Echocardiography
    Oumaima Hamila, Sheela Ramanna, Christopher J. Henry, Serkan Kiranyaz, Ridha Hamila, Rashid Mazhar, Tahir Hamid
    http://arxiv.org/abs/2103.14734v1

    • [eess.IV]Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse Problems
    William Herzberg, Daniel B. Rowe, Andreas Hauptmann, Sarah J. Hamilton
    http://arxiv.org/abs/2103.15138v1

    • [eess.IV]Improving prostate whole gland segmentation in t2-weighted MRI with synthetically generated data
    Alvaro Fernandez-Quilez, Steinar Valle Larsen, Morten Goodwin, Thor Ole Gulsurd, Svein Reidar Kjosavik, Ketil Oppedal
    http://arxiv.org/abs/2103.14955v1

    • [eess.IV]Invertible Image Signal Processing
    Yazhou Xing, Zian Qian, Qifeng Chen
    http://arxiv.org/abs/2103.15061v1

    • [eess.IV]Multi-Disease Detection in Retinal Imaging based on Ensembling Heterogeneous Deep Learning Models
    Dominik Müller, Iñaki Soto-Rey, Frank Kramer
    http://arxiv.org/abs/2103.14660v1

    • [eess.IV]Omniscient Video Super-Resolution
    Peng Yi, Zhongyuan Wang, Kui Jiang, Junjun Jiang, Tao Lu, Xin Tian, Jiayi Ma
    http://arxiv.org/abs/2103.15683v1

    • [eess.IV]Physical model simulator-trained neural network for computational 3D phase imaging of multiple-scattering samples
    Alex Matlock, Lei Tian
    http://arxiv.org/abs/2103.15795v1

    • [eess.IV]Slimmable Compressive Autoencoders for Practical Neural Image Compression
    Fei Yang, Luis Herranz, Yongmei Cheng, Mikhail G. Mozerov
    http://arxiv.org/abs/2103.15726v1

    • [eess.IV]Tuning IR-cut Filter for Illumination-aware Spectral Reconstruction from RGB
    Bo Sun, Junchi Yan, Xiao Zhou, Yinqiang Zheng
    http://arxiv.org/abs/2103.14708v1

    • [eess.SP]MIMO-OFDM Joint Radar-Communications: Is ICI Friend or Foe?
    Musa Furkan Keskin, Henk Wymeersch, Visa Koivunen
    http://arxiv.org/abs/2103.15694v1

    • [eess.SP]On the benefits of robust models in modulation recognition
    Javier Maroto, Gérôme Bovet, Pascal Frossard
    http://arxiv.org/abs/2103.14977v1

    • [eess.SY]Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative-Entropy Trust Regions
    Hany Abdulsamad, Tim Dorau, Boris Belousov, Jia-Jie Zhu, Jan Peters
    http://arxiv.org/abs/2103.15388v1

    • [eess.SY]Risk-Averse Stochastic Shortest Path Planning
    Mohamadreza Ahmadi, Anushri Dixit, Joel W. Burdick, Aaron D. Ames
    http://arxiv.org/abs/2103.14727v1

    • [eess.SY]Self-adaptive Torque Vectoring Controller Using Reinforcement Learning
    Shayan Taherian, Sampo Kuutti, Marco Visca, Saber Fallah
    http://arxiv.org/abs/2103.14892v1

    • [eess.SY]Tuning of extended state observer with neural network-based control performance assessment
    Krzysztof Łakomy, Piotr Kicki, Ki Myung Brian Lee
    http://arxiv.org/abs/2103.15516v1

    • [hep-ex]Porting HEP Parameterized Calorimeter Simulation Code to GPUs
    Zhihua Dong, Heather Gray, Charles Leggett, Meifeng Lin, Vincent R. Pascuzzi, Kwangmin Yu
    http://arxiv.org/abs/2103.14737v1

    • [hep-lat]Generalization capabilities of translationally equivariant neural networks
    Srinath Bulusu, Matteo Favoni, Andreas Ipp, David I. Müller, Daniel Schuh
    http://arxiv.org/abs/2103.14686v1

    • [math.NA]A bandit-learning approach to multifidelity approximation
    Yiming Xu, Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
    http://arxiv.org/abs/2103.15342v1

    • [math.NA]Stiff Neural Ordinary Differential Equations
    Suyong Kim, Weiqi Ji, Sili Deng, Christopher Rackauckas
    http://arxiv.org/abs/2103.15341v1

    • [math.NA]Translating Numerical Concepts for PDEs into Neural Architectures
    Tobias Alt, Pascal Peter, Joachim Weickert, Karl Schrader
    http://arxiv.org/abs/2103.15419v1

    • [math.OC]Automatic differentiation for Riemannian optimization on low-rank matrix and tensor-train manifolds
    Alexander Novikov, Maxim Rakhuba, Ivan Oseledets
    http://arxiv.org/abs/2103.14974v1

    • [math.OC]Learning to Solve the AC-OPF using Sensitivity-Informed Deep Neural Networks
    Manish K. Singh, Vassilis Kekatos, Georgios B. Giannakis
    http://arxiv.org/abs/2103.14779v1

    • [math.OC]On the Stability of Nonlinear Receding Horizon Control: A Geometric Perspective
    Tyler Westenbroek, Max Simchowitz, Michael I. Jordan, S. Shankar Sastry
    http://arxiv.org/abs/2103.15010v1

    • [math.OC]Ridesharing Evacuation Model of Disaster Response
    Lingyu Meng, Zhijie, Dong, Shaolong Hu
    http://arxiv.org/abs/2103.15156v1

    • [math.PR]Exact converses to a reverse AM—GM inequality, with applications to sums of independent random variables and (super)martingales
    Iosif Pinelis
    http://arxiv.org/abs/2103.15740v1

    • [math.PR]Phase transition in noisy high-dimensional random geometric graphs
    Suqi Liu, Miklos Z. Racz
    http://arxiv.org/abs/2103.15249v1

    • [math.ST]Convergence of Griddy Gibbs Sampling and other perturbed Markov chains
    Vu Dinh, Ann E. Rundell, Gregery T. Buzzard
    http://arxiv.org/abs/2103.15672v1

    • [math.ST]Estimation of ergodic square-root diffusion under high-frequency sampling
    Yuzhong Cheng, Nicole Hufnagel, Hiroki Masuda
    http://arxiv.org/abs/2103.15457v1

    • [math.ST]Inference of Random Effects for Linear Mixed-Effects Models with a Fixed Number of Clusters
    Chih-Hao Chang, Hsin-Cheng Huang, Ching-Kang Ing
    http://arxiv.org/abs/2103.15095v1

    • [math.ST]The EM Algorithm is Adaptively-Optimal for Unbalanced Symmetric Gaussian Mixtures
    Nir Weinberger, Guy Bresler
    http://arxiv.org/abs/2103.15653v1

    • [math.ST]Variational inference of the drift function for stochastic differential equations driven by Lévy processes
    Min Dai, Jinqiao Duan, Jianyu Hu, Xiangjun Wang
    http://arxiv.org/abs/2103.15080v1

    • [physics.soc-ph]A stochastic model for the influence of social distancing on loneliness
    José F. Fontanari
    http://arxiv.org/abs/2103.15577v1

    • [q-bio.GN]GateKeeper-GPU: Fast and Accurate Pre-Alignment Filtering in Short Read Mapping
    Zülal Bingöl, Mohammed Alser, Ozcan Ozturk, Can Alkan
    http://arxiv.org/abs/2103.14978v1

    • [q-bio.NC]Frequency-specific segregation and integration of human cerebral cortex: an intrinsic functional atlas
    Zhiguo Luo, Ling-Li Zeng, Hui Shen, Dewen Hu
    http://arxiv.org/abs/2103.14907v1

    • [q-bio.NC]Quantum Bose-Einstein Statistics for Indistinguishable Concepts in Human Language
    Lester Beltran
    http://arxiv.org/abs/2103.15125v1

    • [q-fin.MF]Monte Carlo algorithm for the extrema of tempered stable processes
    Jorge Ignacio González Cázares, Aleksandar Mijatović
    http://arxiv.org/abs/2103.15310v1

    • [q-fin.ST]Accurate Stock Price Forecasting Using Robust and Optimized Deep Learning Models
    Jaydip Sen, Sidra Mehtab
    http://arxiv.org/abs/2103.15096v1

    • [q-fin.TR]A Comparative Evaluation of Predominant Deep Learning Quantified Stock Trading Strategies
    Haohan Zhang
    http://arxiv.org/abs/2103.15304v1

    • [quant-ph]Dual-Parameterized Quantum Circuit GAN Model in High Energy Physics
    Su Yeon Chang, Steven Herbert, Sofia Vallecorsa, Elías F. Combarro, Ross Duncan
    http://arxiv.org/abs/2103.15470v1

    • [stat.AP]Accurate Assessment via Process Data
    Susu Zhang, Zhi Wang, Jitong Qi, Jingchen Liu, Zhiliang Ying
    http://arxiv.org/abs/2103.15034v1

    • [stat.AP]Are Multilevel functional models the next step in sports biomechanics and wearable technology? A case study of Knee Biomechanics patterns in typical training sessions of recreational runners
    Marcos Matabuena, Sherveen Riazati, Nick Caplan, Phil Hayes
    http://arxiv.org/abs/2103.15704v1

    • [stat.AP]Bayesian model averaging for mortality forecasting using leave-future-out validation
    Karim Barigou, Pierre-Olivier Goffard, Stéphane Loisel, Yahia Salhi
    http://arxiv.org/abs/2103.15434v1

    • [stat.AP]Confidence Intervals for Seroprevalence
    Thomas J. DiCiccio, David M. Ritzwoller, Joseph P. Romano, Azeem M. Shaikh
    http://arxiv.org/abs/2103.15018v1

    • [stat.AP]External Correlates of Adult Digital Problem-Solving Behavior: Log Data Analysis of a Large-Scale Assessment
    Susu Zhang, Xueying Tang, Qiwei He, Jingchen Liu, Zhiliang Ying
    http://arxiv.org/abs/2103.15036v1

    • [stat.AP]Modeling Bivariate Geyser Eruption System with Covariate-Adjusted Recurrent Event Process
    Zhongnan Jin, Lu Lu, Khaled Bedair, Yili Hong
    http://arxiv.org/abs/2103.15611v1

    • [stat.AP]Multivariate Gaussian Process Incorporated Predictive Model for Stream Turbine Power Plant
    Prama Debnath, Mithun Ghosh
    http://arxiv.org/abs/2103.14871v1

    • [stat.AP]NesPrInDT: Nested undersampling in PrInDT
    Claus Weihs, Sarah Buschfeld
    http://arxiv.org/abs/2103.14931v1

    • [stat.AP]The study of variability in engineering design, an appreciation and a retrospective
    T P Davis
    http://arxiv.org/abs/2103.15478v1

    • [stat.ME]Accurate directional inference in Gaussian graphical models
    Claudia Di Caterina, Nancy Reid, Nicola Sartori
    http://arxiv.org/abs/2103.15394v1

    • [stat.ME]Bayesian Optimal Experimental Design for Inferring Causal Structure
    Michele Zemplenyi, Jeffrey W. Miller
    http://arxiv.org/abs/2103.15229v1

    • [stat.ME]Comment on “Statistical Modeling: The Two Cultures” by Leo Breiman
    Matteo Bonvini, Alan Mishler, Edward H. Kennedy
    http://arxiv.org/abs/2103.15281v1

    • [stat.ME]Data Integration through outcome adaptive LASSO and a collaborative propensity score approach
    Asma Bahamyirou, Mireille E. Schnitzer
    http://arxiv.org/abs/2103.15218v1

    • [stat.ME]Identifiability of Latent Class Models with Covariates
    Jing Ouyang, Gongjun Xu
    http://arxiv.org/abs/2103.14885v1

    • [stat.ME]Inapplicability of the TVOR method to USHMM Data Outlier Identification
    Melkior Ornik
    http://arxiv.org/abs/2103.14693v1

    • [stat.ME]Inference in the stochastic Cox-Ingersol-Ross diffusion process with continuous sampling: Computational aspects and simulation
    Nafidi Ahmed, El Azri Abdenbi
    http://arxiv.org/abs/2103.15678v1

    • [stat.ME]Is it who you are or where you are? Accounting for compositional differences in cross-site treatment variation
    Benjamin Lu, Eli Ben-Michael, Avi Feller, Luke Miratrix
    http://arxiv.org/abs/2103.14765v1

    • [stat.ME]Martingale Posterior Distributions
    Edwin Fong, Chris Holmes, Stephen G. Walker
    http://arxiv.org/abs/2103.15671v1

    • [stat.ME]Multimodal Data Integration via Mediation Analysis with High-Dimensional Exposures and Mediators
    Yi Zhao, Lexin Li
    http://arxiv.org/abs/2103.15687v1

    • [stat.ME]Nonparametric tests for treatment effect heterogeneity in observational studies
    Maozhu Dai, Weining Shen, Hal S. Stern
    http://arxiv.org/abs/2103.15023v1

    • [stat.ME]Optimal False Discovery Rate Control for Large Scale Multiple Testing with Auxiliary Information
    Hongyuan Cao, Jun Chen, Xianyang Zhang
    http://arxiv.org/abs/2103.15311v1

    • [stat.ME]Sparse and Smooth Functional Data Clustering
    Fabio Centofanti, Antonio Lepore, Biagio Palumbo
    http://arxiv.org/abs/2103.15224v1

    • [stat.ME]Statistical Inference of Auto-correlated Eigenvalues with Applications to Diffusion Tensor Imaging
    Zhou Lan
    http://arxiv.org/abs/2103.15252v1

    • [stat.ME]Structure Learning of Contextual Markov Networks using Marginal Pseudo-likelihood
    Johan Pensar, Henrik Nyman, Jukka Corander
    http://arxiv.org/abs/2103.15540v1

    • [stat.ME]Testing For a Parametric Baseline-Intensity in Dynamic Interaction Networks
    Alexander Kreiss, Enno Mammen, Wolfgang Polonik
    http://arxiv.org/abs/2103.14668v1

    • [stat.ME]The Statistics of Circular Optimal Transport
    Shayan Hundrieser, Marcel Klatt, Axel Munk
    http://arxiv.org/abs/2103.15426v1

    • [stat.ML]Community Detection in General Hypergraph via Graph Embedding
    Yaoming Zhen, Junhui Wang
    http://arxiv.org/abs/2103.15035v1

    • [stat.ML]Compositional Abstraction Error and a Category of Causal Models
    Eigil F. Rischel, Sebastian Weichwald
    http://arxiv.org/abs/2103.15758v1

    • [stat.ML]Deconfounded Score Method: Scoring DAGs with Dense Unobserved Confounding
    Alexis Bellot, Mihaela van der Schaar
    http://arxiv.org/abs/2103.15106v1

    • [stat.ML]Entropy methods for the confidence assessment of probabilistic classification models
    Gabriele N. Tornetta
    http://arxiv.org/abs/2103.15157v1

    • [stat.ML]Learning on heterogeneous graphs using high-order relations
    See Hian Lee, Feng Ji, Wee Peng Tay
    http://arxiv.org/abs/2103.15532v1

    • [stat.ML]Lower Bounds on the Generalization Error of Nonlinear Learning Models
    Inbar Seroussi, Ofer Zeitouni
    http://arxiv.org/abs/2103.14723v1

    • [stat.ML]Machine learning based digital twin for stochastic nonlinear multi-degree of freedom dynamical system
    Shailesh Garg, Ankush Gogoi, Souvik Chakraborty, Budhaditya Hazra
    http://arxiv.org/abs/2103.15636v1

    • [stat.ML]Particle Filter Bridge Interpolation
    Adam Lindhe, Carl Ringqvist, Henrik Hult
    http://arxiv.org/abs/2103.14963v1

    • [stat.ML]Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks
    Curtis G. Northcutt, Anish Athalye, Jonas Mueller
    http://arxiv.org/abs/2103.14749v1

    • [stat.ML]Time-to-event regression using partially monotonic neural networks
    David Rindt, Robert Hu, David Steinsaltz, Dino Sejdinovic
    http://arxiv.org/abs/2103.14755v1