今日学术视野(2021.1.20)

cond-mat.str-el - 强关联电子系统

cs.AI - 人工智能 cs.CE - 计算工程、 金融和科学 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.DM - 离散数学 cs.DS - 数据结构与算法 cs.FL - 形式语言与自动机理论 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.MM - 多媒体 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.SY - 系统和控制 hep-ex - 高能物理实验 math.AT - 代数拓扑 math.LO - 逻辑演算 math.NA - 数值分析 math.OA - 算子代数 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 physics.chem-ph -化学物理 physics.soc-ph - 物理学与社会 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习 stat.OT - 其他统计学

• [cond-mat.str-el]Gauge Invariant Autoregressive Neural Networks for Quantum Lattice Models
• [cs.AI]A Layer-Wise Information Reinforcement Approach to Improve Learning in Deep Belief Networks
• [cs.AI]A Literature Review of Recent Graph Embedding Techniques for Biomedical Data
• [cs.AI]Adversarial Interaction Attack: Fooling AI to Misinterpret Human Intentions
• [cs.AI]An Empirical Comparison of Deep Learning Models for Knowledge Tracing on Large-Scale Dataset
• [cs.AI]An attention model to analyse the risk of agitation and urinary tract infections in people with dementia
• [cs.AI]Artificial Intelligence for Emotion-Semantic Trending and People Emotion Detection During COVID-19 Social Isolation
• [cs.AI]CaEGCN: Cross-Attention Fusion based Enhanced Graph Convolutional Network for Clustering
• [cs.AI]Data Obsolescence Detection in the Light of Newly Acquired Valid Observations
• [cs.AI]Faster Convergence in Deep-Predictive-Coding Networks to Learn Deeper Representations
• [cs.AI]Learning the Implicit Semantic Representation on Graph-Structured Data
• [cs.AI]On the Generalizability of Motion Models for Road Users in Heterogeneous Shared Traffic Spaces
• [cs.AI]Solving QSAT problems with neural MCTS
• [cs.AI]Understanding in Artificial Intelligence
• [cs.CE]Cell division in deep material networks applied to multiscale strain localization modeling
• [cs.CE]Optical Flow Method for Measuring Deformation of Soil Specimen Subjected to Torsional Shearing
• [cs.CG]Computer Aided Formal Design of Swarm Robotics Algorithms
• [cs.CL]Abstractive Opinion Tagging
• [cs.CL]Can a Fruit Fly Learn Word Embeddings?
• [cs.CL]ComQA:Compositional Question Answering via Hierarchical Graph Neural Networks
• [cs.CL]Comparison of Machine Learning for Sentiment Analysis in Detecting Anxiety Based on Social Media Data
• [cs.CL]Few Shot Dialogue State Tracking using Meta-learning
• [cs.CL]Fusing Wav2vec2.0 and BERT into End-to-end Model for Low-resource Speech Recognition
• [cs.CL]GENIE: A Leaderboard for Human-in-the-Loop Evaluation of Text Generation
• [cs.CL]Grid Search Hyperparameter Benchmarking of BERT, ALBERT, and LongFormer on DuoRC
• [cs.CL]HinFlair: pre-trained contextual string embeddings for pos tagging and text classification in the Hindi language
• [cs.CL]Incremental Knowledge Based Question Answering
• [cs.CL]Joint Energy-based Model Training for Better Calibrated Natural Language Understanding Models
• [cs.CL]Linguistically-Enriched and Context-Aware Zero-shot Slot Filling
• [cs.CL]Match-Ignition: Plugging PageRank into Transformer for Long-form Text Matching
• [cs.CL]Model Compression for Domain Adaptation through Causal Effect Estimation
• [cs.CL]Narration Generation for Cartoon Videos
• [cs.CL]Neural Abstractive Text Summarizer for Telugu Language
• [cs.CL]Red Alarm for Pre-trained Models: Universal Vulnerabilities by Neuron-Level Backdoor Attacks
• [cs.CL]Teach me how to Label: Labeling Functions from Natural Language with Text-to-text Transformers
• [cs.CL]TextGNN: Improving Text Encoder via Graph Neural Network in Sponsored Search
• [cs.CL]To Understand Representation of Layer-aware Sequence Encoders as Multi-order-graph
• [cs.CL]Tuiteamos o pongamos un tuit? Investigating the Social Constraints of Loanword Integration in Spanish Social Media
• [cs.CL]Weakly-Supervised Hierarchical Models for Predicting Persuasive Strategies in Good-faith Textual Requests
• [cs.CL]What Makes Good In-Context Examples for GPT-?
• [cs.CR]A System for Efficiently Hunting for Cyber Threats in Computer Systems Using Threat Intelligence
• [cs.CR]A Technical Report for Light-Edge: A Lightweight Authentication Protocol for IoT Devices in an Edge-Cloud Environment
• [cs.CR]DeepPayload: Black-box Backdoor Attack on Deep Learning Models through Neural Payload Injection
• [cs.CR]Leveraging AI to optimize website structure discovery during Penetration Testing
• [cs.CR]SEDAT:Security Enhanced Device Attestation with TPM2.0
• [cs.CV]A relic sketch extraction framework based on detail-aware hierarchical deep network
• [cs.CV]ACP: Automatic Channel Pruning via Clustering and Swarm Intelligence Optimization for CNN
• [cs.CV]Adaptive Graph Representation Learning and Reasoning for Face Parsing
• [cs.CV]Adaptive Remote Sensing Image Attribute Learning for Active Object Detection
• [cs.CV]Assisting Barrett’s esophagus identification using endoscopic data augmentation based on Generative Adversarial Networks
• [cs.CV]Auto4D: Learning to Label 4D Objects from Sequential Point Clouds
• [cs.CV]Bladder segmentation based on deep learning approaches: current limitations and lessons
• [cs.CV]CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Detection in Remote Sensing Images
• [cs.CV]CLASTER: Clustering with Reinforcement Learning for Zero-Shot Action Recognition
• [cs.CV]Catching Out-of-Context Misinformation with Self-supervised Learning
• [cs.CV]Chaotic-to-Fine Clustering for Unlabeled Plant Disease Images
• [cs.CV]CheXtransfer: Performance and Parameter Efficiency of ImageNet Models for Chest X-Ray Interpretation
• [cs.CV]Coarse Temporal Attention Network (CTA-Net) for Driver’s Activity Recognition
• [cs.CV]Context-aware Attentional Pooling (CAP) for Fine-grained Visual Classification
• [cs.CV]Cross-modal Learning for Domain Adaptation in 3D Semantic Segmentation
• [cs.CV]Deep Learning based Virtual Point Tracking for Real-Time Target-less Dynamic Displacement Measurement in Railway Applications
• [cs.CV]Deep Multi-Task Learning for Joint Localization, Perception, and Prediction
• [cs.CV]Deep Parametric Continuous Convolutional Neural Networks
• [cs.CV]Deep Structured Reactive Planning
• [cs.CV]Deep Universal Blind Image Denoising
• [cs.CV]DeepMI: A Mutual Information Based Framework For Unsupervised Deep Learning of Tasks
• [cs.CV]Diversified Patch-based Style Transfer with Shifted Style Normalization
• [cs.CV]Dual-Level Collaborative Transformer for Image Captioning
• [cs.CV]End-to-end Interpretable Neural Motion Planner
• [cs.CV]Exploring Adversarial Robustness of Multi-Sensor Perception Systems in Self Driving
• [cs.CV]Generalized Image Reconstruction over T-Algebra
• [cs.CV]Generating Attribution Maps with Disentangled Masked Backpropagation
• [cs.CV]GeoSim: Photorealistic Image Simulation with Geometry-Aware Composition
• [cs.CV]GridTracer: Automatic Mapping of Power Grids using Deep Learning and Overhead Imagery
• [cs.CV]HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Network that Achieves over 0.9 Mean Dice and 86 FPS
• [cs.CV]Heterogeneous Hand Guise Classification Based on Surface Electromyographic Signals Using Multichannel Convolutional Neural Network
• [cs.CV]Human Activity Recognition Using Multichannel Convolutional Neural Network
• [cs.CV]HySTER: A Hybrid Spatio-Temporal Event Reasoner
• [cs.CV]Improving Apparel Detection with Category Grouping and Multi-grained Branches
• [cs.CV]Intestinal Parasites Classification Using Deep Belief Networks
• [cs.CV]KCP: Kernel Cluster Pruning for Dense Labeling Neural Networks
• [cs.CV]LNSMM: Eye Gaze Estimation With Local Network Share Multiview Multitask
• [cs.CV]Label-Efficient Point Cloud Semantic Segmentation: An Active Learning Approach
• [cs.CV]LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting
• [cs.CV]Latent Variable Models for Visual Question Answering
• [cs.CV]MultiBodySync: Multi-Body Segmentation and Motion Estimation via 3D Scan Synchronization
• [cs.CV]Network Automatic Pruning: Start NAP and Take a Nap
• [cs.CV]Non-parametric Memory for Spatio-Temporal Segmentation of Construction Zones for Self-Driving
• [cs.CV]Optical Flow Estimation via Motion Feature Recovery
• [cs.CV]PLUME: Efficient 3D Object Detection from Stereo Images
• [cs.CV]Real Time Incremental Foveal Texture Mapping for Autonomous Vehicles
• [cs.CV]Regional Attention Network (RAN) for Head Pose and Fine-grained Gesture Recognition
• [cs.CV]S3: Neural Shape, Skeleton, and Skinning Fields for 3D Human Modeling
• [cs.CV]SceneGen: Learning to Generate Realistic Traffic Scenes
• [cs.CV]Secrets of 3D Implicit Object Shape Reconstruction in the Wild
• [cs.CV]Self-Supervised Representation Learning from Flow Equivariance
• [cs.CV]Semi Supervised Deep Quick Instance Detection and Segmentation
• [cs.CV]Semi-Automatic Video Annotation For Object Detection
• [cs.CV]Separable Batch Normalization for Robust Facial Landmark Localization with Cross-protocol Network Training
• [cs.CV]Shape Back-Projection In 3D Scenes
• [cs.CV]TLU-Net: A Deep Learning Approach for Automatic Steel Surface Defect Detection
• [cs.CV]Temporal Spatial-Adaptive Interpolation with Deformable Refinement for Electron Microscopic Images
• [cs.CV]Trilevel Neural Architecture Search for Efficient Single Image Super-Resolution
• [cs.CV]Unsupervised Noisy Tracklet Person Re-identification
• [cs.CV]VideoClick: Video Object Segmentation with a Single Click
• [cs.CV]What Do Deep Nets Learn? Class-wise Patterns Revealed in the Input Space
• [cs.CY]AR-based Modern Healthcare: A Review
• [cs.CY]Capitol (Pat)riots: A comparative study of Twitter and Parler
• [cs.CY]Impact of COVID-19 on Adoption of IoT in Different Sectors
• [cs.CY]The BIVEE Project: an overview of methodology and tools
• [cs.DB]AMALGAM: A Matching Approach to fairfy tabuLar data with knowledGe grAph Model
• [cs.DC]A Distributed Chunk Calculation Approach for Self-scheduling of Parallel Applications on Distributed-memory Systems
• [cs.DC]Big Data application in congestion detection and classification using Apache spark
• [cs.DC]Byzantine Generals in the Permi
1000
ssionless Setting
• [cs.DC]DFOGraph: An I/O- and Communication-Efficient System for Distributed Fully-out-of-Core Graph Process
5000
ing
• [cs.DC]Demystifying Pythia: A Survey of ChainLink Oracles Usage on Ethereum
• [cs.DC]Galleon: Reshaping the Square Peg of NFV
• [cs.DC]T-Lease: A Trusted Lease Primitive for Distributed Systems
• [cs.DC]Tailored Learning-Based Scheduling for Kubernetes-Oriented Edge-Cloud System
• [cs.DC]Ten Simple Rules for Success with HPC, i.e. Responsibly BASHing that Linux Cluster
• [cs.DC]Time-Efficient and High-Quality Graph Partitioning for Graph Dynamic Scaling
• [cs.DC]Tuning the Frequency of Periodic Data Movements over Hybrid Memory Systems
• [cs.DC]ZeRO-Offload: Democratizing Billion-Scale Model Training
• [cs.DM]A note on the price of bandit feedback for mistake-bounded online learning
• [cs.DS]Data stream fusion for accurate quantile tracking and analysis
• [cs.DS]Maximizing approximately k-submodular functions
• [cs.FL]A Passive Online Technique for Learning Hybrid Automata from Input/Output Traces
• [cs.HC]Dissecting the Meme Magic: Understanding Indicators of Virality in Image Memes
• [cs.HC]Motor-Imagery-Based Brain Computer Interface using Signal Derivation and Aggregation Functions
• [cs.IR]A Survey on Extraction of Causal Relations from Natural Language Text
• [cs.IR]A Zero Attentive Relevance Matching Networkfor Review Modeling in Recommendation System
• [cs.IR]Controlling the Risk of Conversational Search via Reinforcement Learning
• [cs.IR]ExpFinder: An Ensemble Expert Finding Model Integrating -gram Vector Space Model and CO-HITS
• [cs.IR]Mitigating the Position Bias of Transformer Models in Passage Re-Ranking
• [cs.IR]Reinforcement learning based recommender systems: A survey
• [cs.IR]Robustness of Meta Matrix Factorization Against Strict Privacy Constraints
• [cs.IR]Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation
• [cs.IR]Studying Catastrophic Forgetting in Neural Ranking Models
• [cs.IR]Tip of the Tongue Known-Item Retrieval: A Case Study in Movie Identification
• [cs.IT]#card=math&code=%28%CE%B5%2C%20n%29) Fixed-Length Strong Coordination Capacity
• [cs.IT]Aggregated Network for Massive MIMO CSI Feedback
• [cs.IT]Almost Optimal Construction of Functional Batch Codes Using Hadamard Codes
• [cs.IT]Deep Learning-Aided 5G Channel Estimation
• [cs.IT]Energy-Efficient RIS-assisted Satellites for IoT Networks
• [cs.IT]Fundamental Limits of Demand-Private Coded Caching
• [cs.IT]Hierarchical Passive Beamforming for Reconfigurable Intelligent Surface Aided Communications
• [cs.IT]Improving Physical Layer Security for Reconfigurable Intelligent Surface aided NOMA 6G Networks
• [cs.IT]Joint Beamforming and Location Optimization for Secure Data Collection in Wireless Sensor Networks with UAV-Carried Intelligent Reflecting Surface
• [cs.IT]Machine Learning-Enabled Joint Antenna Selection and Precoding Design: From Offline Complexity to Online Performance
• [cs.IT]New Low Rank Optimization Model and Convex Approach for Robust Spectral Compressed Sensing
• [cs.IT]On linear codes with one-dimensional Euclidean hull and their applications to EAQECCs
• [cs.IT]On the Asymptotic Performance Analysis of the k-th Best Link Selection over Non-identical Non-central Chi-square Fading Channels
• [cs.IT]Online Caching with Optimal Switching Regret
• [cs.IT]Optimal Pre-Processing to Achieve Fairness and Its Relationship with Total Variation Barycenter
• [cs.IT]Quartic Perturbation-based Outage-constrained Robust Design in Two-hop One-way Relay Networks
• [cs.IT]Resolution Limits of Non-Adaptive 20 Questions Search for Multiple Targets
• [cs.IT]Stable Matching for Selection of Intelligent Reflecting Surfaces in Multiuser MISO Systems
• [cs.IT]The Broadcast Approach in Communication Networks
• [cs.IT]Uplink Beam Management for Millimeter Wave Cellular MIMO Systems with Hybrid Beamforming
• [cs.LG]A multilevel clustering technique for community detection
• [cs.LG]A simple geometric proof for the benefit of depth in ReLU networks
• [cs.LG]Adversarial Attacks On Multi-Agent Communication
• [cs.LG]Alignment and stability of embeddings: measurement and inference improvement
• [cs.LG]Analysis of key flavors of event-driven predictive maintenance using logs of phenomena described by Weibull distributions
• [cs.LG]Bayesian Inference Forgetting
• [cs.LG]Blockchain Assisted Decentralized Federated Learning (BLADE-FL): Performance Analysis and Resource Allocation
• [cs.LG]Classification of fNIRS Data Under Uncertainty: A Bayesian Neural Network Approach
• [cs.LG]Cooperative and Competitive Biases for Multi-Agent Reinforcement Learning
• [cs.LG]Cost-Efficient Online Hyperparameter Optimization
• [cs.LG]Deep Compression of Neural Networks for Fault Detection on Tennessee Eastman Chemical Processes
• [cs.LG]Deep Cox Mixtures for Survival Regression
• [cs.LG]Deep Inertial Odometry with Accurate IMU Preintegration
• [cs.LG]Deep Learning for Moving Blockage Predictionusing Real Millimeter Wave Measurements
• [cs.LG]Deep Reinforcement Learning for Active High Frequency Trading
• [cs.LG]Deep-Mobility: A Deep Learning Approach for an Efficient and Reliable 5G Handover
• [cs.LG]Detection of Insider Attacks in Distributed Projected Subgradient Algorithms
• [cs.LG]Discrete Graph Structure Learning for Forecasting Multiple Time Series
• [cs.LG]Disentangling Observed Causal Effects from Latent Confounders using Method of Moments
• [cs.LG]Diverse Complexity Measures for Dataset Curation in Self-driving
• [cs.LG]Emotional EEG Classification using Connectivity Features and Convolutional Neural Networks
• [cs.LG]Energy-based Dropout in Restricted Boltzmann Machines: Why not go random
• [cs.LG]Estimating informativeness of samples with Smooth Unique Information
• [cs.LG]Evaluating Online and Offline Accuracy Traversal Algorithms for k-Complete Neural Network Architectures
• [cs.LG]Fast and accurate learned multiresolution dynamical downscaling for precipitation
• [cs.LG]Free Lunch for Few-shot Learning: Distribution Calibration
• [cs.LG]Fundamental Tradeoffs in Distributionally Adversarial Training
• [cs.LG]Generative Counterfactuals for Neural Networks via Attribute-Informed Perturbation
• [cs.LG]GraphAttacker: A General Multi-Task GraphAttack Framework
• [cs.LG]Heterogeneous Similarity Graph Neural Network on Electronic Health Records
• [cs.LG]Hierarchical Reinforcement Learning By Discovering Intrinsic Options
• [cs.LG]HyperNTF: A Hypergraph Regularized Nonnegative Tensor Factorization for Dimensionality Reduction
• [cs.LG]In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning
• [cs.LG]Interpretable Policy Specification and Synthesis through Natural Language and RL
• [cs.LG]JITuNE: Just-In-Time Hyperparameter Tuning for Network Embedding Algorithms
• [cs.LG]Learning DNN networks using un-rectifying ReLU with compressed sensing application
• [cs.LG]Learning Successor States and Goal-Dependent Values: A Mathematical Viewpoint
• [cs.LG]Learning from pandemics: using extraordinary events can improve disease now-casting models
• [cs.LG]Machine-Learning Mathematical Structures
• [cs.LG]Measure-conditional Discriminator with Stationary Optimum for GANs and Statistical Distance Surrogates
• [cs.LG]Membership Inference Attack on Graph Neural Networks
• [cs.LG]Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models
• [cs.LG]Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction
• [cs.LG]Multi-Source Data Fusion for Cyberattack Detection in Power Systems
• [cs.LG]Multi-objective Search of Robust Neural Architectures against Multiple Types of Adversarial Attacks
• [cs.LG]Multimodal Variational Autoencoders for Semi-Supervised Learning: In Defense of Product-of-Experts
• [cs.LG]NNStreamer: Efficient and Agile Development of On-Device AI Systems
• [cs.LG]On the Differentially Private Nature of Perturbed Gradient Descent
• [cs.LG]Online detection of failures generated by storage simulator
• [cs.LG]Phases of learning dynamics in artificial neural networks: with or without mislabeled data
• [cs.LG]Physics-Informed Deep Learning for Traffic State Estimation
• [cs.LG]Privacy-Preserving Learning of Human Activity Predictors in Smart Environments
• [cs.LG]Regularized Policies are Reward Robust
• [cs.LG]Removing Undesirable Feature Contributions Using Out-of-Distribution Data
• [cs.LG]Robustness to Augmentations as a Generalization metric
• [cs.LG]Scaling Deep Contrastive Learning Batch Size with Almost Constant Peak Memory Usage
• [cs.LG]Screening for Sparse Online Learning
• [cs.LG]SelfMatch: Combining Contrastive Self-Supervision and Consistency for Semi-Supervised Learning
• [cs.LG]Slot Machines: Discovering Winning Combinations of Random Weights in Neural Networks
• [cs.LG]Spatial Network Decomposition for Fast and Scalable AC-OPF Learning
• [cs.LG]Stable Recovery of Entangled Weights: Towards Robust Identification of Deep Neural Networks from Minimal Samples
• [cs.LG]Stable deep reinforcement learning method by predicting uncertainty in rewards as a subtask
• [cs.LG]Stacked LSTM Based Deep Recurrent Neural Network with Kalman Smoothing for Blood Glucose Prediction
• [cs.LG]Towards Searching Efficient and Accurate Neural Network Architectures in Binary Classification Problems
• [cs.LG]Transferring model structure in Bayesian transfer learning for Gaussian process regression
• [cs.LG]Visual Analytics approach for finding spatiotemporal patterns from COVID19
• [cs.LG]Yet Another Representation of Binary Decision Trees: A Mathematical Demonstration
• [cs.MM]A Novel Local Binary Pattern Based Blind Feature Image Steganography
• [cs.MM]Designing a mobile game to generate player data — lessons learned
• [cs.NE]A Spiking Central Pattern Generator for the control of a simulated lamprey robot running on SpiNNaker and Loihi neuromorphic boards
• [cs.NE]Performance Analysis and Improvement of Parallel Differential Evolution
• [cs.NI]Wi-Fi Wardriving Studies Must Account for Important Statistical Issues
• [cs.RO]A New Particle Filter Framework for Bayesian Receiver Autonomous Integrity Monitoring in Urban Environments
• [cs.RO]A Safe Hierarchical Planning Framework for Complex Driving Scenarios based on Reinforcement Learning
• [cs.RO]AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles
• [cs.RO]Asynchronous Multi-View SLAM
• [cs.RO]Data-Driven Protection Levels for Camera and 3D Map-based Safe Urban Localization
• [cs.RO]Deep Reinforcement Learning with Embedded LQR Controllers
• [cs.RO]Fast and Accurate Multi-Body Simulation with Stiff Viscoelastic Contacts
• [cs.RO]From hand to brain and back: Grip forces deliver insight into the functional plasticity of somatosensory processes
• [cs.RO]Generation of GelSight Tactile Images for Sim2Real Learning
• [cs.RO]Kimera: from SLAM to Spatial Perception with 3D Dynamic Scene Graphs
• [cs.RO]Learning by Watching: Physical Imitation of Manipulation Skills from Human Videos
• [cs.RO]LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving
• [cs.RO]MP3: A Unified Model to Map, Perceive, Predict and Plan
• [cs.RO]MPC-MPNet: Model-Predictive Motion Planning Networks for Fast, Near-Optimal Planning under Kinodynamic Constraints
• [cs.RO]Online Robust Sliding-Windowed LiDAR SLAM in Natural Environments
• [cs.RO]Predictive Processing in Cognitive Robotics: a Review
• [cs.RO]Provably Constant-time Planning and Replanning for Real-time Grasping Objects off a Conveyor Belt
• [cs.RO]Slider: On the Design and Modeling of a 2D Floating Satellite Platform
• [cs.RO]Soft Constrained Autonomous Vehicle Navigation using Gaussian Processes and Instance Segmentation
• [cs.RO]Stereo Camera Visual SLAM with Hierarchical Masking and Motion-state Classification at Outdoor Construction Sites Containing Large Dynamic Objects
• [cs.RO]Towards Deep Learning Assisted Autonomous UAVs for Manipulation Tasks in GPS-Denied Environments
• [cs.RO]TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviors
• [cs.RO]TridentNet: A Cond
1000
itional Generative Model for Dynamic Trajectory Generation
• [cs.RO]Wearable Sensors for Spatio-Temporal Grip Force Profiling
• [cs.SD]Hierarchical disentangled representation learning for singing voice conversion
• [cs.SE]ConE: A Concurrent Edit Detection Tool for Large ScaleSoftware Development
• [cs.SI]”I Won the Election!”: An Empirical Analysis of Soft Moderation Interventions on Twitter
• [cs.SI]Characterizing Discourse about COVID-19 Vaccines: A Reddit Version of the Pandemic Story
• [cs.SI]Community Detection in Blockchain Social Networks
• [cs.SI]Digital Contact Tracing: Large-scale Geolocation Data as an Alternative to Bluetooth-based Apps’ Failure
• [cs.SI]From Gen Z, Millennials, to Babyboomers: Portraits of Working from Home during the COVID-19 Pandemic
• [cs.SI]PRESTO: Simple and Scalable Sampling Techniques for the Rigorous Approximation of Temporal Motif Counts
• [cs.SI]Separating Controversy from Noise: Comparison and Normalization of Structural Polarization Measures
• [cs.SI]Understanding Patterns of Users Who Repost Censored Posts on Weibo
• [cs.SI]Unsupervised Link and Unlink Prediction on Dynamic Networks
• [eess.AS]Mispronunciation Detection in Non-native (L2) English with Uncertainty Modeling
• [eess.IV]A Hitchhiker’s Guide to Structural Similarity
• [eess.IV]A New Approach for Automatic Segmentation and Evaluation of Pigmentation Lesion by using Active Contour Model and Speeded Up Robust Features
• [eess.IV]A Novel Registration & Colorization Technique for Thermal to Cross Domain Colorized Images
• [eess.IV]Adversarial cycle-consistent synthesis of cerebral microbleeds for data augmentation
• [eess.IV]Comparing Deep Learning strategies for paired but unregistered multimodal segmentation of the liver in T1 and T2-weighted MRI
• [eess.IV]Covid-19 classification with deep neural network and belief functions
• [eess.IV]Deep Symmetric Adaptation Network for Cross-modality Medical Image Segmentation
• [eess.IV]Iterative Facial Image Inpainting using Cyclic Reverse Generator
• [eess.IV]Latent Space Analysis of VAE and Intro-VAE applied to 3-dimensional MR Brain Volumes of Multiple Sclerosis, Leukoencephalopathy, and Healthy Patients
• [eess.IV]Optimized and autonomous machine learning framework for characterizing pores, particles, grains and grain boundaries in microstructural images
• [eess.IV]Scale factor point spread function matching: Beyond aliasing in image resampling
• [eess.IV]Symmetric-Constrained Irregular Structure Inpainting for Brain MRI Registration with Tumor Pathology
• [eess.IV]Uncertainty-Aware Body Composition Analysis with Deep Regression Ensembles on UK Biobank MRI
• [eess.SY]Incorporating Coincidental Water Data into Non-intrusive Load Monitoring
• [eess.SY]Learning Robust Hybrid Control Barrier Functions for Uncertain Systems
• [eess.SY]Quantification of Disaggregation Difficulty with Respect to the Number of Meters
• [hep-ex]Hashing and metric learning for charged particle tracking
• [math.AT]Hypernetworks: From Posets to Geometry
• [math.LO]Binary strings of finite VC dimension
• [math.NA]Deep neural network surrogates for non-smooth quantities of interest in shape uncertainty quantification
• [math.NA]GPU Methodologies for Numerical Partial Differential Equations
• [math.NA]On the efficient parallel computing of long term reliable trajectories for the Lorenz system
• [math.NA]What was the river Ister in the time of Strabo? A mathematical approach
• [math.OA]Tracial smooth functions of non-commuting variables and the free Wasserstein manifold
• [math.OC]TREGO: a Trust-Region Framework for Efficient Global Optimization
• [math.PR]Asymptotics of running maxima for -subgaussian random double arrays
• [math.PR]Wasserstein Convergence Rate for Empirical Measures of Markov Chains
• [math.ST]Conditional Independence Testing in Hilbert Spaces with Applications to Functional Data Analysis
• [math.ST]Consistent Bayesian Community Detection
• [math.ST]Higher Order Targeted Maximum Likelihood Estimation
• [physics.chem-ph]Data-driven discovery of multiscale chemical reactions governed by the law of mass action
• [physics.soc-ph]Temporal Clustering of Disorder Events During the COVID-19 Pandemic
• [stat.AP]A deterministic matching method for exact matchings to compare the outcome of different interventions
• [stat.AP]Do In-Person Lectures Help? A Study of a Large Statistics Class
• [stat.AP]Generative Dynamics of Supreme Court Citations: Analysis with a New Statistical Network Model
• [stat.AP]Making the most of imprecise measurements: Changing patterns of arsenic concentrations in shallow wells of Bangladesh from laboratory and field data
• [stat.AP]Post-processing numerical weather prediction ensembles for probabilistic solar irradiance forecasting
• [stat.CO]An MCMC Method to Sample from Lattice Distributions
• [stat.ME]Adaptive Change Point Monitoring for High-Dimensional Data
• [stat.ME]Bias Reduction as a Remedy to the Consequences of Infinite Estimates in Poisson and Tobit Regression
• [stat.ME]Inference for BART with Multinomial Outcomes
• [stat.ME]Model structures and structural identifiability: What? Why? How?
• [stat.ME]Novel Bayesian Procrustes Variance-based Inferences in Geometric Morphometrics & Novel R package: BPviGM1
• [stat.ME]On the relationship between a Gamma distributed precision parameter and the associated standard deviation in the context of Bayesian parameter inference
• [stat.ME]Perturbations and Causality in Gaussian Models
• [stat.ME]Query-Based Selection of Optimal Candidates under the Mallows Model
• [stat.ME]Robust Functional Principal Component Analysis via Functional Pairwise Spatial Signs
• [stat.ME]Spatial deformation for non-stationary extremal dependence
• [stat.ME]TSEC: a framework for online experimentation under experimental constraints
• [stat.ME]The Violating Assumptions Series: Simulated demonstrations to illustrate how assumptions can affect statistical estimates
• [stat.ME]Variance Estimation and Confidence Intervals from High-dimensional Genome-wide Association Studies Through Misspecified Mixed Model Analysis
• [stat.ML]Exponential Kernels with Latency in Hawkes Processes: Applications in Finance
• [stat.ML]Identifying Treatment Effects under Unobserved Confounding by Causal Representation Learning
• [stat.ML]Informative core identification in complex networks
• [stat.ML]Interactive slice visualization for exploring machine learning models
• [stat.ML]Multi-view Data Visualisation via Manifold Learning
• [stat.ML]On Data-Augmentation and Consistency-Based Semi-Supervised Learning
• [stat.ML]Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary
• [stat.ML]Sensitivity Prewarping for Local Surrogate Modeling
• [stat.ML]The Connection between Discrete- and Continuous-Time Descriptions of Gaussian Continuous Processes
• [stat.OT]Statistical Analysis of Quantum Annealing

·····································

• [cond-mat.str-el]Gauge Invariant Autoregressive Neural Networks for Quantum Lattice Models
Di Luo, Zhuo Chen, Kaiwen Hu, Zhizhen Zhao, Vera Mikyoung Hur, Bryan K. Clark
http://arxiv.org/abs/2101.07243v1

• [cs.AI]A Layer-Wise Information Reinforcement Approach to Improve Learning in Deep Belief Networks
Mateus Roder, Leandro A. Passos, Luiz Carlos Felix Ribeiro, Clayton Pereira, João Paulo Papa
http://arxiv.org/abs/2101.06749v1

• [cs.AI]A Literature Review of Recent Graph Embedding Techniques for Biomedical Data
Yankai Chen, Yaozu Wu, Shicheng Ma, Irwin King
http://arxiv.org/abs/2101.06569v1

• [cs.AI]Adversarial Interaction Attack: Fooling AI to Misinterpret Human Intentions
Nodens Koren, Qiuhong Ke, Yisen Wang, James Bailey, Xingjun Ma
http://arxiv.org/abs/2101.06704v1

• [cs.AI]An Empirical Comparison of Deep Learning Models for Knowledge Tracing on Large-Scale Dataset
Shalini Pandey, George Karypis, Jaideep Srivastava
http://arxiv.org/abs/2101.06373v1

• [cs.AI]An attention model to analyse the risk of agitation and urinary tract infections in people with dementia
Honglin Li, Roonak Rezvani, Magdalena Anita Kolanko, David J. Sharp, Maitreyee Wairagkar, Ravi Vaidyanathan, Ramin Nilforooshan, Payam Barnaghi
http://arxiv.org/abs/2101.07007v1

• [cs.AI]Artificial Intelligence for Emotion-Semantic Trending and People Emotion Detection During COVID-19 Social Isolation
Hamed Jelodar, Rita Orji, Stan Matwin, Swarna Weerasinghe, Oladapo Oyebode, Yongli Wang
http://arxiv.org/abs/2101.06484v1

• [cs.AI]CaEGCN: Cross-Attention Fusion based Enhanced Graph Convolutional Network for Clustering
Guangyu Huo, Yong Zhang, Junbin Gao, Boyue Wang, Yongli Hu, Baocai Yin
http://arxiv.org/abs/2101.06883v1

• [cs.AI]Data Obsolescence Detection in the Light of Newly Acquired Valid Observations
Salma Chaieb, Ali Ben Mrad, Brahim Hnich, Véronique Delcroix
http://arxiv.org/abs/2101.07067v1

• [cs.AI]Faster Convergence in Deep-Predictive-Coding Networks to Learn Deeper Representations
Isaac J. Sledge, Jose C. Principe
http://arxiv.org/abs/2101.06848v1

• [cs.AI]Learning the Implicit Semantic Representation on Graph-Structured Data
Likang Wu, Zhi Li, Hongke Zhao, Qi Liu, Jun Wang, Mengdi Zhang, Enhong Chen
http://arxiv.org/abs/2101.06471v1

• [cs.AI]On the Generalizability of Motion Models for Road Users in Heterogeneous Shared Traffic Spaces
Fatema T. Johora, Dongfang Yang, Jörg P. Müller, Ümit Özgüner
http://arxiv.org/abs/2101.06974v1

• [cs.AI]Solving QSAT problems with neural MCTS
Ruiyang Xu, Karl Lieberherr
http://arxiv.org/abs/2101.06619v1

• [cs.AI]Understanding in Artificial Intelligence
Stefan Maetschke, David Martinez Iraola, Pieter Barnard, Elaheh ShafieiBavani, Peter Zhong, Ying Xu, Antonio Jimeno Yepes
http://arxiv.org/abs/2101.06573v1

• [cs.CE]Cell division in deep material networks applied to multiscale strain localization modeling
Zeliang Liu
http://arxiv.org/abs/2101.07226v1

• [cs.CE]Optical Flow Method for Measuring Deformation of Soil Specimen Subjected to Torsional Shearing
Piotr E. Srokosz, Marcin Bujko, Marta Bocheńska, Rafał Ossowski
http://arxiv.org/abs/2101.07005v1

• [cs.CG]Computer Aided Formal Design of Swarm Robotics Algorithms
Thibaut Balabonski, Pierre Courtieu, Robin Pelle, Lionel Rieg, Sébastien Tixeuil, Xavier Urbain
http://arxiv.org/abs/2101.06966v1

• [cs.CL]Abstractive Opinion Tagging
Qintong Li, Piji Li, Xinyi Li, Zhaochun Ren, Zhumin Chen, Maarten de Rijke
http://arxiv.org/abs/2101.06880v1

• [cs.CL]Can a Fruit Fly Learn Word Embeddings?
Yuchen Liang, Chaitanya K. Ryali, Benjamin Hoover, Leopold Grinberg, Saket Navlakha, Mohammed J. Zaki, Dmitry Krotov
http://arxiv.org/abs/2101.06887v1

• [cs.CL]ComQA:Compositional Question Answering via Hierarchical Graph Neural Networks
Bingning Wang, Ting Yao, Weipeng Chen, Jingfang Xu, Xiaochuan Wang
http://arxiv.org/abs/2101.06400v1

• [cs.CL]Comparison of Machine Learning for Sentiment Analysis in Detecting Anxiety Based on Social Media Data
Shoffan Saifullah, Yuli Fauziah, Agus Sasmito Aribowo
http://arxiv.org/abs/2101.06353v1

• [cs.CL]Few Shot Dialogue State Tracking using Meta-learning
Saket Dingliwal, Bill Gao, Sanchit Agarwal, Chien-Wei Lin, Tagyoung Chung, Dilek Hakkani-Tur
http://arxiv.org/abs/2101.06779v1

• [cs.CL]Fusing Wav2vec2.0 and BERT into End-to-end Model for Low-resource Speech Recognition
Cheng Yi, Shiyu Zhou, Bo Xu
http://arxiv.org/abs/2101.06699v1

• [cs.CL]GENIE: A Leaderboard for Human-in-the-Loop Evaluation of Text Generation
Daniel Khashabi, Gabriel Stanovsky, Jonathan Bragg, Nicholas Lourie, Jungo Kasai, Yejin Choi, Noah A. Smith, Daniel S. Weld
http://arxiv.org/abs/2101.06561v1

• [cs.CL]Grid Search Hyperparameter Benchmarking of BERT, ALBERT, and LongFormer on DuoRC
Alex John Quijano, Sam Nguyen, Juanita Ordonez
http://arxiv.org/abs/2101.06326v1

• [cs.CL]HinFlair: pre-trained contextual string embeddings for pos tagging and text classification in the Hindi language
Harsh Patel
http://arxiv.org/abs/2101.06949v1

• [cs.CL]Incremental Knowledge Based Question Answering
Yongqi Li, Wenjie Li, Liqiang Nie
http://arxiv.org/abs/2101.06938v1

• [cs.CL]Joint Energy-based Model Training for Better Calibrated Natural Language Understanding Models
Tianxing He, Bryan McCann, Caiming Xiong, Ehsan Hosseini-Asl
http://arxiv.org/abs/2101.06829v1

• [cs.CL]Linguistically-Enriched and Context-Aware Zero-shot Slot Filling
A. B. Siddique, Fuad Jamour, Vagelis Hristidis
http://arxiv.org/abs/2101.06514v1

• [cs.CL]Match-Ignition: Plugging PageRank into Transformer for Long-form Text Matching
Liang Pang, Yanyan Lan, Xueqi Cheng
http://arxiv.org/abs/2101.06423v1

• [cs.CL]Model Compression for Domain Adaptation through Causal Effect Estimation
Guy Rotman, Amir Feder, Roi Reichart
http://arxiv.org/abs/2101.07086v1

• [cs.CL]Narration Generation for Cartoon Videos
Nikos Papasarantopoulos, Shay B. Cohen
http://arxiv.org/abs/2101.06803v1

• [cs.CL]Neural Abstractive Text Summarizer for Telugu Language
Mohan Bharath B, Aravindh Gowtham B, Akhil M
http://arxiv.org/abs/2101.07120v1

• [cs.CL]Red Alarm for Pre-trained Models: Universal Vulnerabilities by Neuron-Level Backdoor Attacks
Zhengyan Zhang, Guangxuan Xiao, Yongwei Li, Tian Lv, Fanchao Qi, Yasheng Wang, Xin Jiang, Zhiyuan Liu, Maosong Sun
http://arxiv.org/abs/2101.06969v1

• [cs.CL]Teach me how to Label: Labeling Functions from Natural Language with Text-to-text Transformers
Yannis Papanikolaou
http://arxiv.org/abs/2101.07138v1

• [cs.CL]TextGNN: Improving Text Encoder via Graph Neural Network in Sponsored Search
Jason Zhu, Yanling Cui, Yuming Liu, Hao Sun, Xue Li, Markus Pelger, Liangjie Zhang, Tianqi Yan, Ruofei Zhang, Huasha Zhao
http://arxiv.org/abs/2101.06323v1

• [cs.CL]To Understand Representation of Layer-aware Sequence Encoders as Multi-order-graph
Sufeng Duan, Hai Zhao, Rui Wang
http://arxiv.org/abs/2101.06397v1

• [cs.CL]Tuiteamos o pongamos un tuit? Investigating the Social Constraints of Loanword Integration in Spanish Social Media
Ian Stewart, Diyi Yang, Jacob Eisenstein
http://arxiv.org/abs/2101.06368v1

• [cs.CL]Weakly-Supervised Hierarchical Models for Predicting Persuasive Strategies in Good-faith Textual Requests
Jiaao Chen, Diyi Yang
http://arxiv.org/abs/2101.06351v1

• [cs.CL]What Makes Good In-Context Examples for GPT-?
Jiachang Liu, Dinghan Shen, Yizhe Zhang, Bill Dolan, Lawrence Carin, Weizhu Chen
http://arxiv.org/abs/2101.06804v1

• [cs.CR]A System for Efficiently Hunting for Cyber Threats in Computer Systems Using Threat Intelligence
Peng Gao, Fei Shao, Xiaoyuan Liu, Xusheng Xiao, Haoyuan Liu, Zheng Qin, Fengyuan Xu, Prateek Mittal, Sanjeev R. Kulkarni, Dawn Song
http://arxiv.org/abs/2101.06761v1

• [cs.CR]A Technical Report for Light-Edge: A Lightweight Authentication Protocol for IoT Devices in an Edge-Cloud Environment
Ali Shahidinejad, Mostafa Ghobaei-Arani, Alireza Souri, Mohammad Shojafar, Saru Kumari
http://arxiv.org/abs/2101.06676v1

• [cs.CR]DeepPayload: Black-box Backdoor Attack on Deep Learning Models through Neural Payload Injection
Yuanchun Li, Jiayi Hua, Haoyu Wang, Chunyang Chen, Yunxin Liu
http://arxiv.org/abs/2101.06896v1

• [cs.CR]Leveraging AI to optimize website structure discovery during Penetration Testing
Diego Antonelli, Roberta Cascella, Gaetano Perrone, Simon Pietro Romano, Antonio Schiano
http://arxiv.org/abs/2101.07223v1

• [cs.CR]SEDAT:Security Enhanced Device Attestation with TPM2.0
Avani Dave, Monty Wiseman, David Safford
http://arxiv.org/abs/2101.06362v1

• [cs.CV]A relic sketch extraction framework based on detail-aware hierarchical deep network
Jinye Peng, Jiaxin Wang, Jun Wang, Erlei Zhang, Qunxi Zhang, Yongqin Zhang, Xianlin Peng, Kai Yu
http://arxiv.org/abs/2101.06616v1

• [cs.CV]ACP: Automatic Channel Pruning via Clustering and Swarm Intelligence Optimization for CNN
Jingfei Chang, Yang Lu, Ping Xue, Yiqun Xu, Zhen Wei
http://arxiv.org/abs/2101.06407v1

• [cs.CV]Adaptive Graph Representation Learning and Reasoning for Face Parsing
Gusi Te, Wei Hu, Yinglu Liu, Hailin Shi, Tao Mei
http://arxiv.org/abs/2101.07034v1

• [cs.CV]Adaptive Remote Sensing Image Attribute Learning for Active Object Detection
Nuo Xu, Chunlei Huo, Jiacheng Guo, Yiwei Liu, Jian Wang, Chunhong Pan
http://arxiv.org/abs/2101.06438v1

• [cs.CV]Assisting Barrett’s esophagus identification using endoscopic data augmentation based on Generative Adversarial Networks
Luis A. de Souza Jr., Leandro A. Passos, Robert Mendel, Alanna Ebigbo, Andreas Probst, Helmut Messmann, Christoph Palm, João P. Papa
http://arxiv.org/abs/2101.07209v1

• [cs.CV]Auto4D: Learning to Label 4D Objects from Sequential Point Clouds
Bin Yang, Min Bai, Ming Liang, Wenyuan Zeng, Raquel Urtasun
http://arxiv.org/abs/2101.06586v1

• [cs.CV]Bladder segmentation based on deep learning approaches: current limitations and lessons
Mark G. Bandyk, Dheeraj R Gopireddy, Chandana Lall, K. C. Balaji, Jose Dolz
http://arxiv.org/abs/2101.06498v1

• [cs.CV]CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Detection in Remote Sensing Images
Qi Ming, Lingjuan Miao, Zhiqiang Zhou, Yunpeng Dong
http://arxiv.org/abs/2101.06849v1

• [cs.CV]CLASTER: Clustering with Reinforcement Learning for Zero-Shot Action Recognition
Shreyank N Gowda, Laura Sevilla-Lara, Frank Keller, Marcus Rohrbach
http://arxiv.org/abs/2101.07042v1

• [cs.CV]Catching Out-of-Context Misinformation with Self-supervised Learning
Shivangi Aneja, Christoph Bregler, Matthias Nießner
http://arxiv.org/abs/2101.06278v1

• [cs.CV]Chaotic-to-Fine Clustering for Unlabeled Plant Disease Images
Uno Fang, Jianxin Li, Xuequan Lu, Mumtaz Ali, Longxiang Gao, Yong Xiang
http://arxiv.org/abs/2101.06820v1

• [cs.CV]CheXtransfer: Performance and Parameter Efficiency of ImageNet Models for Chest X-Ray Interpretation
Alexander Ke, William Ellsworth, Oishi Banerjee, Andrew Y. Ng, Pranav Rajpurkar
http://arxiv.org/abs/2101.06871v1

• [cs.CV]Coarse Temporal Attention Network (CTA-Net) for Driver’s Activity Recognition
Zachary Wharton, Ardhendu Behera, Yonghuai Liu, Nik Bessis
http://arxiv.org/abs/2101.06636v1

• [cs.CV]Context-aware Attentional Pooling (CAP) for Fine-grained Visual Classification
Ardhendu Behera, Zachary Wharton, Pradeep Hewage, Asish Bera
http://arxiv.org/abs/2101.06635v1

• [cs.CV]Cross-modal Learning for Domain Adaptation in 3D Semantic Segmentation
Maximilian Jaritz, Tuan-Hung Vu, Raoul de Charette, Émilie Wirbel, Patrick Pérez
http://arxiv.org/abs/2101.07253v1

• [cs.CV]Deep Learning based Virtual Point Tracking for Real-Time Target-less Dynamic Displacement Measurement in Railway Applications
Dachuan Shi, Eldar Sabanovic, Luca Rizzetto, Viktor Skrickij, Roberto Oliverio, Nadia Kaviani, Yunguang Ye, Gintautas Bureika, Stefano Ricci, Markus Hecht
http://arxiv.org/abs/2101.06702v1

• [cs.CV]Deep Multi-Task Learning for Joint Localization, Perception, and Prediction
John Phillips, Julieta Martinez, Ioan Andrei Bârsan, Sergio Casas, Abbas Sadat, Raquel Urtasun
http://arxiv.org/abs/2101.06720v1

• [cs.CV]Deep Parametric Continuous Convolutional Neural Networks
Shenlong Wang, Simon Suo, Wei-Chiu Ma, Andrei Pokrovsky, Raquel Urtasun
http://arxiv.org/abs/2101.06742v1

• [cs.CV]Deep Structured Reactive Planning
Jerry Liu, Wenyuan Zeng, Raquel Urtasun, Ersin Yumer
http://arxiv.org/abs/2101.06832v1

• [cs.CV]Deep Universal Blind Image Denoising
Jae Woong Soh, Nam Ik Cho
http://arxiv.org/abs/2101.07017v1

• [cs.CV]DeepMI: A Mutual Information Based Framework For Unsupervised Deep Learning of Tasks
Ashish Kumar, Laxmidhar Behera
http://arxiv.org/abs/2101.06411v1

• [cs.CV]Diversified Patch-based Style Transfer with Shifted Style Normalization
Zhizhong Wang, Lei Zhao, Haibo Chen, Zhiwen Zuo, Ailin Li, Wei Xing, Dongming Lu
http://arxiv.org/abs/2101.06381v1

• [cs.CV]Dual-Level Collaborative Transformer for Image Captioning
Yunpeng Luo, Jiayi Ji, Xiaoshuai Sun, Liujuan Cao, Yongjian Wu, Feiyue Huang, Chia-Wen Lin, Rongrong Ji
http://arxiv.org/abs/2101.06462v1

• [cs.CV]End-to-end Interpretable Neural Motion Planner
Wenyuan Zeng, Wenjie Luo, Simon Suo, Abbas Sadat, Bin Yang, Sergio Casas, Raquel Urtasun
http://arxiv.org/abs/2101.06679v1

• [cs.CV]Exploring Adversarial Robustness of Multi-Sensor Perception Systems in Self Driving
James Tu, Huichen Li, Xinchen Yan, Mengye Ren, Yun Chen, Ming Liang, Eilyan Bitar, Ersin Yumer, Raquel Urtasun
http://arxiv.org/abs/2101.06784v1

• [cs.CV]Generalized Image Reconstruction over T-Algebra
Liang Liao, Xuechun Zhang, Xinqiang Wang, Sen Lin, Xin Liu
http://arxiv.org/abs/2101.06650v1

• [cs.CV]Generating Attribution Maps with Disentangled Masked Backpropagation
Adria Ruiz, Antonio Agudo, Francesc Moreno
http://arxiv.org/abs/2101.06773v1

• [cs.CV]GeoSim: Photorealistic Image Simulation with Geometry-Aware Composition
Yun Chen, Frieda Rong, Shivam Duggal, Shenlong Wang, Xinchen Yan, Sivabalan Manivasagam, Shangjie Xue, Ersin Yumer, Raquel Urtasun
http://arxiv.org/abs/2101.06543v1

• [cs.CV]GridTracer: Automatic Mapping of Power Grids using Deep Learning and Overhead Imagery
Bohao Huang, Jichen Yang, Artem Streltsov, Kyle Bradbury, Leslie M. Collins, Jordan Malof
http://arxiv.org/abs/2101.06390v1

• [cs.CV]HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Network that Achieves over 0.9 Mean Dice and 86 FPS
Chien-Hsiang Huang, Hung-Yu Wu, Youn-Long Lin
http://arxiv.org/abs/2101.07172v1

• [cs.CV]Heterogeneous Hand Guise Classification Based on Surface Electromyographic Signals Using Multichannel Convolutional Neural Network
Niloy Sikder, Abu Shamim Mohammad Arif, Abdullah-Al Nahid
http://arxiv.org/abs/2101.06715v1

• [cs.CV]Human Activity Recognition Using Multichannel Convolutional Neural Network
Niloy Sikder, Md. Sanaullah Chowdhury, Abu Shamim Mohammad Arif, Abdullah-Al Nahid
http://arxiv.org/abs/2101.06709v1

• [cs.CV]HySTER: A Hybrid Spatio-Temporal Event Reasoner
Theophile Sautory, Nuri Cingillioglu, Alessandra Russo
http://arxiv.org/abs/2101.06644v1

• [cs.CV]Improving Apparel Detection with Category Grouping and Multi-grained Branches
Qing Tian, Sampath Chanda, K C Amit Kumar, Douglas Gray
http://arxiv.org/abs/2101.06770v1

• [cs.CV]Intestinal Parasites Classification Using Deep Belief Networks
Mateus Roder, Leandro A. Passos, Luiz Carlos Felix Ribeiro, Barbara Caroline Benato, Alexandre Xavier Falcão, João Paulo Papa
http://arxiv.org/abs/2101.06747v1

• [cs.CV]KCP: Kernel Cluster Pruning for Dense Labeling Neural Networks
Po-Hsiang Yu, Sih-Sian Wu, Liang-Gee Chen
http://arxiv.org/abs/2101.06686v1

• [cs.CV]LNSMM: Eye Gaze Estimation With Local Network Share Multiview Multitask
Yong Huang, 642a
Ben Chen, Daiming Qu
http://arxiv.org/abs/2101.07116v1

• [cs.CV]Label-Efficient Point Cloud Semantic Segmentation: An Active Learning Approach
Xian Shi, Xun Xu, Ke Chen, Lile Cai, Chuan Sheng Foo, Kui Jia
http://arxiv.org/abs/2101.06931v1

• [cs.CV]LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting
Wenyuan Zeng, Ming Liang, Renjie Liao, Raquel Urtasun
http://arxiv.org/abs/2101.06653v1

• [cs.CV]Latent Variable Models for Visual Question Answering
Zixu Wang, Yishu Miao, Lucia Specia
http://arxiv.org/abs/2101.06399v1

• [cs.CV]MultiBodySync: Multi-Body Segmentation and Motion Estimation via 3D Scan Synchronization
Jiahui Huang, He Wang, Tolga Birdal, Minhyuk Sung, Federica Arrigoni, Shi-Min Hu, Leonidas Guibas
http://arxiv.org/abs/2101.06605v1

• [cs.CV]Network Automatic Pruning: Start NAP and Take a Nap
Wenyuan Zeng, Yuwen Xiong, Raquel Urtasun
http://arxiv.org/abs/2101.06608v1

• [cs.CV]Non-parametric Memory for Spatio-Temporal Segmentation of Construction Zones for Self-Driving
Min Bai, Shenlong Wang, Kelvin Wong, Ersin Yumer, Raquel Urtasun
http://arxiv.org/abs/2101.06865v1

• [cs.CV]Optical Flow Estimation via Motion Feature Recovery
Yang Jiao, Guangming Shi, Trac D. Tran
http://arxiv.org/abs/2101.06333v1

• [cs.CV]PLUME: Efficient 3D Object Detection from Stereo Images
Yan Wang, Bin Yang, Rui Hu, Ming Liang, Raquel Urtasun
http://arxiv.org/abs/2101.06594v1

• [cs.CV]Real Time Incremental Foveal Texture Mapping for Autonomous Vehicles
Ashish Kumar, James R. McBride, Gaurav Pandey
http://arxiv.org/abs/2101.06393v1

• [cs.CV]Regional Attention Network (RAN) for Head Pose and Fine-grained Gesture Recognition
Ardhendu Behera, Zachary Wharton, Morteza Ghahremani, Swagat Kumar, Nik Bessis
http://arxiv.org/abs/2101.06634v1

• [cs.CV]S3: Neural Shape, Skeleton, and Skinning Fields for 3D Human Modeling
Ze Yang, Shenlong Wang, Sivabalan Manivasagam, Zeng Huang, Wei-Chiu Ma, Xinchen Yan, Ersin Yumer, Raquel Urtasun
http://arxiv.org/abs/2101.06571v1

• [cs.CV]SceneGen: Learning to Generate Realistic Traffic Scenes
Shuhan Tan, Kelvin Wong, Shenlong Wang, Sivabalan Manivasagam, Mengye Ren, Raquel Urtasun
http://arxiv.org/abs/2101.06541v1

• [cs.CV]Secrets of 3D Implicit Object Shape Reconstruction in the Wild
Shivam Duggal, Zihao Wang, Wei-Chiu Ma, Sivabalan Manivasagam, Justin Liang, Shenlong Wang, Raquel Urtasun
http://arxiv.org/abs/2101.06860v1

• [cs.CV]Self-Supervised Representation Learning from Flow Equivariance
Yuwen Xiong, Mengye Ren, Wenyuan Zeng, Raquel Urtasun
http://arxiv.org/abs/2101.06553v1

• [cs.CV]Semi Supervised Deep Quick Instance Detection and Segmentation
Ashish Kumar, L. Behera
http://arxiv.org/abs/2101.06405v1

• [cs.CV]Semi-Automatic Video Annotation For Object Detection
Kutalmis Gokalp Ince, Aybora Koksal, Arda Fazla, A. Aydin Alatan
http://arxiv.org/abs/2101.06977v1

• [cs.CV]Separable Batch Normalization for Robust Facial Landmark Localization with Cross-protocol Network Training
Shuangping Jin, Zhenhua Feng, Wankou Yang, Josef Kittler
http://arxiv.org/abs/2101.06663v1

• [cs.CV]Shape Back-Projection In 3D Scenes
Ashish Kumar, L. Behera
http://arxiv.org/abs/2101.06409v1

• [cs.CV]TLU-Net: A Deep Learning Approach for Automatic Steel Surface Defect Detection
Praveen Damacharla, Achuth Rao M. V., Jordan Ringenberg, Ahmad Y Javaid
http://arxiv.org/abs/2101.06915v1

• [cs.CV]Temporal Spatial-Adaptive Interpolation with Deformable Refinement for Electron Microscopic Images
Zejin Wang, Guodong Sun, Lina Zhang, Guoqing Li, Hua Han
http://arxiv.org/abs/2101.06771v1

• [cs.CV]Trilevel Neural Architecture Search for Efficient Single Image Super-Resolution
Yan Wu, Zhiwu Huang, Suryansh Kumar, Rhea Sanjay Sukthanker, Radu Timofte, Luc Van Gool
http://arxiv.org/abs/2101.06658v1

• [cs.CV]Unsupervised Noisy Tracklet Person Re-identification
Minxian Li, Xiatian Zhu, Shaogang Gong
http://arxiv.org/abs/2101.06391v1

• [cs.CV]VideoClick: Video Object Segmentation with a Single Click
Namdar Homayounfar, Justin Liang, Wei-Chiu Ma, Raquel Urtasun
http://arxiv.org/abs/2101.06545v1

• [cs.CV]What Do Deep Nets Learn? Class-wise Patterns Revealed in the Input Space
Shihao Zhao, Xingjun Ma, Yisen Wang, James Bailey, Bo Li, Yu-Gang Jiang
http://arxiv.org/abs/2101.06898v1

• [cs.CY]AR-based Modern Healthcare: A Review
Jinat Ara, Hanif Bhuiyan, Yeasin Arafat Bhuiyan, Salma Begum Bhyan, Muhammad Ismail Bhuiyan
http://arxiv.org/abs/2101.06364v1

• [cs.CY]Capitol (Pat)riots: A comparative study of Twitter and Parler
Hitkul, Avinash Prabhu, Dipanwita Guhathakurta, Jivitesh jain, Mallika Subramanian, Manvith Reddy, Shradha Sehgal, Tanvi Karandikar, Amogh Gulati, Udit Arora, Rajiv Ratn Shah, Ponnurangam Kumaraguru
http://arxiv.org/abs/2101.06914v1

• [cs.CY]Impact of COVID-19 on Adoption of IoT in Different Sectors
Muhammad Umair, Muhammad Aamir Cheema, Omer Cheema, Huan Li, Hua Lu
http://arxiv.org/abs/2101.07196v1

• [cs.CY]The BIVEE Project: an overview of methodology and tools
M. Missikoff, P. Assogna
http://arxiv.org/abs/2101.06736v1

• [cs.DB]AMALGAM: A Matching Approach to fairfy tabuLar data with knowledGe grAph Model
Rabia Azzi, Gayo Diallo
http://arxiv.org/abs/2101.06637v1

• [cs.DC]A Distributed Chunk Calculation Approach for Self-scheduling of Parallel Applications on Distributed-memory Systems
Ahmed Eleliemy, Florina M. Ciorba
http://arxiv.org/abs/2101.07050v1

• [cs.DC]Big Data application in congestion detection and classification using Apache spark
Atousa Zarindast, Anuj Sharma
http://arxiv.org/abs/2101.06524v1

• [cs.DC]Byzantine Generals in the Permi
1000
ssionless Setting
Andrew Lewis-Pye
http://arxiv.org/abs/2101.07095v1

• [cs.DC]DFOGraph: An I/O- and Communication-Efficient System for Distributed Fully-out-of-Core Graph Process
5000
ing
Jiping Yu, Wei Qin, Xiaowei Zhu, Zhenbo Sun, Jianqiang Huang, Xiaohan Li, Wenguang Chen
http://arxiv.org/abs/2101.06911v1

• [cs.DC]Demystifying Pythia: A Survey of ChainLink Oracles Usage on Ethereum
Mudabbir Kaleem, Weidong Shi
http://arxiv.org/abs/2101.06781v1

• [cs.DC]Galleon: Reshaping the Square Peg of NFV
Jianfeng Wang, Tamás Lévai, Zhuojin Li, Marcos A. M. Vieira, Ramesh Govindan, Barath Raghavan
http://arxiv.org/abs/2101.06466v1

• [cs.DC]T-Lease: A Trusted Lease Primitive for Distributed Systems
Bohdan Trach, Rasha Faqeh, Oleksii Oleksenko, Wojciech Ozga, Pramod Bhatotia, Christof Fetzer
http://arxiv.org/abs/2101.06485v1

• [cs.DC]Tailored Learning-Based Scheduling for Kubernetes-Oriented Edge-Cloud System
Yiwen Han, Shihao Shen, Xiaofei Wang, Shiqiang Wang, Victor C. M. Leung
http://arxiv.org/abs/2101.06582v1

• [cs.DC]Ten Simple Rules for Success with HPC, i.e. Responsibly BASHing that Linux Cluster
Jamie J. Alnasir
http://arxiv.org/abs/2101.06737v1

• [cs.DC]Time-Efficient and High-Quality Graph Partitioning for Graph Dynamic Scaling
Masatoshi Hanai, Nikos Tziritas, Toyotaro Suzumura, Wentong Cai, Georgios Theodoropoulos
http://arxiv.org/abs/2101.07026v1

• [cs.DC]Tuning the Frequency of Periodic Data Movements over Hybrid Memory Systems
Thaleia Dimitra Doudali, Daniel Zahka, Ada Gavrilovska
http://arxiv.org/abs/2101.07200v1

• [cs.DC]ZeRO-Offload: Democratizing Billion-Scale Model Training
Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi, Olatunji Ruwase, Shuangyan Yang, Minjia Zhang, Dong Li, Yuxiong He
http://arxiv.org/abs/2101.06840v1

• [cs.DM]A note on the price of bandit feedback for mistake-bounded online learning
Jesse Geneson
http://arxiv.org/abs/2101.06891v1

• [cs.DS]Data stream fusion for accurate quantile tracking and analysis
Massimo Cafaro, Catiuscia Melle, Italo Epicoco, Marco Pulimeno
http://arxiv.org/abs/2101.06758v1

• [cs.DS]Maximizing approximately k-submodular functions
Leqian Zheng, Hau Chan, Grigorios Loukides, Minming Li
http://arxiv.org/abs/2101.07157v1

• [cs.FL]A Passive Online Technique for Learning Hybrid Automata from Input/Output Traces
Iman Saberi, Fathiyeh Faghih, Farzad Sobhi Bavil
http://arxiv.org/abs/2101.07053v1

• [cs.HC]Dissecting the Meme Magic: Understanding Indicators of Virality in Image Memes
Chen Ling, Ihab AbuHilal, Jeremy Blackburn, Emiliano De Cristofaro, Savvas Zannettou, Gianluca Stringhini
http://arxiv.org/abs/2101.06535v1

• [cs.HC]Motor-Imagery-Based Brain Computer Interface using Signal Derivation and Aggregation Functions
Javier Fumanal-Idocin, Yu-Kai Wang, Chin-Teng Lin, Javier Fernández, Jose Antonio Sanz, Humberto Bustince
http://arxiv.org/abs/2101.06968v1

• [cs.IR]A Survey on Extraction of Causal Relations from Natural Language Text
Jie Yang, Soyeon Caren Han, Josiah Poon
http://arxiv.org/abs/2101.06426v1

• [cs.IR]A Zero Attentive Relevance Matching Networkfor Review Modeling in Recommendation System
Hansi Zeng, Zhichao Xu, Qingyao Ai
http://arxiv.org/abs/2101.06387v1

• [cs.IR]Controlling the Risk of Conversational Search via Reinforcement Learning
Zhenduo Wang, Qingyao Ai
http://arxiv.org/abs/2101.06327v1

• [cs.IR]ExpFinder: An Ensemble Expert Finding Model Integrating -gram Vector Space Model and CO-HITS
Yong-Bin Kang, Hung Du, Abdur Rahim Mohammad Forkan, Prem Prakash Jayaraman, Amir Aryani, Timos Sellis
http://arxiv.org/abs/2101.06821v1

• [cs.IR]Mitigating the Position Bias of Transformer Models in Passage Re-Ranking
Sebastian Hofstätter, Aldo Lipani, Sophia Althammer, Markus Zlabinger, Allan Hanbury
http://arxiv.org/abs/2101.06980v1

• [cs.IR]Reinforcement learning based recommender systems: A survey
M. Mehdi Afsar, Trafford Crump, Behrouz Far
http://arxiv.org/abs/2101.06286v1

• [cs.IR]Robustness of Meta Matrix Factorization Against Strict Privacy Constraints
Peter Müllner, Dominik Kowald, Elisabeth Lex
http://arxiv.org/abs/2101.06927v1

• [cs.IR]Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation
Junliang Yu, Hongzhi Yin, Jundong Li, Qinyong Wang, Nguyen Quoc Viet Hung, Xiangliang Zhang
http://arxiv.org/abs/2101.06448v1

• [cs.IR]Studying Catastrophic Forgetting in Neural Ranking Models
Jesus Lovon-Melgarejo, Laure Soulier, Karen Pinel-Sauvagnat, Lynda Tamine
http://arxiv.org/abs/2101.06984v1

• [cs.IR]Tip of the Tongue Known-Item Retrieval: A Case Study in Movie Identification
Jaime Arguello, Adam Ferguson, Emery Fine, Bhaskar Mitra, Hamed Zamani, Fernando Diaz
http://arxiv.org/abs/2101.07124v1

• [cs.IT]#card=math&code=%28%CE%B5%2C%20n%29) Fixed-Length Strong Coordination Capacity
Giulia Cervia, Tobias J. Oechtering, Mikael Skoglund
http://arxiv.org/abs/2101.06937v1

• [cs.IT]Aggregated Network for Massive MIMO CSI Feedback
Zhilin Lu, Hongyi He, Zhengyang Duan, Jintao Wang, Jian Song
http://arxiv.org/abs/2101.06618v1

• [cs.IT]Almost Optimal Construction of Functional Batch Codes Using Hadamard Codes
Lev Yohananov, Eitan Yaakobi
http://arxiv.org/abs/2101.06722v1

• [cs.IT]Deep Learning-Aided 5G Channel Estimation
An Le Ha, Trinh Van Chien, Tien Hoa Nguyen, Wan Choi, Van Duc Nguyen
http://arxiv.org/abs/2101.06666v1

• [cs.IT]Energy-Efficient RIS-assisted Satellites for IoT Networks
Kürşat Tekbıyık, Güneş Karabulut Kurt, Halim Yanikomeroglu
http://arxiv.org/abs/2101.07166v1

• [cs.IT]Fundamental Limits of Demand-Private Coded Caching
Chinmay Gurjarpadhye, Jithin Ravi, Sneha Kamath, Bikash Kumar Dey, Nikhil Karamchandani
http://arxiv.org/abs/2101.07127v1

• [cs.IT]Hierarchical Passive Beamforming for Reconfigurable Intelligent Surface Aided Communications
Chang Cai, Xiaojun Yuan, Wenjing Yan, Zhouyang Huang, Ying-Chang Liang, Wei Zhang
http://arxiv.org/abs/2101.06926v1

• [cs.IT]Improving Physical Layer Security for Reconfigurable Intelligent Surface aided NOMA 6G Networks
Zhe Zhang, Chensi Zhang, Chengjun Jiang, Fan Jia, Jianhua Ge, Fengkui Gong
http://arxiv.org/abs/2101.06948v1

• [cs.IT]Joint Beamforming and Location Optimization for Secure Data Collection in Wireless Sensor Networks with UAV-Carried Intelligent Reflecting Surface
Christantus O. Nnamani, Muhammad R. A. Khandaker, Mathini Sellathurai
http://arxiv.org/abs/2101.06565v1

• [cs.IT]Machine Learning-Enabled Joint Antenna Selection and Precoding Design: From Offline Complexity to Online Performance
Thang X. Vu, Symeon Chatzinotas, Van-Dinh Nguyen, Dinh Thai Hoang, Diep N. Nguyen, Marco Di Renzo, Bjorn Ottersten
http://arxiv.org/abs/2101.07004v1

• [cs.IT]New Low Rank Optimization Model and Convex Approach for Robust Spectral Compressed Sensing
Zai Yang, Xunmeng Wu
http://arxiv.org/abs/2101.06433v1

• [cs.IT]On linear codes with one-dimensional Euclidean hull and their applications to EAQECCs
Lin Sok
http://arxiv.org/abs/2101.06461v1

• [cs.IT]On the Asymptotic Performance Analysis of the k-th Best Link Selection over Non-identical Non-central Chi-square Fading Channels
Athira Subhash, Sheetal Kalyani, Yazan H. Al-Badarneh, Mohamed-Slim Alouini
http://arxiv.org/abs/2101.06978v1

• [cs.IT]Online Caching with Optimal Switching Regret
Samrat Mukhopadhyay, Abhishek Sinha
http://arxiv.org/abs/2101.07043v1

• [cs.IT]Optimal Pre-Processing to Achieve Fairness and Its Relationship with Total Variation Barycenter
Farhad Farokhi
http://arxiv.org/abs/2101.06811v1

• [cs.IT]Quartic Perturbation-based Outage-constrained Robust Design in Two-hop One-way Relay Networks
Sissi Xiaoxiao Wu, Sherry Xue-Ying Ni, Jiaying Li, Anthony Man-Cho So
http://arxiv.org/abs/2101.06907v1

• [cs.IT]Resolution Limits of Non-Adaptive 20 Questions Search for Multiple Targets
Lin Zhou, Alfred Hero
http://arxiv.org/abs/2101.06843v1

• [cs.IT]Stable Matching for Selection of Intelligent Reflecting Surfaces in Multiuser MISO Systems
Jawad Mirza, Bakhtiar Ali, Muhammad Awais Javed
http://arxiv.org/abs/2101.06502v1

• [cs.IT]The Broadcast Approach in Communication Networks
Ali Tajer, Avi Steiner, Shlomo Shamai
http://arxiv.org/abs/2101.07173v1

• [cs.IT]Uplink Beam Management for Millimeter Wave Cellular MIMO Systems with Hybrid Beamforming
George C. Alexandropoulos, Ioanna Vinieratou, Mattia Rebato, Luca Rose, Michele Zorzi
http://arxiv.org/abs/2101.07106v1

• [cs.LG]A multilevel clustering technique for community detection
Isa Inuwa-Dutse, Mark Liptrott, Yannis Korkontzelos
http://arxiv.org/abs/2101.06551v1

• [cs.LG]A simple geometric proof for the benefit of depth in ReLU networks
Asaf Amrami, Yoav Goldberg
http://arxiv.org/abs/2101.07126v1

• [cs.LG]Adversarial Attacks On Multi-Agent Communication
James Tu, Tsunhsuan Wang, Jingkang Wang, Sivabalan Manivasagam, Mengye Ren, Raquel Urtasun
http://arxiv.org/abs/2101.06560v1

• [cs.LG]Alignment and stability of embeddings: measurement and inference improvement
Furkan Gürsoy, Mounir Haddad, Cécile Bothorel
http://arxiv.org/abs/2101.07251v1

• [cs.LG]Analysis of key flavors of event-driven predictive maintenance using logs of phenomena described by Weibull distributions
Petros Petsinis, Athanasios Naskos, Anastasios Gounaris
http://arxiv.org/abs/2101.07033v1

• [cs.LG]Bayesian Inference Forgetting
Shaopeng Fu, Fengxiang He, Yue Xu, Dacheng Tao
http://arxiv.org/abs/2101.06417v1

• [cs.LG]Blockchain Assisted Decentralized Federated Learning (BLADE-FL): Performance Analysis and Resource Allocation
Jun Li, Yumeng Shao, Kang Wei, Ming Ding, Chuan Ma, Long Shi, Zhu Han, H. Vincent Poor
http://arxiv.org/abs/2101.06905v1

• [cs.LG]Classification of fNIRS Data Under Uncertainty: A Bayesian Neural Network Approach
Talha Siddique, Md Shaad Mahmud
http://arxiv.org/abs/2101.07128v1

• [cs.LG]Cooperative and Competitive Biases for Multi-Agent Reinforcement Learning
Heechang Ryu, Hayong Shin, Jinkyoo Park
http://arxiv.org/abs/2101.06890v1

• [cs.LG]Cost-Efficient Online Hyperparameter Optimization
Jingkang Wang, Mengye Ren, Ilija Bogunovic, Yuwen Xiong, Raquel Urtasun
http://arxiv.org/abs/2101.06590v1

• [cs.LG]Deep Compression of Neural Networks for Fault Detection on Tennessee Eastman Chemical Processes
Mingxuan Li, Yuanxun Shao
http://arxiv.org/abs/2101.06993v1

• [cs.LG]Deep Cox Mixtures for Survival Regression
Chirag Nagpal, Steve Yadlowsky, Negar Rostamzadeh, Katherine Heller
http://arxiv.org/abs/2101.06536v1

• [cs.LG]Deep Inertial Odometry with Accurate IMU Preintegration
Rooholla Khorrambakht, Chris Xiaoxuan Lu, Hamed Damirchi, Zhenghua Chen, Zhengguo Li
http://arxiv.org/abs/2101.07061v1

• [cs.LG]Deep Learning for Moving Blockage Predictionusing Real Millimeter Wave Measurements
Shunyao Wu, Muhammad Alrabeiah, Andrew Hredzak, Chaitali Chakrabarti, Ahmed Alkhateeb
http://arxiv.org/abs/2101.06886v1

• [cs.LG]Deep Reinforcement Learning for Active High Frequency Trading
Antonio Briola, Jeremy Turiel, Riccardo Marcaccioli, Tomaso Aste
http://arxiv.org/abs/2101.07107v1

• [cs.LG]Deep-Mobility: A Deep Learning Approach for an Efficient and Reliable 5G Handover
Rahul Arun Paropkari, Anurag Thantharate, Cory Beard
http://arxiv.org/abs/2101.06558v1

• [cs.LG]Detection of Insider Attacks in Distributed Projected Subgradient Algorithms
Sissi Xiaoxiao Wu, Gangqiang Li, Shengli Zhang, Xiaohui Lin
http://arxiv.org/abs/2101.06917v1

• [cs.LG]Discrete Graph Structure Learning for Forecasting Multiple Time Series
Chao Shang, Jie Chen, Jinbo Bi
http://arxiv.org/abs/2101.06861v1

• [cs.LG]Disentangling Observed Causal Effects from Latent Confounders using Method of Moments
Anqi Liu, Hao Liu, Tongxin Li, Saeed Karimi-Bidhendi, Yisong Yue, Anima Anandkumar
http://arxiv.org/abs/2101.06614v1

• [cs.LG]Diverse Complexity Measures for Dataset Curation in Self-driving
Abbas Sadat, Sean Segal, Sergio Casas, James Tu, Bin Yang, Raquel Urtasun, Ersin Yumer
http://arxiv.org/abs/2101.06554v1

• [cs.LG]Emotional EEG Classification using Connectivity Features and Convolutional Neural Networks
Seong-Eun Moon, Chun-Jui Chen, Cho-Jui Hsieh, Jane-Ling Wang, Jong-Seok Lee
http://arxiv.org/abs/2101.07069v1

• [cs.LG]Energy-based Dropout in Restricted Boltzmann Machines: Why not go random
Mateus Roder, Gustavo H. de Rosa, Victor Hugo C. de Albuquerque, André L. D. Rossi, João P. Papa
http://arxiv.org/abs/2101.06741v1

• [cs.LG]Estimating informativeness of samples with Smooth Unique Information
Hrayr Harutyunyan, Alessandro Achille, Giovanni Paolini, Orchid Majumder, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
http://arxiv.org/abs/2101.06640v1

• [cs.LG]Evaluating Online and Offline Accuracy Traversal Algorithms for k-Complete Neural Network Architectures
Yigit Alparslan, Ethan Jacob Moyer, Edward Kim
http://arxiv.org/abs/2101.06518v1

• [cs.LG]Fast and accurate learned multiresolution dynamical downscaling for precipitation
Jiali Wang, Zhengchun Liu, Ian Foster, Won Chang, Rajkumar Kettimuthu, Rao Kotamarthi
http://arxiv.org/abs/2101.06813v1

• [cs.LG]Free Lunch for Few-shot Learning: Distribution Calibration
Shuo Yang, Lu Liu, Min Xu
http://arxiv.org/abs/2101.06395v1

• [cs.LG]Fundamental Tradeoffs in Distributionally Adversarial Training
Mohammad Mehrabi, Adel Javanmard, Ryan A. Rossi, Anup Rao, Tung Mai
http://arxiv.org/abs/2101.06309v1

• [cs.LG]Generative Counterfactuals for Neural Networks via Attribute-Informed Perturbation
Fan Yang, Ninghao Liu, Mengnan Du, Xia Hu
http://arxiv.org/abs/2101.06930v1

• [cs.LG]GraphAttacker: A General Multi-Task GraphAttack Framework
Jinyin Chen, Dunjie Zhang, Zhaoyan Ming, Kejie Huang
http://arxiv.org/abs/2101.06855v1

• [cs.LG]Heterogeneous Similarity Graph Neural Network on Electronic Health Records
Zheng Liu, Xiaohan Li, Hao Peng, Lifang He, Philip S. Yu
http://arxiv.org/abs/2101.06800v1

• [cs.LG]Hierarchical Reinforcement Learning By Discovering Intrinsic Options
Jesse Zhang, Haonan Yu, Wei Xu
http://arxiv.org/abs/2101.06521v1

• [cs.LG]HyperNTF: A Hypergraph Regularized Nonnegative Tensor Factorization for Dimensionality Reduction
Wanguang Yin, Zhengming Ma, Quanying Liu
http://arxiv.org/abs/2101.06827v1

• [cs.LG]In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning
Mamshad Nayeem Rizve, Kevin Duarte, Yogesh S Rawat, Mubarak Shah
http://arxiv.org/abs/2101.06329v1

• [cs.LG]Interpretable Policy Specification and Synthesis through Natural Language and RL
Pradyumna Tambwekar, Andrew Silva, Nakul Gopalan, Matthew Gombolay
http://arxiv.org/abs/2101.07140v1

• [cs.LG]JITuNE: Just-In-Time Hyperparameter Tuning for Network Embedding Algorithms
Mengying Guo, Yuqing Zhu, Tao Yi, Yungang Bao
http://arxiv.org/abs/2101.06427v1

• [cs.LG]Learning DNN networks using un-rectifying ReLU with compressed sensing application
Wen-Liang Hwang, Shih-Shuo Tung
http://arxiv.org/abs/2101.06940v1

• [cs.LG]Learning Successor States and Goal-Dependent Values: A Mathematical Viewpoint
Léonard Blier, Corentin Tallec, Yann Ollivier
http://arxiv.org/abs/2101.07123v1

• [cs.LG]Learning from pandemics: using extraordinary events can improve disease now-casting models
Sara Mesquita, Cláudio Haupt Vieira, Lília Perfeito, Joana Gonçalves-Sá
http://arxiv.org/abs/2101.06774v1

• [cs.LG]Machine-Learning Mathematical Structures
Yang-Hui He
http://arxiv.org/abs/2101.06317v1

• [cs.LG]Measure-conditional Discriminator with Stationary Optimum for GANs and Statistical Distance Surrogates
Liu Yang, Tingwei Meng, George Em Karniadakis
http://arxiv.org/abs/2101.06802v1

• [cs.LG]Membership Inference Attack on Graph Neural Networks
Iyiola E. Olatunji, Wolfgang Nejdl, Megha Khosla
http://arxiv.org/abs/2101.06570v1

• [cs.LG]Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models
Justin Bayer, Maximilian Soelch, Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt
http://arxiv.org/abs/2101.07046v1

• [cs.LG]Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction
Qiang Zhou, Jingjing Gu, Xinjiang Lu, Fuzhen Zhuang, Yanchao Zhao, Qiuhong Wang, Xiao Zhang
http://arxiv.org/abs/2101.06954v1

• [cs.LG]Multi-Source Data Fusion for Cyberattack Detection in Power Systems
Abhijeet Sahu, Zeyu Mao, Patrick Wlazlo, Hao Huang, Katherine Davis, Ana Goulart, Saman Zonouz
http://arxiv.org/abs/2101.06897v1

• [cs.LG]Multi-objective Search of Robust Neural Architectures against Multiple Types of Adversarial Attacks
Jia Liu, Yaochu Jin
http://arxiv.org/abs/2101.06507v1

• [cs.LG]Multimodal Variational Autoencoders for Semi-Supervised Learning: In Defense of Product-of-Experts
Svetlana Kutuzova, Oswin Krause, Douglas McCloskey, Mads Nielsen, Christian Igel
http://arxiv.org/abs/2101.07240v1

• [cs.LG]NNStreamer: Efficient and Agile Development of On-Device AI Systems
MyungJoo Ham, Jijoong Moon, Geunsik Lim, Jaeyun Jung, Hyoungjoo Ahn, Wook Song, Sangjung Woo, Parichay Kapoor, Dongju Chae, Gichan Jang, Yongjoo Ahn, Jihoon Lee
http://arxiv.org/abs/2101.06371v1

• [cs.LG]On the Differentially Private Nature of Perturbed Gradient Descent
Thulasi Tholeti, Sheetal Kalyani
http://arxiv.org/abs/2101.06847v1

• [cs.LG]Online detection of failures generated by storage simulator
Kenenbek Arzymatov, Mikhail Hushchyn, Andrey Sapronov, Vladislav Belavin, Leonid Gremyachikh, Maksim Karpov, Andrey Ustyuzhanin
http://arxiv.org/abs/2101.07100v1

• [cs.LG]Phases of learning dynamics in artificial neural networks: with or without mislabeled data
Yu Feng, Yuhai Tu
http://arxiv.org/abs/2101.06509v1

• [cs.LG]Physics-Informed Deep Learning for Traffic State Estimation
Rongye Shi, Zhaobin Mo, Kuang Huang, Xuan Di, Qiang Du
http://arxiv.org/abs/2101.06580v1

• [cs.LG]Privacy-Preserving Learning of Human Activity Predictors in Smart Environments
Sharare Zehtabian, Siavash Khodadadeh, Ladislau Bölöni, Damla Turgut
http://arxiv.org/abs/2101.06564v1

• [cs.LG]Regularized Policies are Reward Robust
Hisham Husain, Kamil Ciosek, Ryota Tomioka
http://arxiv.org/abs/2101.07012v1

• [cs.LG]Removing Undesirable Feature Contributions Using Out-of-Distribution Data
Saehyung Lee, Changhwa Park, Hyungyu Lee, Jihun Yi, Jonghyun Lee, Sungroh Yoon
http://arxiv.org/abs/2101.06639v1

• [cs.LG]Robustness to Augmentations as a Generalization metric
Sumukh Aithal K, Dhruva Kashyap, Natarajan Subramanyam
http://arxiv.org/abs/2101.06459v1

• [cs.LG]Scaling Deep Contrastive Learning Batch Size with Almost Constant Peak Memory Usage
Luyu Gao, Yunyi Zhang
http://arxiv.org/abs/2101.06983v1

• [cs.LG]Screening for Sparse Online Learning
Jingwei Liang, Clarice Poon
http://arxiv.org/abs/2101.06982v1

• [cs.LG]SelfMatch: Combining Contrastive Self-Supervision and Consistency for Semi-Supervised Learning
Byoungjip Kim, Jinho Choo, Yeong-Dae Kwon, Seongho Joe, Seungjai Min, Youngjune Gwon
http://arxiv.org/abs/2101.06480v1

• [cs.LG]Slot Machines: Discovering Winning Combinations of Random Weights in Neural Networks
Maxwell Mbabilla Aladago, Lorenzo Torresani
http://arxiv.org/abs/2101.06475v1

• [cs.LG]Spatial Network Decomposition for Fast and Scalable AC-OPF Learning
Minas Chatzos, Terrence W. K. Mak, Pascal Van Hentenryck
http://arxiv.org/abs/2101.06768v1

• [cs.LG]Stable Recovery of Entangled Weights: Towards Robust Identification of Deep Neural Networks from Minimal Samples
Christian Fiedler, Massimo Fornasier, Timo Klock, Michael Rauchensteiner
http://arxiv.org/abs/2101.07150v1

• [cs.LG]Stable deep reinforcement learning method by predicting uncertainty in rewards as a subtask
Kanata Suzuki, Tetsuya Ogata
http://arxiv.org/abs/2101.06906v1

• [cs.LG]Stacked LSTM Based Deep Recurrent Neural Network with Kalman Smoothing for Blood Glucose Prediction
Md Fazle Rabby, Yazhou Tu, Md Imran Hossen, Insup Le, Anthony S Maida, Xiali Hei
http://arxiv.org/abs/2101.06850v1

• [cs.LG]Towards Searching Efficient and Accurate Neural Network Architectures in Binary Classification Problems
Yigit Alparslan, Ethan Jacob Moyer, Isamu Mclean Isozaki, Daniel Schwartz, Adam Dunlop, Shesh Dave, Edward Kim
http://arxiv.org/abs/2101.06511v1

• [cs.LG]Transferring model structure in Bayesian transfer learning for Gaussian process regression
Milan Papež, Anthony Quinn
http://arxiv.org/abs/2101.06884v1

• [cs.LG]Visual Analytics approach for finding spatiotemporal patterns from COVID19
Arunav Das
http://arxiv.org/abs/2101.06476v1

• [cs.LG]Yet Another Representation of Binary Decision Trees: A Mathematical Demonstration
Jinxiong Zhang
http://arxiv.org/abs/2101.07077v1

• [cs.MM]A Novel Local Binary Pattern Based Blind Feature Image Steganography
Soumendu Chakraborty, Anand Singh Jalal
http://arxiv.org/abs/2101.06383v1

• [cs.MM]Designing a mobile game to generate player data — lessons learned
William Wallis, William Kavanagh, Alice Miller, Tim Storer
http://arxiv.org/abs/2101.07144v1

• [cs.NE]A Spiking Central Pattern Generator for the control of a simulated lamprey robot running on SpiNNaker and Loihi neuromorphic boards
Emmanouil Angelidis, Emanuel Buchholz, Jonathan Patrick Arreguit O’Neil, Alexis Rougè, Terrence Stewart, Axel von Arnim, Alois Knoll, Auke Ijspeert
http://arxiv.org/abs/2101.07001v1

• [cs.NE]Performance Analysis and Improvement of Parallel Differential Evolution
Pan Zibin
http://arxiv.org/abs/2101.06599v1

• [cs.NI]Wi-Fi Wardriving Studies Must Account for Important Statistical Issues
Edward J Oughton, Julius Kusuma, Thibault Peyronel, Jon Crowcroft
http://arxiv.org/abs/2101.06301v1

• [cs.RO]A New Particle Filter Framework for Bayesian Receiver Autonomous Integrity Monitoring in Urban Environments
Shubh Gupta, Grace X. Gao
http://arxiv.org/abs/2101.06380v1

• [cs.RO]A Safe Hierarchical Planning Framework for Complex Driving Scenarios based on Reinforcement Learning
Jinning Li, Liting Sun, Masayoshi Tomizuka, Wei Zhan
http://arxiv.org/abs/2101.06778v1

• [cs.RO]AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles
Jingkang Wang, Ava Pun, James Tu, Sivabalan Manivasagam, Abbas Sadat, Sergio Casas, Mengye Ren, Raquel Urtasun
http://arxiv.org/abs/2101.06549v1

• [cs.RO]Asynchronous Multi-View SLAM
Anqi Joyce Yang, Can Cui, Ioan Andrei Bârsan, Raquel Urtasun, Shenlong Wang
http://arxiv.org/abs/2101.06562v1

• [cs.RO]Data-Driven Protection Levels for Camera and 3D Map-based Safe Urban Localization
Shubh Gupta, Grace X. Gao
http://arxiv.org/abs/2101.06379v1

• [cs.RO]Deep Reinforcement Learning with Embedded LQR Controllers
Wouter Caarls
http://arxiv.org/abs/2101.07175v1

• [cs.RO]Fast and Accurate Multi-Body Simulation with Stiff Viscoelastic Contacts
Bilal Hammoud, Luca Olivieri, Ludovic Righetti, Justin Carpentier, Andrea Del Prete
http://arxiv.org/abs/2101.06846v1

• [cs.RO]From hand to brain and back: Grip forces deliver insight into the functional plasticity of somatosensory processes
Birgitta Dresp-Langley
http://arxiv.org/abs/2101.06483v1

• [cs.RO]Generation of GelSight Tactile Images for Sim2Real Learning
Daniel Fernandes Gomes, Paolo Paoletti, Shan Luo
http://arxiv.org/abs/2101.07169v1

• [cs.RO]Kimera: from SLAM to Spatial Perception with 3D Dynamic Scene Graphs
Antoni Rosinol, Andrew Violette, Marcus Abate, Nathan Hughes, Yun Chang, Jingnan Shi, Arjun Gupta, Luca Carlone
http://arxiv.org/abs/2101.06894v1

• [cs.RO]Learning by Watching: Physical Imitation of Manipulation Skills from Human Videos
Haoyu Xiong, Quanzhou Li, Yun-Chun Chen, Homanga Bharadhwaj, Samarth Sinha, Animesh Garg
http://arxiv.org/abs/2101.07241v1

• [cs.RO]LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving
Alexander Cui, Abbas Sadat, Sergio Casas, Renjie Liao, Raquel Urtasun
http://arxiv.org/abs/2101.06547v1

• [cs.RO]MP3: A Unified Model to Map, Perceive, Predict and Plan
Sergio Casas, Abbas Sadat, Raquel Urtasun
http://arxiv.org/abs/2101.06806v1

• [cs.RO]MPC-MPNet: Model-Predictive Motion Planning Networks for Fast, Near-Optimal Planning under Kinodynamic Constraints
Linjun Li, Yinglong Miao, Ahmed H. Qureshi, Michael C. Yip
http://arxiv.org/abs/2101.06798v1

• [cs.RO]Online Robust Sliding-Windowed LiDAR SLAM in Natural Environments
Ha Pham-Quang, Huy Tran-Ngoc, Toan Nguyen-Thanh, Duc Ho-Tran-Minh, Vu Dinh-Quang
http://arxiv.org/abs/2101.06615v1

• [cs.RO]Predictive Processing in Cognitive Robotics: a Review
Alejandra Ciria, Guido Schillaci, Giovanni Pezzulo, Verena V. Hafner, Bruno Lara
http://arxiv.org/abs/2101.06611v1

• [cs.RO]Provably Constant-time Planning and Replanning for Real-time Grasping Objects off a Conveyor Belt
Fahad Islam, Oren Salzman, Aditya Agarwal, Maxim Likhachev
http://arxiv.org/abs/2101.07148v1

• [cs.RO]Slider: On the Design and Modeling of a 2D Floating Satellite Platform
Avijit Banerjee, Jakub Haluska, Sumeet G. Satpute, Dariusz Kominiak, George Nikolakopoulos
http://arxiv.org/abs/2101.06335v1

• [cs.RO]Soft Constrained Autonomous Vehicle Navigation using Gaussian Processes and Instance Segmentation
Bruno H. Groenner Barbosa, Neel P. Bhatt, Amir Khajepour, Ehsan Hashemi
http://arxiv.org/abs/2101.06901v1

• [cs.RO]Stereo Camera Visual SLAM with Hierarchical Masking and Motion-state Classification at Outdoor Construction Sites Containing Large Dynamic Objects
Runqiu Bao, Ren Komatsu, Renato Miyagusuku, Masaki Chino, Atsushi Yamashita, Hajime Asama
http://arxiv.org/abs/2101.06563v1

• [cs.RO]Towards Deep Learning Assisted Autonomous UAVs for Manipulation Tasks in GPS-Denied Environments
Ashish Kumar, Mohit Vohra, Ravi Prakash, L. Behera
http://arxiv.org/abs/2101.06414v1

• [cs.RO]TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviors
Simon Suo, Sebastian Regalado, Sergio Casas, Raquel Urtasun
http://arxiv.org/abs/2101.06557v1

• [cs.RO]TridentNet: A Cond
1000
itional Generative Model for Dynamic Trajectory Generation
David Paz, Hengyuan Zhang, Henrik I. Christensen
http://arxiv.org/abs/2101.06374v1

• [cs.RO]Wearable Sensors for Spatio-Temporal Grip Force Profiling
Rongrong Liu, Florent Nageotte, Philippe Zanne, Michel de Mathelin, Birgitta Dresp-Langley
http://arxiv.org/abs/2101.06479v1

• [cs.SD]Hierarchical disentangled representation learning for singing voice conversion
Naoya Takahashi, Mayank Kumar Singh, Yuki Mitsufuji
http://arxiv.org/abs/2101.06842v1

• [cs.SE]ConE: A Concurrent Edit Detection Tool for Large ScaleSoftware Development
Chandra Maddila, Nachiappan Nagappan, Christian Bird, Georgios Gousios, Arie van Deursen
http://arxiv.org/abs/2101.06542v1

• [cs.SI]“I Won the Election!”: An Empirical Analysis of Soft Moderation Interventions on Twitter
Savvas Zannettou
http://arxiv.org/abs/2101.07183v1

• [cs.SI]Characterizing Discourse about COVID-19 Vaccines: A Reddit Version of the Pandemic Story
Wei Wu, Hanjia Lyu, Jiebo Luo
http://arxiv.org/abs/2101.06321v1

• [cs.SI]Community Detection in Blockchain Social Networks
Sissi Xiaoxiao Wu, Zixian Wu, Shihui Chen, Gangqiang Li, Shengli Zhang
http://arxiv.org/abs/2101.06406v1

• [cs.SI]Digital Contact Tracing: Large-scale Geolocation Data as an Alternative to Bluetooth-based Apps’ Failure
José González Cabañas, Ángel Cuevas, Rubén Cuevas, Martin Maier
http://arxiv.org/abs/2101.07024v1

• [cs.SI]From Gen Z, Millennials, to Babyboomers: Portraits of Working from Home during the COVID-19 Pandemic
Ziyu Xiong, Pin Li, Hanjia Lyu, Jiebo Luo
http://arxiv.org/abs/2101.06762v1

• [cs.SI]PRESTO: Simple and Scalable Sampling Techniques for the Rigorous Approximation of Temporal Motif Counts
Ilie Sarpe, Fabio Vandin
http://arxiv.org/abs/2101.07152v1

• [cs.SI]Separating Controversy from Noise: Comparison and Normalization of Structural Polarization Measures
Ali Salloum, Ted Hsuan Yun Chen, Mikko Kivelä
http://arxiv.org/abs/2101.07009v1

• [cs.SI]Understanding Patterns of Users Who Repost Censored Posts on Weibo
Yichi Qian, Feng Yuan, Hanjia Lyu, Jiebo Luo
http://arxiv.org/abs/2101.06864v1

• [cs.SI]Unsupervised Link and Unlink Prediction on Dynamic Networks
Kun He, Christina Muro, Boyu Li
http://arxiv.org/abs/2101.06919v1

• [eess.AS]Mispronunciation Detection in Non-native (L2) English with Uncertainty Modeling
Daniel Korzekwa, Jaime Lorenzo-Trueba, Szymon Zaporowski, Shira Calamaro, Thomas Drugman, Bozena Kostek
http://arxiv.org/abs/2101.06396v1

• [eess.IV]A Hitchhiker’s Guide to Structural Similarity
Abhinau K. Venkataramanan, Chengyang Wu, Alan C. Bovik, Ioannis Katsavounidis, Zafar Shahid
http://arxiv.org/abs/2101.06354v1

• [eess.IV]A New Approach for Automatic Segmentation and Evaluation of Pigmentation Lesion by using Active Contour Model and Speeded Up Robust Features
Sara Mardanisamani, Zahra Karimi, Akram Jamshidzadeh, Mehran Yazdi, Melika Farshad, Amirmehdi Farshad
http://arxiv.org/abs/2101.07195v1

• [eess.IV]A Novel Registration & Colorization Technique for Thermal to Cross Domain Colorized Images
Suranjan Goswami, Satish Kumar Singh
http://arxiv.org/abs/2101.06910v1

• [eess.IV]Adversarial cycle-consistent synthesis of cerebral microbleeds for data augmentation
Khrystyna Faryna, Kevin Koschmieder, Marcella M. Paul, Thomas van den Heuvel, Anke van der Eerden, Rashindra Manniesing, Bram van Ginneken
http://arxiv.org/abs/2101.06468v1

• [eess.IV]Comparing Deep Learning strategies for paired but unregistered multimodal segmentation of the liver in T1 and T2-weighted MRI
Vincent Couteaux, Mathilde Trintignac, Olivier Nempont, Guillaume Pizaine, Anna Sesilia Vlachomitrou, Pierre-Jean Valette, Laurent Milot, Isabelle Bloch
http://arxiv.org/abs/2101.06979v1

• [eess.IV]Covid-19 classification with deep neural network and belief functions
Ling Huang, Su Ruan, Thierry Denoeux
http://arxiv.org/abs/2101.06958v1

• [eess.IV]Deep Symmetric Adaptation Network for Cross-modality Medical Image Segmentation
Xiaoting Han, Lei Qi, Qian Yu, Ziqi Zhou, Yefeng Zheng, Yinghuan Shi, Yang Gao
http://arxiv.org/abs/2101.06853v1

• [eess.IV]Iterative Facial Image Inpainting using Cyclic Reverse Generator
Yahya Dogan, Hacer Yalim Keles
http://arxiv.org/abs/2101.07036v1

• [eess.IV]Latent Space Analysis of VAE and Intro-VAE applied to 3-dimensional MR Brain Volumes of Multiple Sclerosis, Leukoencephalopathy, and Healthy Patients
Christopher Vogelsanger, Christian Federau
http://arxiv.org/abs/2101.06772v1

• [eess.IV]Optimized and autonomous machine learning framework for characterizing pores, particles, grains and grain boundaries in microstructural images
Roberto Perera, Davide Guzzetti, Vinamra Agrawal
http://arxiv.org/abs/2101.06474v1

• [eess.IV]Scale factor point spread function matching: Beyond aliasing in image resampling
M. Jorge Cardoso, Marc Modat, Tom Vercauteren, Sebastien Ourselin
http://arxiv.org/abs/2101.06440v1

• [eess.IV]Symmetric-Constrained Irregular Structure Inpainting for Brain MRI Registration with Tumor Pathology
Xiaofeng Liu, Fangxu Xing, Chao Yang, C. -C. Jay Kuo, Georges ElFakhri, Jonghye Woo
http://arxiv.org/abs/2101.06775v1

• [eess.IV]Uncertainty-Aware Body Composition Analysis with Deep Regression Ensembles on UK Biobank MRI
Taro Langner, Fredrik K. Gustafsson, Benny Avelin, Robin Strand, Håkan Ahlström, Joel Kullberg
http://arxiv.org/abs/2101.06963v1

• [eess.SY]Incorporating Coincidental Water Data into Non-intrusive Load Monitoring
Mohammad-Mehdi Keramati, Elnaz Azizi, Hamidreza Momeni, Sadegh Bolouki
http://arxiv.org/abs/2101.07190v1

• [eess.SY]Learning Robust Hybrid Control Barrier Functions for Uncertain Systems
Alexander Robey, Lars Lindemann, Stephen Tu, Nikolai Matni
http://arxiv.org/abs/2101.06492v1

• [eess.SY]Quantification of Disaggregation Difficulty with Respect to the Number of Meters
Elnaz Azizi, Mohammad T H Beheshti, Sadegh Bolouki
http://arxiv.org/abs/2101.07191v1

• [hep-ex]Hashing and metric learning for charged particle tracking
Sabrina Amrouche, Moritz Kiehn, Tobias Golling, Andreas Salzburger
http://arxiv.org/abs/2101.06428v1

• [math.AT]Hypernetworks: From Posets to Geometry
Emil Saucan
http://arxiv.org/abs/2101.06429v1

• [math.LO]Binary strings of finite VC dimension
Hunter R Johnson
http://arxiv.org/abs/2101.06490v1

• [math.NA]Deep neural network surrogates for non-smooth quantities of interest in shape uncertainty quantification
Laura Scarabosio
http://arxiv.org/abs/2101.07023v1

• [math.NA]GPU Methodologies for Numerical Partial Differential Equations
Andrew Gloster
http://arxiv.org/abs/2101.06550v1

• [math.NA]On the efficient parallel computing of long term reliable trajectories for the Lorenz system
I. Hristov, R. Hristova, S. Dimova, P. Armyanov, N. Shegunov, I. Puzynin, T. Puzynina, Z. Sharipov, Z. Tukhliev
http://arxiv.org/abs/2101.06682v1

• [math.NA]What was the river Ister in the time of Strabo? A mathematical approach
Karol Mikula, Martin Ambroz, Renata Mokosova
http://arxiv.org/abs/2101.06505v1

• [math.OA]Tracial smooth functions of non-commuting variables and the free Wasserstein manifold
David Jekel, Wuchen Li, Dimitri Shlyakhtenko
http://arxiv.org/abs/2101.06572v1

• [math.OC]TREGO: a Trust-Region Framework for Efficient Global Optimization
Youssef Diouane, Victor Picheny, Rodolphe Le Riche, Alexandre Scotto Di Perrotolo
http://arxiv.org/abs/2101.06808v1

• [math.PR]Asymptotics of running maxima for -subgaussian random double arrays
Nour Al Hayek, Illia Donhauzer, Rita Giuliano, Andriy Olenko, Andrei Volodin
http://arxiv.org/abs/2101.06366v1

• [math.PR]Wasserstein Convergence Rate for Empirical Measures of Markov Chains
Adrian Riekert
http://arxiv.org/abs/2101.06936v1

• [math.ST]Conditional Independence Testing in Hilbert Spaces with Applications to Functional Data Analysis
Anton Rask Lundborg, Rajen D. Shah, Jonas Peters
http://arxiv.org/abs/2101.07108v1

• [math.ST]Consistent Bayesian Community Detection
Sheng Jiang, Surya Tokdar
http://arxiv.org/abs/2101.06531v1

• [math.ST]Higher Order Targeted Maximum Likelihood Estimation
Mark van der Laan, Zeyi Wang, Lars van der Laan
http://arxiv.org/abs/2101.06290v1

• [physics.chem-ph]Data-driven discovery of multiscale chemical reactions governed by the law of mass action
Juntao Huang, Yizhou Zhou, Wen-An Yong
http://arxiv.org/abs/2101.06589v1

• [physics.soc-ph]Temporal Clustering of Disorder Events During the COVID-19 Pandemic
Gian Maria Campedelli, Maria Rita D’Orsogna
http://arxiv.org/abs/2101.06458v1

• [stat.AP]A deterministic matching method for exact matchings to compare the outcome of different interventions
Felix Bestehorn, Maike Bestehorn, Christian Kirches
http://arxiv.org/abs/2101.07029v1

• [stat.AP]Do In-Person Lectures Help? A Study of a Large Statistics Class
Ellen S. Fireman, Zachary S. Donnini, Daniel J. Eck, Michael B. Weissman
http://arxiv.org/abs/2101.06755v1

• [stat.AP]Generative Dynamics of Supreme Court Citations: Analysis with a New Statistical Network Model
Christian S. Schmid, Ted Hsuan Yun Chen, Bruce A. Desmarais
http://arxiv.org/abs/2101.07197v1

• [stat.AP]Making the most of imprecise measurements: Changing patterns of arsenic concentrations in shallow wells of Bangladesh from laboratory and field data
Yuling Yao, Rajib Mozumder, Benjamin Bostick, Brian Mailloux, Charles F. Harvey, Andrew Gelman, Alexander van Geen
http://arxiv.org/abs/2101.06631v1

• [stat.AP]Post-processing numerical weather prediction ensembles for probabilistic solar irradiance forecasting
Benedikt Schulz, Mehrez El Ayari, Sebastian Lerch, Sándor Baran
http://arxiv.org/abs/2101.06717v1

• [stat.CO]An MCMC Method to Sample from Lattice Distributions
Anand Jerry George, Navin Kashyap
http://arxiv.org/abs/2101.06453v1

• [stat.ME]Adaptive Change Point Monitoring for High-Dimensional Data
Teng Wu, Runmin Wang, Hao Yan, Xiaofeng Shao
http://arxiv.org/abs/2101.06839v1

• [stat.ME]Bias Reduction as a Remedy to the Consequences of Infinite Estimates in Poisson and Tobit Regression
Susanne Köll, Ioannis Kosmidis, Christian Kleiber, Achim Zeileis
http://arxiv.org/abs/2101.07141v1

• [stat.ME]Inference for BART with Multinomial Outcomes
Yizhen Xu, Joseph W. Hogan, Michael J. Daniels, Rami Kantor, Ann Mwangi
http://arxiv.org/abs/2101.06823v1

• [stat.ME]Model structures and structural identifiability: What? Why? How?
Jason M. Whyte
http://arxiv.org/abs/2101.06382v1

• [stat.ME]Novel Bayesian Procrustes Variance-based Inferences in Geometric Morphometrics & Novel R package: BPviGM1
Debashis Chatterjee
http://arxiv.org/abs/2101.06494v1

• [stat.ME]On the relationship between a Gamma distributed precision parameter and the associated standard deviation in the context of Bayesian parameter inference
Manuel M. Eichenlaub
http://arxiv.org/abs/2101.06289v1

• [stat.ME]Perturbations and Causality in Gaussian Models
Armeen Taeb, Peter Bühlmann
http://arxiv.org/abs/2101.06950v1

• [stat.ME]Query-Based Selection of Optimal Candidates under the Mallows Model
Xujun Liu, Olgica Milenkovic, George V. Moustakides
http://arxiv.org/abs/2101.07250v1

• [stat.ME]Robust Functional Principal Component Analysis via Functional Pairwise Spatial Signs
Guangxing Wang, Sisheng Liu, Fang Han, Chongzhi Di
http://arxiv.org/abs/2101.06415v1

• [stat.ME]Spatial deformation for non-stationary extremal dependence
Jordan Richards, Jennifer L. Wadsworth
http://arxiv.org/abs/2101.07167v1

• [stat.ME]TSEC: a framework for online experimentation under experimental constraints
Simon Mak, Yuanshuo Zhou, Lavonne Hoang, C. F. Jeff Wu
http://arxiv.org/abs/2101.06592v1

• [stat.ME]The Violating Assumptions Series: Simulated demonstrations to illustrate how assumptions can affect statistical estimates
Ian A Silver
http://arxiv.org/abs/2101.07097v1

• [stat.ME]Variance Estimation and Confidence Intervals from High-dimensional Genome-wide Association Studies Through Misspecified Mixed Model Analysis
Cecilia Dao, Jiming Jiang, Debashis Paul, Hongyu Zhao
http://arxiv.org/abs/2101.06638v1

• [stat.ML]Exponential Kernels with Latency in Hawkes Processes: Applications in Finance
Marcos Costa Santos Carreira
http://arxiv.org/abs/2101.06348v1

• [stat.ML]Identifying Treatment Effects under Unobserved Confounding by Causal Representation Learning
Pengzhou Wu, Kenji Fukumizu
http://arxiv.org/abs/2101.06662v1

• [stat.ML]Informative core identification in complex networks
Ruizhong Miao, Tianxi Li
http://arxiv.org/abs/2101.06388v1

• [stat.ML]Interactive slice visualization for exploring machine learning models
Catherine B. Hurley, Mark O’Connell, Katarina Domijan
http://arxiv.org/abs/2101.06986v1

• [stat.ML]Multi-view Data Visualisation via Manifold Learning
Theodoulos Rodosthenous, Vahid Shahrezaei, Marina Evangelou
http://arxiv.org/abs/2101.06763v1

• [stat.ML]On Data-Augmentation and Consistency-Based Semi-Supervised Learning
Atin Ghosh, Alexandre H. Thiery
http://arxiv.org/abs/2101.06967v1

• [stat.ML]Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary
Jean-Francois Rajotte, Sumit Mukherjee, Caleb Robinson, Anthony Ortiz, Christopher West, Juan Lavista Ferres, Raymond T Ng
http://arxiv.org/abs/2101.07235v1

• [stat.ML]Sensitivity Prewarping for Local Surrogate Modeling
Nathan Wycoff, Mickaël Binois, Robert B. Gramacy
http://arxiv.org/abs/2101.06296v1

• [stat.ML]The Connection between Discrete- and Continuous-Time Descriptions of Gaussian Continuous Processes
Federica Ferretti, Victor Chardès, Thierry Mora, Aleksandra M Walczak, Irene Giardina
http://arxiv.org/abs/2101.06482v1

• [stat.OT]Statistical Analysis of Quantum Annealing
Xinyu Song, Yazhen Wang, Shang Wu, Donggyu Kim
http://arxiv.org/abs/2101.06854v1