cond-mat.mtrl-sci - 材料科学

    cs.AI - 人工智能 cs.AR - 硬件体系结构 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.DL - 数字图书馆 cs.DS - 数据结构与算法 cs.GR - 计算机图形学 cs.GT - 计算机科学与博弈论 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.LO - 计算逻辑 cs.MA - 多代理系统 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.PF - 计算性能 cs.PL - 编程语言 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 econ.EM - 计量经济学 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 math-ph - 数学物理 math.PR - 概率 math.ST - 统计理论 physics.comp-ph - 计算物理学 physics.geo-ph - 地球物理学 physics.soc-ph - 物理学与社会 q-bio.NC - 神经元与认知 q-bio.QM - 定量方法 q-fin.ST - 统计金融学 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

    • [cond-mat.mtrl-sci]Current Overview of Statistical Fiber Bundles Model and Its Application to Physics-based Reliability Analysis of Thin-film Dielectrics
    • [cs.AI]Accelerating science with human versus alien artificial intelligences
    • [cs.AI]Artificial Intelligence Methods Based Hierarchical Classification of Frontotemporal Dementia to Improve Diagnostic Predictability
    • [cs.AI]Boltzmann Tuning of Generative Models
    • [cs.AI]Deep Attributed Network Representation Learning via Attribute Enhanced Neighborhood
    • [cs.AI]Interpretable Methods for Identifying Product Variants
    • [cs.AI]Learning dynamic and hierarchical traffic spatiotemporal features with Transformer
    • [cs.AI]Machine learning and deep learning
    • [cs.AI]MeToo Tweets Sentiment Analysis Using Multi Modal frameworks
    • [cs.AI]Multiple Run Ensemble Learning withLow-Dimensional Knowledge Graph Embeddings
    • [cs.AI]On Unifying Misinformation Detection
    • [cs.AI]Print Error Detection using Convolutional Neural Networks
    • [cs.AI]Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning
    • [cs.AI]Regression Networks For Calculating Englacial Layer Thickness
    • [cs.AI]Selection-Expansion: A Unifying Framework for Motion-Planning and Diversity Search Algorithms
    • [cs.AR]iELAS: An ELAS-Based Energy-Efficient Accelerator for Real-Time Stereo Matching on FPGA Platform
    • [cs.CL]Assessing Reference-Free Peer Evaluation for Machine Translation
    • [cs.CL]Backtranslation Feedback Improves User Confidence in MT, Not Quality
    • [cs.CL]Better Feature Integration for Named Entity Recognition
    • [cs.CL]Building a Swedish Open-Domain Conversational Language Model
    • [cs.CL]Combining exogenous and endogenous signals with a semi-supervised co-attention network for early detection of COVID-19 fake tweets
    • [cs.CL]Comparing the Benefit of Synthetic Training Data for Various Automatic Speech Recognition Architectures
    • [cs.CL]Constructing Contrastive samples via Summarization for Text Classification with limited annotations
    • [cs.CL]Contextualized Knowledge-aware Attentive Neural Network: Enhancing Answer Selection with Knowledge
    • [cs.CL]Continual Learning for Text Classification with Information Disentanglement Based Regularization
    • [cs.CL]Conversational Semantic Role Labeling
    • [cs.CL]Cross-Lingual Word Embedding Refinement by 今日学术视野(2021.4.14) - 图1 Norm Optimisation
    • [cs.CL]DATE: Detecting Anomalies in Text via Self-Supervision of Transformers
    • [cs.CL]Deep Learning for Prominence Detection in Children’s Read Speech
    • [cs.CL]Developing Annotated Resources for Internal Displacement Monitoring
    • [cs.CL]Disentangled Contrastive Learning for Learning Robust Textual Representations
    • [cs.CL]Disentangling Semantics and Syntax in Sentence Embeddings with Pre-trained Language Models
    • [cs.CL]Does syntax matter? A strong baseline for Aspect-based Sentiment Analysis with RoBERTa
    • [cs.CL]Double Perturbation: On the Robustness of Robustness and Counterfactual Bias Evaluation
    • [cs.CL]Edge: Enriching Knowledge Graph Embeddings with External Text
    • [cs.CL]Estimating Subjective Crowd-Evaluations as an Additional Objective to Improve Natural Language Generation
    • [cs.CL]Estimation of Summary-to-Text Inconsistency by Mismatched Embeddings
    • [cs.CL]FRAKE: Fusional Real-time Automatic Keyword Extraction
    • [cs.CL]FUDGE: Controlled Text Generation With Future Discriminators
    • [cs.CL]Factual Probing Is [MASK]: Learning vs. Learning to Recall
    • [cs.CL]Fine-Tuning Transformers for Identifying Self-Reporting Potential Cases and Symptoms of COVID-19 in Tweets
    • [cs.CL]Fine-tuning Encoders for Improved Monolingual and Zero-shot Polylingual Neural Topic Modeling
    • [cs.CL]Fool Me Twice: Entailment from Wikipedia Gamification
    • [cs.CL]FreSaDa: A French Satire Data Set for Cross-Domain Satire Detection
    • [cs.CL]HTCInfoMax: A Global Model for Hierarchical Text Classification via Information Maximization
    • [cs.CL]Identifying and Categorizing Offensive Language in Social Media
    • [cs.CL]Imperfect also Deserves Reward: Multi-Level and Sequential Reward Modeling for Better Dialog Management
    • [cs.CL]Innovative Bert-based Reranking Language Models for Speech Recognition
    • [cs.CL]Investigating Methods to Improve Language Model Integration for Attention-based Encoder-Decoder ASR Models
    • [cs.CL]Joint Universal Syntactic and Semantic Parsing
    • [cs.CL]Learning to Remove: Towards Isotropic Pre-trained BERT Embedding
    • [cs.CL]MIPT-NSU-UTMN at SemEval-2021 Task 5: Ensembling Learning with Pre-trained Language Models for Toxic Spans Detection
    • [cs.CL]Machine Translation Decoding beyond Beam Search
    • [cs.CL]Macro-Average: Rare Types Are Important Too
    • [cs.CL]Meta-learning for fast cross-lingual adaptation in dependency parsing
    • [cs.CL]Meta-tuning Language Models to Answer Prompts Better
    • [cs.CL]Multilingual Language Models Predict Human Reading Behavior
    • [cs.CL]NLI Data Sanity Check: Assessing the Effect of Data Corruption on Model Performance
    • [cs.CL]NeMo Inverse Text Normalization: From Development To Production
    • [cs.CL]Non-Autoregressive Semantic Parsing for Compositional Task-Oriented Dialog
    • [cs.CL]Non-autoregressive Transformer-based End-to-end ASR using BERT
    • [cs.CL]NorDial: A Preliminary Corpus of Written Norwegian Dialect Use
    • [cs.CL]Not All Attention Is All You Need
    • [cs.CL]On the Inductive Bias of Masked Language Modeling: From Statistical to Syntactic Dependencies
    • [cs.CL]Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages
    • [cs.CL]Self-Training with Weak Supervision
    • [cs.CL]Semantic Frame Forecast
    • [cs.CL]Sentiment-based Candidate Selection for NMT
    • [cs.CL]ShadowGNN: Graph Projection Neural Network for Text-to-SQL Parser
    • [cs.CL]Stay Together: A System for Single and Split-antecedent Anaphora Resolution
    • [cs.CL]StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer
    • [cs.CL]SuperSim: a test set for word similarity and relatedness in Swedish
    • [cs.CL]Survey on reinforcement learning for language processing
    • [cs.CL]Text2Chart: A Multi-Staged Chart Generator from Natural Language Text
    • [cs.CL]The Great Misalignment Problem in Human Evaluation of NLP Methods
    • [cs.CL]The structure of online social networks modulates the rate of lexical change
    • [cs.CL]TransWiC at SemEval-2021 Task 2: Transformer-based Multilingual and Cross-lingual Word-in-Context Disambiguation
    • [cs.CL]UTNLP at SemEval-2021 Task 5: A Comparative Analysis of Toxic Span Detection using Attention-based, Named Entity Recognition, and Ensemble Models
    • [cs.CL]UniDrop: A Simple yet Effective Technique to Improve Transformer without Extra Cost
    • [cs.CL]Unsupervised Learning of Explainable Parse Trees for Improved Generalisation
    • [cs.CL]Updater-Extractor Architecture for Inductive World State Representations
    • [cs.CL]WEC: Deriving a Large-scale Cross-document Event Coreference dataset from Wikipedia
    • [cs.CL]WHOSe Heritage: Classification of UNESCO World Heritage “Outstanding Universal Value” Documents with Smoothed Labels
    • [cs.CL]WLV-RIT at SemEval-2021 Task 5: A Neural Transformer Framework for Detecting Toxic Spans
    • [cs.CL]ZS-BERT: Towards Zero-Shot Relation Extraction with Attribute Representation Learning
    • [cs.CR]Supervised Feature Selection Techniques in Network Intrusion Detection: a Critical Review
    • [cs.CR]Using a Neural Network to Detect Anomalies given an N-gram Profile
    • [cs.CV]A Bop and Beyond: A Second Order Optimizer for Binarized Neural Networks
    • [cs.CV]A Learnable Self-supervised Task for Unsupervised Domain Adaptation on Point Clouds
    • [cs.CV]A Novel Unified Model for Multi-exposure Stereo Coding Based on Low Rank Tucker-ALS and 3D-HEVC
    • [cs.CV]A-FMI: Learning Attributions from Deep Networks via Feature Map Importance
    • [cs.CV]Action-Conditioned 3D Human Motion Synthesis with Transformer VAE
    • [cs.CV]Adversarial Open Domain Adaption for Sketch-to-Photo Synthesis
    • [cs.CV]All Labels Are Not Created Equal: Enhancing Semi-supervision via Label Grouping and Co-training
    • [cs.CV]An MRF-UNet Product of Experts for Image Segmentation
    • [cs.CV]Approach for modeling single branches of meadow orchard trees with 3D point clouds
    • [cs.CV]Behavioral Research and Practical Models of Drivers’ Attention
    • [cs.CV]Blazer: Laser Scanning Simulation using Physically Based Rendering
    • [cs.CV]CAPRI-Net: Learning Compact CAD Shapes with Adaptive Primitive Assembly
    • [cs.CV]Class-Balanced Distillation for Long-Tailed Visual Recognition
    • [cs.CV]Cloth In
    7180
    teractive Transformer for Virtual Try-On
    • [cs.CV]Coastline extraction from ALOS-2 satellite SAR images
    • [cs.CV]Cross-Modal Contrastive Learning for Abnormality Classification and Localization in Chest X-rays with Radiomics using a Feedback Loop
    • [cs.CV]Deep Recursive Embedding for High-Dimensional Data
    • [cs.CV]Deep learning using Havrda-Charvat entropy for classification of pulmonary endomicroscopy
    • [cs.CV]Deformable Capsules for Object Detection
    • [cs.CV]Diamond in the rough: Improving image realism by traversing the GAN latent space
    • [cs.CV]Do as we do: Multiple Person Video-To-Video Transfer
    • [cs.CV]Drafting and Revision: Laplacian Pyramid Network for Fast High-Quality Artistic Style Transfer
    • [cs.CV]Dual Discriminator Adversarial Distillation for Data-free Model Compression
    • [cs.CV]Egocentric Pose Estimation from Human Vision Span
    • [cs.CV]Enhancing Deep Neural Network Saliency Visualizations with Gradual Extrapolation
    • [cs.CV]Ensemble Learning based on Classifier Prediction Confidence and Comprehensive Learning Particle Swarm Optimisation for polyp localisation
    • [cs.CV]Error Propagation in Satellite Multi-image Geometry
    • [cs.CV]Escaping the Big Data Paradigm with Compact Transformers
    • [cs.CV]Estimation of BMI from Facial Images using Semantic Segmentation based Region-Aware Pooling
    • [cs.CV]Event-based Timestamp Image Encoding Network for Human Action Recognition and Anticipation
    • [cs.CV]Feature Decomposition and Reconstruction Learning for Effective Facial Expression Recognition
    • [cs.CV]Fine-Grained Attention for Weakly Supervised Object Localization
    • [cs.CV]Fruit Quality and Defect Image Classification with Conditional GAN Data Augmentation
    • [cs.CV]GAttANet: Global attention agreement for convolutional neural networks
    • [cs.CV]GR-RNN: Global-Context Residual Recurrent Neural Networks for Writer Identification
    • [cs.CV]GarmentNets: Category-Level Pose Estimation for Garments via Canonical Space Shape Completion
    • [cs.CV]Glance and Gaze: Inferring Action-aware Points for One-Stage Human-Object Interaction Detection
    • [cs.CV]Holistic Image Manipulation Detection using Pixel Co-occurrence Matrices
    • [cs.CV]Hyperspectral Pigment Analysis of Cultural Heritage Artifacts Using the Opaque Form of Kubelka-Munk Theory
    • [cs.CV]Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection
    • [cs.CV]Improving Online Performance Prediction
    83e
    for Semantic Segmentation
    • [cs.CV]Instagram Filter Removal on Fashionable Images
    • [cs.CV]Integrating Information Theory and Adversarial Learning for Cross-modal Retrieval
    • [cs.CV]Intra-Class Uncertainty Loss Function for Classification
    • [cs.CV]Latent Code-Based Fusion: A Volterra Neural Network Approach
    • [cs.CV]Learning Chebyshev Basis in Graph Convolutional Networks for Skeleton-based Action Recognition
    • [cs.CV]Learning Robust Visual-semantic Mapping for Zero-shot Learning
    • [cs.CV]Learning from 2D: Pixel-to-Point Knowledge Transfer for 3D Pretraining
    • [cs.CV]Learning from Subjective Ratings Using Auto-Decoded Deep Latent Embeddings
    • [cs.CV]Lip reading using external viseme decoding
    • [cs.CV]LocalViT: Bringing Locality to Vision Transformers
    • [cs.CV]Location-Sensitive Visual Recognition with Cross-IOU Loss
    • [cs.CV]Look Closer to Segment Better: Boundary Patch Refinement for Instance Segmentation
    • [cs.CV]Memory-guided Unsupervised Image-to-image Translation
    • [cs.CV]MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition
    • [cs.CV]MobileStyleGAN: A Lightweight Convolutional Neural Network for High-Fidelity Image Synthesis
    • [cs.CV]Neural Camera Simulators
    • [cs.CV]Object Priors for Classifying and Localizing Unseen Actions
    • [cs.CV]Object-Centric Representation Learning for Video Question Answering
    • [cs.CV]Occlusion Guided Self-supervised Scene Flow Estimation on 3D Point Clouds
    • [cs.CV]One Ring to Rule Them All: a simple solution to multi-view 3D-Reconstruction of shapes with unknown BRDF via a small Recurrent ResNet
    • [cs.CV]PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering Network
    • [cs.CV]Physically-Consistent Generative Adversarial Networks for Coastal Flood Visualization
    • [cs.CV]Predicting Pedestrian Crossing Intention with Feature Fusion and Spatio-Temporal Attention
    • [cs.CV]Preprocessing Methods of Lane Detection and Tracking for Autonomous Driving
    • [cs.CV]RPSRNet: End-to-End Trainable Rigid Point Set Registration Network using Barnes-Hut 今日学术视野(2021.4.14) - 图2-Tree Representation
    • [cs.CV]Raindrops on Windshield: Dataset and Lightweight Gradient-Based Detection Algorithm
    • [cs.CV]RayNet: Real-time Scene Arbitrary-shape Text Detection with Multiple Rays
    • [cs.CV]Research on Optimization Method of Multi-scale Fish Target Fast Detection Network
    • [cs.CV]Robust Classification from Noisy Labels: Integrating Additional Knowledge for Chest Radiography Abnormality Assessment
    • [cs.CV]Robust Egocentric Photo-realistic Facial Expression Transfer for Virtual Reality
    • [cs.CV]SCPM-Net: An Anchor-free 3D Lung Nodule Detection Network using Sphere Representation and Center Points Matching
    • [cs.CV]SIGAN: A Novel Image Generation Method for Solar Cell Defect Segmentation and Augmentation
    • [cs.CV]SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Clouds with 1000x Fewer Labels
    • [cs.CV]Self-supervised Multi-view Stereo via Effective Co-Segmentation and Data-Augmentation
    • [cs.CV]Shuffler: A Large Scale Data Management Tool for ML in Computer Vision
    • [cs.CV]StereoPIFu: Depth Aware Clothed Human Digitization via Stereo Vision
    • [cs.CV]Target-Aware Object Discovery and Association for Unsupervised Video Multi-Object Segmentation
    • [cs.CV]Temporal Consistency Two-Stream CNN for Human Motion Prediction
    • [cs.CV]Towards Automated and Marker-less Parkinson Disease Assessment: Predicting UPDRS Scores using Sit-stand videos
    • [cs.CV]Towards Efficient Graph Convolutional Networks for Point Cloud Handling
    • [cs.CV]Towards a Collective Agenda on AI for Earth Science Data Analysis
    • [cs.CV]Two layer Ensemble of Deep Learning Models for Medical Image Segmentation
    • [cs.CV]UNIT-DDPM: UNpaired Image Translation with Denoising Diffusion Probabilistic Models
    • [cs.CV]USACv20: robust essential, fundamental and homography matrix estimation
    • [cs.CV]Unidentified Video Objects: A Benchmark for Dense, Open-World Segmentation
    • [cs.CV]Unveiling personnel movement in a larger indoor area with a non-overlapping multi-camera system
    • [cs.CV]View-Guided Point Cloud Completion
    • [cs.CV]Visiting the Invisible: Layer-by-Layer Completed Scene Decomposition
    • [cs.CV]Volume and leaf area calculation of cabbage with a neural network-based instance segmentation
    • [cs.CV]Zero-Shot Learning on 3D Point Cloud Objects and Beyond
    • [cs.CY]A Conceptual Framework for Establishing Trust in Real World Intelligent Systems
    • [cs.CY]An Extended Epidemic Model on Interconnected Networks for COVID-19 to Explore the Epidemic Dynamics
    • [cs.CY]Automated Meta-Analysis: A Causal Learning Perspective
    • [cs.CY]Consideration of resilience for digital farming systems
    • [cs.CY]TermAdventure: Interactively Teaching UNIX Command Line, Text Adventure Style
    • [cs.CY]Towards Algorithmic Transparency: A Diversity Perspective
    • [cs.DB]Auto-Validate: Unsupervised Data Validation Using Data-Domain Patterns Inferred from Data Lakes
    • [cs.DB]Discovering Categorical Main and Interaction Effects Based on Association Rule Mining
    • [cs.DC]A Hybrid Parallelization Approach for Distributed and Scalable Deep Learning
    • [cs.DC]Achieving 100X faster simulations of complex biological phenomena by coupling ML to HPC ensembles
    • [cs.DC]Avocado Buying Trends in the United States Using SAC
    • [cs.DC]Fed-DDM: A Federated Ledgers based Framework for Hierarchical Decentralized Data Marketplaces
    • [cs.DC]High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models
    • [cs.DC]LIBRA: An Economical Hybrid Approach for Cloud Applications with Strict SLAs
    • [cs.DC]LearningCity: Knowledge Generation for Smart Cities
    • [cs.DC]ODT FLOW: A Scalable Platform for Extracting, Analyzing, and Sharing Multi-source Multi-scale Human Mobility
    • [cs.DC]Optimizing the Whole-life Cost in End-to-end CNN Acceleration
    • [cs.DC]Secure and Privacy-Preserving Stored Surveillance Video Sharing atop Permissioned Blockchain
    • [cs.DC]The Programming of Deep Learning Accelerators as a Constraint Satisfaction Problem
    • [cs.DC]Voting-based probabilistic consensuses and their applications in distributed ledgers
    • [cs.DL]A Graph Convolutional Neural Network based Framework for Estimating Future Citations Count of Research Articles
    • [cs.DL]Breaking Community Boundary: Comparing Academic and Social Communication Preferences regarding Global Pandemics
    • [cs.DS]Beyond Pointwise Submodularity: Non-Monotone Adaptive Submodular Maximization subject to a Knapsack Constraint
    • [cs.GR]Fabrication-aware Design for Furniture with Planar Pieces
    • [cs.GT]A Non-Negative Matrix Factorization Game
    • [cs.GT]Automated Mechanism Design for Classification with Partial Verification
    • [cs.HC]Building Mental Models through Preview of Autopilot Behaviors
    • [cs.HC]Student Barriers to Active Learning in Synchronous Online Classes: Characterization, Reflections, and Suggestions
    • [cs.IR]A Probabilistic Framework for Lexicon-based Keyword Spotting in Handwritten Text Images
    • [cs.IR]Dynamic Modeling of User Preferences for Stable Recommendations
    • [cs.IR]Fatigued PageRank
    • [cs.IR]Fatigued Random Walks in Hypergraphs: A Neuronal Analogy to Improve Retrieval Performance
    • [cs.IR]Generating Code with the Help of Retrieved Template Functions and Stack Overflow Answers
    • [cs.IR]Personalized Bundle Recommendation in Online Games
    • [cs.IT]Capacity-Driven Low-Interference Fast Beam Synthesis for Next Generation Base Stations
    • [cs.IT]Distributed coordinated precoding for MIMO cellular network virtualization
    • [cs.IT]Energy-Efficient Coverage Enhancement of Indoor THz-MISO Systems: An FD-NOMA Approach
    • [cs.IT]Hovering UAV-Based FSO Communications: Channel Modelling, Performance Analysis, and Parameter Optimization
    • [cs.IT]Hybrid Reconfigurable Intelligent Metasurfaces: Enabling Simultaneous Tunable Reflections and Sensing for 6G Wireless Communications
    • [cs.IT]Information Rate Optimization for Joint Relay and Link in Non-Regenerative MIMO Channels
    • [cs.IT]Iterative Access Point Selection, MMSE Precoding and Power Allocation for Cell-Free Networks
    • [cs.IT]Learning the CSI Denoising and Feedback Without Supervision
    • [cs.IT]MIMO-OFDM-Based Massive Connectivity With Frequency Selectivity Compensation
    • [cs.IT]NOMA for Next-generation Massive IoT: Performance Potential and Technology Directions
    • [cs.IT]ON-OFF Privacy Against Correlation Over Time
    • [cs.IT]On Two-Stage Guessing
    • [cs.IT]Polar-Precoding: A Unitary Finite-Feedback Transmit Precoder for Polar-Coded MIMO Systems
    • [cs.IT]Simple Majority Consensus in Networks with Unreliable Communication
    • [cs.IT]Stochastic Binning and Coded Demixing for Unsourced Random Access
    • [cs.IT]The Undecidability of Conditional Affine Information Inequalities and Conditional Independence Implication with a Binary Constraint
    • [cs.LG]A Swarm Variant for the Schrödinger Solver
    • [cs.LG]ALT-MAS: A Data-Efficient Framework for Active Testing of Machine Learning Algorithms
    • [cs.LG]Accelerating Neural Network Training with Distributed Asynchronous and Selective Optimization (DASO)
    • [cs.LG]Achieving Model Robustness through Discrete Adversarial Training
    • [cs.LG]Adversarial Training as Stackelberg Game: An Unrolled Optimization Approach
    • [cs.LG]Adversarially-Trained Nonnegative Matrix Factorization
    • [cs.LG]Affinity-Based Hierarchical Learning of Dependent Concepts for Human Activity Recognition
    • [cs.LG]An Approach to Symbolic Regression Using Feyn
    • [cs.LG]An Efficient 2D Method for Training Super-Large Deep Learning Models
    • [cs.LG]An Efficient Algorithm for Deep Stochastic Contextual Bandits
    • [cs.LG]Approximate Bayesian Computation of Bézier Simplices
    • [cs.LG]Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment
    • [cs.LG]Auto-weighted Multi-view Feature Selection with Graph Optimization
    • [cs.LG]AutoGL: A Library for Automated Graph Learning
    • [cs.LG]Boosted Embeddings for Time Series Forecasting
    • [cs.LG]CoPE: Conditional image generation using Polynomial Expansions
    • [cs.LG]Compressive Neural Representations of Volumetric Scalar Fields
    • [cs.LG]Consequence-aware Sequential Counterfactual Generation
    • [cs.LG]Data-Free Knowledge Distillation with Soft Targeted Transfer Set Synthesis
    • [cs.LG]Deep Learning for IoT
    • [cs.LG]Deep Transformer Networks for Time Series Classification: The NPP Safety Case
    • [cs.LG]DeepSITH: Efficient Learning via Decomposition of What and When Across Time Scales
    • [cs.LG]Description of Structural Biases and Associated Data in Sensor-Rich Environments
    • [cs.LG]Distributed Learning Systems with First-order Methods
    • [cs.LG]Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph
    • [cs.LG]Generalization bounds via distillation
    • [cs.LG]Group Equivariant Neural Architecture Search via Group Decomposition and Reinforcement Learning
    • [cs.LG]Highly Efficient Knowledge Graph Embedding Learning with Orthogonal Procrustes Analysis
    • [cs.LG]How Sensitive are Meta-Learners to Dataset Imbalance?
    • [cs.LG]Individual Explanations in Machine Learning Models: A Case Study on Poverty Estimation
    • [cs.LG]Individual Explanations in Machine Learning Models: A Survey for Practitioners
    • [cs.LG]Landmark Regularization: Ranking Guided Super-Net Training in Neural Architecture Search
    • [cs.LG]Learn Goal-Conditioned Policy with Intrinsic Motivation for Deep Reinforcement Learning
    • [cs.LG]Learning from Censored and Dependent Data: The case of Linear Dynamics
    • [cs.LG]Learning representations with end-to-end models for improved remaining useful life prognostics
    • [cs.LG]Meta-Learning Bidirectional Update Rules
    • [cs.LG]Meta-Regularization: An Approach to Adaptive Choice of the Learning Rate in Gradient Descent
    • [cs.LG]Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx
    • [cs.LG]Noether: The More Things Change, the More Stay the Same
    • [cs.LG]On Analyzing Churn Prediction in Mobile Games
    • [cs.LG]On Universal Black-Box Domain Adaptation
    • [cs.LG]One-class Autoencoder Approach for Optimal Electrode Set-up Identification in Wearable EEG Event Monitoring
    • [cs.LG]PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging
    • [cs.LG]Pure Exploration with Structured Preference Feedback
    • [cs.LG]Pyramidal Reservoir Graph Neural Network
    • [cs.LG]Rank-R FNN: A Tensor-Based Learning Model for High-Order Data Classification
    • [cs.LG]Reducing Representation Drift in Online Continual Learning
    • [cs.LG]Representation Learning for Networks in Biology and Medicine: Advancements, Challenges, and Opportunities
    • [cs.LG]SGD Implicitly Regularizes Generalization Error
    • [cs.LG]Saddlepoints in Unsupervised Least Squares
    • [cs.LG]Scalable Power Control/Beamforming in Heterogeneous Wireless Networks with Graph Neural Networks
    • [cs.LG]Smart Vectorizations for Single and Multiparameter Persistence
    • [cs.LG]Sparse Coding Frontend for Robust Neural Networks
    • [cs.LG]TedNet: A Pytorch Toolkit for Tensor Decomposition Networks
    • [cs.LG]The Atari Data Scraper
    • [cs.LG]The Many Faces of 1-Lipschitz Neural Networks
    • [cs.LG]The World as a Graph: Improving El Niño Forecasts with Graph Neural Networks
    • [cs.LG]Traffic Forecasting using Vehicle-to-Vehicle Communication
    • [cs.LG]Uncover Residential Energy Consumption Patterns Using Socioeconomic and Smart Meter Data
    • [cs.LG]Understanding Overparameterization in Generative Adversarial Networks
    • [cs.LG]Understanding Prediction Discrepancies in Machine Learning Classifiers
    • [cs.LG]Unsupervised Lane-Change Identification for On-Ramp Merge Analysis in Naturalistic Driving Data
    • [cs.LG]Use of Metamorphic Relations as Knowledge Carriers to Train Deep Neural Networks
    • [cs.LG]Weak Form Generalized Hamiltonian Learning
    • [cs.LG]What Makes an Effective Scalarising Function for Multi-Objective Bayesian Optimisation?
    • [cs.LO]Actors — A Process Algebra Based Approach
    • [cs.LO]Online Machine Learning Techniques for Coq: A Comparison
    • [cs.MA]A Hierarchical State-Machine-Based Framework for Platoon Manoeuvre Descriptions
    • [cs.NE]A coevolutionairy approach to deep multi-agent reinforcement learning
    • [cs.NE]Adaptive conversion of real-valued input into spike trains
    • [cs.NE]An error-propagation spiking neural network compatible with neuromorphic processors
    • [cs.NE]Epigenetic evolution of deep convolutional models
    • [cs.NE]Self-Adjusting Population Sizes for Non-Elitist Evolutionary Algorithms: Why Success Rates Matter
    • [cs.NI]Smart and Secure CAV Networks Empowered by AI-Enabled Blockchain: Next Frontier for Intelligent Safe-Driving Assessment
    • [cs.PF]PPT-Multicore: Performance Prediction of OpenMP applications using Reuse Profiles and Analytical Modeling
    • [cs.PL]A Deep Learning Based Cost Model for Automatic Code Optimization
    • [cs.RO]A multi-sensor robotic platform for ground mapping and estimation beyond the visible spectrum
    • [cs.RO]Ambient awareness for agricultural robotic vehicles
    • [cs.RO]CalQNet — Detection of Calibration Quality for Life-Long Stereo Camera Setups
    • [cs.RO]Context-Aware Task Handling in Resource-Constrained Robots with Virtualization
    • [cs.RO]Deep Weakly Supervised Positioning
    • [cs.RO]Door Delivery of Packages using Drones
    • [cs.RO]Efficient Path Planning in Narrow Passages via Closed-Form Minkowski Operations
    • [cs.RO]Fast and Efficient Locomotion via Learned Gait Transitions
    • [cs.RO]Guided Incremental Local Densification for Accelerated Sampling-based Motion Planning
    • [cs.RO]MPPI-VS: Sampling-Based Model Predictive Control Strategy for Constrained Image-Based and Position-Based Visual Servoing
    • [cs.RO]MPTP: Motion-Planning-aware Task Planning for Navigation in Belief Space
    • [cs.RO]Point wise or Feature wise? Benchmark Comparison of Public Available LiDAR Odometry Algorithms in Urban Canyons
    • [cs.RO]Radar SLAM: A Robust SLAM System for All Weather Conditions
    • [cs.RO]Risk-Averse Biased Human Policies in Assistive Multi-Armed Bandit Settings
    • [cs.RO]Three Cooperative Robotic Fabrication Methods for the Scaffold-Free Construction of a Masonry Arch
    • [cs.RO]Virtual Barriers in Augmented Reality for Safe and Effective Human-Robot Cooperation in Manufacturing
    • [cs.SD]End-to-End Mandarin Tone Classification with Short Term Context Information
    • [cs.SD]Unified Source-Filter GAN: Unified Source-filter Network Based On Factorization of Quasi-Periodic Parallel WaveGAN
    • [cs.SE]Assessing and Supplying the Health of Videos Games via Formal Semantics
    • [cs.SE]ManyTypes4Py: A Benchmark Python Dataset for Machine Learning-based Type Inference
    • [cs.SE]On migration to Perpetual Enterprise System
    • [cs.SI]Can Author Collaboration Reveal Impact? The Case of h-index
    • [cs.SI]Cross-Partisan Discussions on YouTube: Conservatives Talk to Liberals but Liberals Don’t Talk to Conservatives
    • [cs.SI]Edgeless-GNN: Unsupervised Inductive Edgeless Network Embedding
    • [cs.SI]Evaluation and Control of Opinion Polarization and Disagreement: A Review
    • [cs.SI]Towards Collaborative Mobile Crowdsourcing
    • [econ.EM]Identification of Dynamic Panel Logit Models with Fixed Effects
    • [eess.AS]Accented Speech Recognition Inspired by Human Perception
    • [eess.AS]L3DAS21 Challenge: Machine Learning for 3D Audio Signal Processing
    • [eess.AS]NeMo Toolbox for Speech Dataset Construction
    • [eess.IV]Detecting COVID-19 and Community Acquired Pneumonia using Chest CT scan images with Deep Learning
    • [eess.IV]Dual-Octave Convolution for Accelerated Parallel MR Image Reconstruction
    • [eess.IV]Edge-Aware Image Compression using Deep Learning-based Super-resolution Network
    • [eess.IV]Efficient Model Monitoring for Quality Control in Cardiac Image Segmentation
    • [eess.IV]Q-matrix Unaware Double JPEG Detection using DCT-Domain Deep BiLSTM Network
    • [eess.IV]Unsupervised foreign object detection based on dual-energy absorptiometry in the food industry
    • [eess.SP]An Optimal Low-Complexity Energy-Efficient ADC Bit Allocation for Massive MIMO
    • [eess.SY]ENOS: Energy-Aware Network Operator Search for Hybrid Digital and Compute-in-Memory DNN Accelerators
    • [math-ph]Quantum protocols at presence of non-abelian superselection rules in the framework of algebraic model
    • [math.PR]Asymptotic distributions for weighted power sums of extreme values
    • [math.PR]Semi-今日学术视野(2021.4.14) - 图3-normal: a Hybrid between Normal and 今日学术视野(2021.4.14) - 图4-normal
    • [math.PR]Statistical inference of finite-rank tensors
    • [math.ST]A symmetric matrix-variate normal local approximation for the Wishart distribution and some applications
    • [math.ST]Analytic and Bootstrap-after-Cross-Validation Methods for Selecting Penalty Parameters of High-Dimensional M-Estimators
    • [math.ST]Spiked eigenvalues of noncentral Fisher matrix with applications
    • [physics.comp-ph]High Performance Implementation of Boris Particle Pusher on DPC++. A First Look at oneAPI
    • [physics.geo-ph]Applications of physics-informed scientific machine learning in subsurface science: A survey
    • [physics.geo-ph]DuRIN: A Deep-unfolded Sparse Seismic Reflectivity Inversion Network
    • [physics.soc-ph]On the Accuracy of Deterministic Models for Viral Spread on Networks
    • [q-bio.NC]Modelling Brain Connectivity Networks by Graph Embedding for Dyslexia Diagnosis
    • [q-bio.QM]Deep Learning Identifies Neuroimaging Signatures of Alzheimer’s Disease Using Structural and Synthesized Functional MRI Data
    • [q-fin.ST]A Fast Evidential Approach for Stock Forecasting
    • [quant-ph]Classical-quantum network coding: a story about tensor
    • [quant-ph]QZNs: Quantum Z-numbers
    • [quant-ph]Quantum Machine Learning for Power System Stability Assessment
    • [stat.AP]Computer Algebra Systems in R with caracas
    • [stat.AP]Increased risk of hospitalisation for COVID-19 patients infected with SARS-CoV-2 variant B.1.1.7
    • [stat.AP]Inferring Risks of Coronavirus Transmission from Community Household Data
    • [stat.ME]A dose-effect network meta-analysis model: an application in antidepressants
    • [stat.ME]A smoothed and probabilistic PARAFAC model with covariates
    • [stat.ME]Bayesian exponential random graph models for populations of networks
    • [stat.ME]Conditional Inference: Towards a Hierarchy of Statistical Evidence
    • [stat.ME]Couplings for Multinomial Hamiltonian Monte Carlo
    • [stat.ME]CovNet: Covariance Networks for Functional Data on Multidimensional Domains
    • [stat.ME]Exact-corrected confidence interval for risk difference in noninferiority binomial trials
    • [stat.ME]Inference from Non-Random Samples Using Bayesian Machine Learning
    • [stat.ME]Model-assisted analyses of cluster-randomized experiments
    • [stat.ME]Modeling Time-Varying Random Objects and Dynamic Networks
    • [stat.ME]Nonparametric Method for Clustered Data in Pre-Post Factorial Design
    • [stat.ME]On the Evaluation of Surrogate Markers in Real World Data Settings
    • [stat.ME]Parallel integrative learning for large-scale multi-response regression with incomplete outcomes
    • [stat.ME]Probabilistic HIV Recency Classification — A Logistic Regression without Labeled Individual Level Training Data
    • [stat.ML]Deep Time Series Forecasting with Shape and Temporal Criteria
    • [stat.ML]GPflux: A Library for Deep Gaussian Processes
    • [stat.ML]Random Intersection Chains
    • [stat.ML]Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning
    • [stat.ML]Unsuitability of NOTEARS for Causal Graph Discovery

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

    • [cond-mat.mtrl-sci]Current Overview of Statistical Fiber Bundles Model and Its Application to Physics-based Reliability Analysis of Thin-film Dielectrics
    James U. Gleaton, David Han, James D. Lynch, Hon Keung Tony Ng, Fabrizio Rugger
    http://arxiv.org/abs/2104.05449v1

    • [cs.AI]Accelerating science with human versus alien artificial intelligences
    Jamshid Sourati, James Evans
    http://arxiv.org/abs/2104.05188v1

    • [cs.AI]Artificial Intelligence Methods Based Hierarchical Classification of Frontotemporal Dementia to Improve Diagnostic Predictability
    Km Poonam, Rajlakshmi Guha, Partha P Chakrabarti
    http://arxiv.org/abs/2104.05235v1

    • [cs.AI]Boltzmann Tuning of Generative Models
    Victor Berger, Michele Sebag
    http://arxiv.org/abs/2104.05252v1

    • [cs.AI]Deep Attributed Network Representation Learning via Attribute Enhanced Neighborhood
    Cong Li, Min Shi, Bo Qu, Xiang Li
    http://arxiv.org/abs/2104.05234v1

    • [cs.AI]Interpretable Methods for Identifying Product Variants
    Rebecca West, Khalifeh Al Jadda, Unaiza Ahsan, Huiming Qu, Xiquan Cui
    http://arxiv.org/abs/2104.05504v1

    • [cs.AI]Learning dynamic and hierarchical traffic spatiotemporal features with Transformer
    Haoyang Yan, Xiaolei Ma
    http://arxiv.org/abs/2104.05163v1

    • [cs.AI]Machine learning and deep learning
    Christian Janiesch Patrick Zschech Kai Heinrich
    http://arxiv.org/abs/2104.05314v1

    • [cs.AI]MeToo Tweets Sentiment Analysis Using Multi Modal frameworks
    Rushil Thareja
    http://arxiv.org/abs/2104.05331v1

    • [cs.AI]Multiple Run Ensemble Learning withLow-Dimensional Knowledge Graph Embeddings
    Chengjin Xu, Mojtaba Nayyeri, Sahar Vahdati, Jens Lehmann
    http://arxiv.org/abs/2104.05003v1

    • [cs.AI]On Unifying Misinformation Detection
    Nayeon Lee, Belinda Z. Li, Sinong Wang, Pascale Fung, Hao Ma, Wen-tau Yih, Madian Khabsa
    http://arxiv.org/abs/2104.05243v1

    • [cs.AI]Print Error Detection using Convolutional Neural Networks
    Suyash Shandilya
    http://arxiv.org/abs/2104.05046v1

    • [cs.AI]Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning
    Xuelu Chen, Michael Boratko, Muhao Chen, Shib Sankar Dasgupta, Xiang Lorraine Li, Andrew McCallum
    http://arxiv.org/abs/2104.04597v1

    • [cs.AI]Regression Networks For Calculating Englacial Layer Thickness
    Debvrat Varshney, Maryam Rahnemoonfar, Masoud Yari, John Paden
    http://arxiv.org/abs/2104.04654v1

    • [cs.AI]Selection-Expansion: A Unifying Framework for Motion-Planning and Diversity Search Algorithms
    Alexandre Chenu, Nicolas Perrin-Gilbert, Stéphane Doncieux, Olivier Sigaud
    http://arxiv.org/abs/2104.04768v1

    • [cs.AR]iELAS: An ELAS-Based Energy-Efficient Accelerator for Real-Time Stereo Matching on FPGA Platform
    Tian Gao, Zishen Wan, Yuyang Zhang, Bo Yu, Yanjun Zhang, Shaoshan Liu, Arijit Raychowdhury
    http://arxiv.org/abs/2104.05112v1

    • [cs.CL]Assessing Reference-Free Peer Evaluation for Machine Translation
    Sweta Agrawal, George Foster, Markus Freitag, Colin Cherry
    http://arxiv.org/abs/2104.05146v1

    • [cs.CL]Backtranslation Feedback Improves User Confidence in MT, Not Quality
    Vilém Zouhar, Michal Novák, Matúš Žilinec, Ondřej Bojar, Mateo Obregón, Robin L. Hill, Frédéric Blain, Marina Fomicheva, Lucia Specia, Lisa Yankovskaya
    http://arxiv.org/abs/2104.05688v1

    • [cs.CL]Better Feature Integration for Named Entity Recognition
    Lu Xu, Zhanming Jie, Wei Lu, Lidong Bing
    http://arxiv.org/abs/2104.05316v1

    • [cs.CL]Building a Swedish Open-Domain Conversational Language Model
    Tobias Norlund, Agnes Stenbom
    http://arxiv.org/abs/2104.05277v1

    • [cs.CL]Combining exogenous and endogenous signals with a semi-supervised co-attention network for early detection of COVID-19 fake tweets
    Rachit Bansal, William Scott Paka, Nidhi, Shubhashis Sengupta, Tanmoy Chakraborty
    http://arxiv.org/abs/2104.05321v1

    • [cs.CL]Comparing the Benefit of Synthetic Training Data for Various Automatic Speech Recognition Architectures
    Nick Rossenbach, Mohammad Zeineldeen, Benedikt Hilmes, Ralf Schlüter, Hermann Ney
    http://arxiv.org/abs/2104.05379v1

    • [cs.CL]Constructing Contrastive samples via Summarization for Text Classification with limited annotations
    Yangkai Du, Tengfei Ma, Lingfei Wu, Fangli Xu, Xuhong Zhang, Shouling Ji
    http://arxiv.org/abs/2104.05094v1

    • [cs.CL]Contextualized Knowledge-aware Attentive Neural Network: Enhancing Answer Selection with Knowledge
    Yang Deng, Yuexiang Xie, Yaliang Li, Min Yang, Wai Lam, Ying Shen
    http://arxiv.org/abs/2104.05216v1

    • [cs.CL]Continual Learning for Text Classification with Information Disentanglement Based Regularization
    Yufan Huang, Yanzhe Zhang, Jiaao Chen, Xuezhi Wang, Diyi Yang
    http://arxiv.org/abs/2104.05489v1

    • [cs.CL]Conversational Semantic Role Labeling
    Kun Xu, Han Wu, Linfeng Song, Haisong Zhang, Linqi Song, Dong Yu
    http://arxiv.org/abs/2104.04947v1

    • [cs.CL]Cross-Lingual Word Embedding Refinement by 今日学术视野(2021.4.14) - 图5 Norm Optimisation
    Xutan Peng, Chenghua Lin, Mark Stevenson
    http://arxiv.org/abs/2104.04916v1

    • [cs.CL]DATE: Detecting Anomalies in Text via Self-Supervision of Transformers
    Andrei Manolache, Florin Brad, Elena Burceanu
    http://arxiv.org/abs/2104.05591v1

    • [cs.CL]Deep Learning for Prominence Detection in Children’s Read Speech
    Kamini Sabu, Mithilesh Vaidya, Preeti Rao
    http://arxiv.org/abs/2104.05488v1

    • [cs.CL]Developing Annotated Resources for Internal Displacement Monitoring
    Fabio Poletto, Yunbai Zhang, Andre Panisson, Yelena Mejova, Daniela Paolotti, Sylvain Ponserre
    http://arxiv.org/abs/2104.05459v1

    • [cs.CL]Disentangled Contrastive Learning for Learning Robust Textual Representations
    Xiang Chen, Xin Xie, Zhen Bi, Hongbin Ye, Shumin Deng, Ningyu Zhang, Huajun Chen
    http://arxiv.org/abs/2104.04907v1

    • [cs.CL]Disentangling Semantics and Syntax in Sentence Embeddings with Pre-trained Language Models
    James Y. Huang, Kuan-Hao Huang, Kai-Wei Chang
    http://arxiv.org/abs/2104.05115v1

    • [cs.CL]Does syntax matter? A strong baseline for Aspect-based Sentiment Analysis with RoBERTa
    Junqi Dai, Hang Yan, Tianxiang Sun, Pengfei Liu, Xipeng Qiu
    http://arxiv.org/abs/2104.04986v1

    • [cs.CL]Double Perturbation: On the Robustness of Robustness and Counterfactual Bias Evaluation
    Chong Zhang, Jieyu Zhao, Huan Zhang, Kai-Wei Chang, Cho-Jui Hsieh
    http://arxiv.org/abs/2104.05232v1

    • [cs.CL]Edge: Enriching Knowledge Graph Embeddings with External Text
    Saed Rezayi, Handong Zhao, Sungchul Kim, Ryan A. Rossi, Nedim Lipka, Sheng Li
    http://arxiv.org/abs/2104.04909v1

    • [cs.CL]Estimating Subjective Crowd-Evaluations as an Additional Objective to Improve Natural Language Generation
    Jakob Nyberg, Ramesh Manuvinakurike, Maike Paetzel-Prüsmann
    http://arxiv.org/abs/2104.05224v1

    • [cs.CL]Estimation of Summary-to-Text Inconsistency by Mismatched Embeddings
    Oleg Vasilyev, John Bohannon
    http://arxiv.org/abs/2104.05156v1

    • [cs.CL]FRAKE: Fusional Real-time Automatic Keyword Extraction
    Aidin Zehtab-Salmasi, Mohammad-Reza Feizi-Derakhshi, Mohamad-Ali Balafar
    http://arxiv.org/abs/2104.04830v1

    • [cs.CL]FUDGE: Controlled Text Generation With Future Discriminators
    Kevin Yang, Dan Klein
    http://arxiv.org/abs/2104.05218v1

    • [cs.CL]Factual Probing Is [MASK]: Learning vs. Learning to Recall**
    Zexuan Zhong, Dan Friedman, Danqi Chen
    http://arxiv.org/abs/2104.05240v1

    • [cs.CL]Fine-Tuning Transformers for Identifying Self-Reporting Potential Cases and Symptoms of COVID-19 in Tweets
    Max Fleming, Priyanka Dondeti, Caitlin N. Dreisbach, Adam Poliak
    http://arxiv.org/abs/2104.05501v1

    • [cs.CL]Fine-tuning Encoders for Improved Monolingual and Zero-shot Polylingual Neural Topic Modeling
    Aaron Mueller, Mark Dredze
    http://arxiv.org/abs/2104.05064v1

    • [cs.CL]Fool Me Twice: Entailment from Wikipedia Gamification
    Julian Martin Eisenschlos, Bhuwan Dhingra, Jannis Bulian, Benjamin Börschinger, Jordan Boyd-Graber
    http://arxiv.org/abs/2104.04725v1

    • [cs.CL]FreSaDa: A French Satire Data Set for Cross-Domain Satire Detection
    Radu Tudor Ionescu, Adrian Gabriel Chifu
    http://arxiv.org/abs/2104.04828v1

    • [cs.CL]HTCInfoMax: A Global Model for Hierarchical Text Classification via Information Maximization
    Zhongfen Deng, Hao Peng, Dongxiao He, Jianxin Li, Philip S. Yu
    http://arxiv.org/abs/2104.05220v1

    • [cs.CL]Identifying and Categorizing Offensive Language in Social Media
    Nikhil Oswal
    http://arxiv.org/abs/2104.04871v1

    • [cs.CL]Imperfect also Deserves Reward: Multi-Level and Sequential Reward Modeling for Better Dialog Management
    Zhengxu Hou, Bang Liu, Ruihui Zhao, Zijing Ou, Yafei Liu, Xi Chen, Yefeng Zheng
    http://arxiv.org/abs/2104.04748v1

    • [cs.CL]Innovative Bert-based Reranking Language Models for Speech Recognition
    Shih-Hsuan Chiu, Berlin Chen
    http://arxiv.org/abs/2104.04950v1

    • [cs.CL]Investigating Methods to Improve Language Model Integration for Attention-based Encoder-Decoder ASR Models
    Mohammad Zeineldeen, Aleksandr Glushko, Wilfried Michel, Albert Zeyer, Ralf Schlüter, Hermann Ney
    http://arxiv.org/abs/2104.05544v1

    • [cs.CL]Joint Universal Syntactic and Semantic Parsing
    Elias Stengel-Eskin, Kenton Murray, Kenton Murray, Aaron Steven White, Benjamin Van Durme
    http://arxiv.org/abs/2104.05696v1

    • [cs.CL]Learning to Remove: Towards Isotropic Pre-trained BERT Embedding
    Yuxin Liang, Rui Cao, Jie Zheng, Jie Ren, Ling Gao
    http://arxiv.org/abs/2104.05274v1

    • [cs.CL]MIPT-NSU-UTMN at SemEval-2021 Task 5: Ensembling Learning with Pre-trained Language Models for Toxic Spans Detection
    Mikhail Kotyushev, Anna Glazkova, Dmitry Morozov
    http://arxiv.org/abs/2104.04739v1

    • [cs.CL]Machine Translation Decoding beyond Beam Search
    Rémi Leblond, Jean-Baptiste Alayrac, Laurent Sifre, Miruna Pislar, Jean-Baptiste Lespiau, Ioannis Antonoglou, Karen Simonyan, Oriol Vinyals
    http://arxiv.org/abs/2104.05336v1

    • [cs.CL]Macro-Average: Rare Types Are Important Too
    Thamme Gowda, Weiqiu You, Constantine Lignos, Jonathan May
    http://arxiv.org/abs/2104.05700v1

    • [cs.CL]Meta-learning for fast cross-lingual adaptation in dependency parsing
    Anna Langedijk, Verna Dankers, Sander Bos, Bryan Cardenas Guevara, Helen Yannakoudakis, Ekaterina Shutova
    http://arxiv.org/abs/2104.04736v1

    • [cs.CL]Meta-tuning Language Models to Answer Prompts Better
    Ruiqi Zhong, Kristy Lee, Zheng Zhang, Dan Klein
    http://arxiv.org/abs/2104.04670v1

    • [cs.CL]Multilingual Language Models Predict Human Reading Behavior
    Nora Hollenstein, Federico Pirovano, Ce Zhang, Lena Jäger, Lisa Beinborn
    http://arxiv.org/abs/2104.05433v1

    • [cs.CL]NLI Data Sanity Check: Assessing the Effect of Data Corruption on Model Performance
    Aarne Talman, Marianna Apidianaki, Stergios Chatzikyriakidis, Jörg Tiedemann
    http://arxiv.org/abs/2104.04751v1

    • [cs.CL]NeMo Inverse Text Normalization: From Development To Production
    Yang Zhang, Evelina Bakhturina, Kyle Gorman, Boris Ginsburg
    http://arxiv.org/abs/2104.05055v1

    • [cs.CL]Non-Autoregressive Semantic Parsing for Compositional Task-Oriented Dialog
    Arun Babu, Akshat Shrivastava, Armen Aghajanyan, Ahmed Aly, Angela Fan, Marjan Ghazvininejad
    http://arxiv.org/abs/2104.04923v1

    • [cs.CL]Non-autoregressive Transformer-based End-to-end ASR using BERT
    Fu-Hao Yu, Kuan-Yu Chen
    http://arxiv.org/abs/2104.04805v1

    • [cs.CL]NorDial: A Preliminary Corpus of Written Norwegian Dialect Use
    Jeremy Barnes, Petter Mæhlum, Samia Touileb
    http://arxiv.org/abs/2104.04989v1

    • [cs.CL]Not All Attention Is All You Need
    Hongqiu Wu, Hai Zhao, Min Zhang
    http://arxiv.org/abs/2104.04692v1

    • [cs.CL]On the Inductive Bias of Masked Language Modeling: From Statistical to Syntactic Dependencies
    Tianyi Zhang, Tatsunori Hashimoto
    http://arxiv.org/abs/2104.05694v1

    • [cs.CL]Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages
    Gowtham Ramesh, Sumanth Doddapaneni, Aravinth Bheemaraj, Mayank Jobanputra, Raghavan AK, Ajitesh Sharma, Sujit Sahoo, Harshita Diddee, Mahalakshmi J, Divyanshu Kakwani, Navneet Kumar, Aswin Pradeep, Kumar Deepak, Vivek Raghavan, Anoop Kunchukuttan, Pratyush Kumar, Mitesh Shantadevi Khapra
    http://arxiv.org/abs/2104.05596v1

    • [cs.CL]Self-Training with Weak Supervision
    Giannis Karamanolakis, Subhabrata Mukherjee, Guoqing Zheng, Ahmed Hassan Awadallah
    http://arxiv.org/abs/2104.05514v1

    • [cs.CL]Semantic Frame Forecast
    Chieh-Yang Huang, Ting-Hao ‘Kenneth’ Huang
    http://arxiv.org/abs/2104.05604v1

    • [cs.CL]Sentiment-based Candidate Selection for NMT
    Alex Jones, Derry Tanti Wijaya
    http://arxiv.org/abs/2104.04840v1

    • [cs.CL]ShadowGNN: Graph Projection Neural Network for Text-to-SQL Parser
    Zhi Chen, Lu Chen, Yanbin Zhao, Ruisheng Cao, Zihan Xu, Su Zhu, Kai Yu
    http://arxiv.org/abs/2104.04689v1

    • [cs.CL]Stay Together: A System for Single and Split-antecedent Anaphora Resolution
    Juntao Yu, Nafise Sadat Moosavi, Silviu Paun, Massimo Poesio
    http://arxiv.org/abs/2104.05320v1

    • [cs.CL]StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer
    Yiwei Lyu, Paul Pu Liang, Hai Pham, Eduard Hovy, Barnabás Póczos, Ruslan Salakhutdinov, Louis-Philippe Morency
    http://arxiv.org/abs/2104.05196v1

    • [cs.CL]SuperSim: a test set for word similarity and relatedness in Swedish
    Simon Hengchen, Nina Tahmasebi
    http://arxiv.org/abs/2104.05228v1

    • [cs.CL]Survey on reinforcement learning for language processing
    Victor Uc-Cetina, Nicolas Navarro-Guerrero, Anabel Martin-Gonzalez, Cornelius Weber, Stefan Wermter
    http://arxiv.org/abs/2104.05565v1

    • [cs.CL]Text2Chart: A Multi-Staged Chart Generator from Natural Language Text
    Md. Mahinur Rashid, Hasin Kawsar Jahan, Annysha Huzzat, Riyasaat Ahmed Rahul, Tamim Bin Zakir, Farhana Meem, Md. Saddam Hossain Mukta, Swakkhar Shatabda
    http://arxiv.org/abs/2104.04584v1

    • [cs.CL]The Great Misalignment Problem in Human Evaluation of NLP Methods
    Mika Hämäläinen, Khalid Alnajjar
    http://arxiv.org/abs/2104.05361v1

    • [cs.CL]The structure of online social networks modulates the rate of lexical change
    Jian Zhu, David Jurgens
    http://arxiv.org/abs/2104.05010v1

    • [cs.CL]TransWiC at SemEval-2021 Task 2: Transformer-based Multilingual and Cross-lingual Word-in-Context Disambiguation
    Hansi Hettiarachchi, Tharindu Ranasinghe
    http://arxiv.org/abs/2104.04632v1

    • [cs.CL]UTNLP at SemEval-2021 Task 5: A Comparative Analysis of Toxic Span Detection using Attention-based, Named Entity Recognition, and Ensemble Models
    Alireza Salemi, Nazanin Sabri, Emad Kebriaei, Behnam Bahrak, Azadeh Shakery
    http://arxiv.org/abs/2104.04770v1

    • [cs.CL]UniDrop: A Simple yet Effective Technique to Improve Transformer without Extra Cost
    Zhen Wu, Lijun Wu, Qi Meng, Yingce Xia, Shufang Xie, Tao Qin, Xinyu Dai, Tie-Yan Liu
    http://arxiv.org/abs/2104.04946v1

    • [cs.CL]Unsupervised Learning of Explainable Parse Trees for Improved Generalisation
    Atul Sahay, Ayush Maheshwari, Ritesh Kumar, Ganesh Ramakrishnan, Manjesh Kumar Hanawal, Kavi Arya
    http://arxiv.org/abs/2104.04998v1

    • [cs.CL]Updater-Extractor Architecture for Inductive World State Representations
    Arseny Moskvichev, James A. Liu
    http://arxiv.org/abs/2104.05500v1

    • [cs.CL]WEC: Deriving a Large-scale Cross-document Event Coreference dataset from Wikipedia
    Alon Eirew, Arie Cattan, Ido Dagan
    http://arxiv.org/abs/2104.05022v1

    • [cs.CL]WHOSe Heritage: Classification of UNESCO World Heritage “Outstanding Universal Value” Documents with Smoothed Labels
    Nan Bai, Renqian Luo, Pirouz Nourian, Ana Pereira Roders
    http://arxiv.org/abs/2104.05547v1

    • [cs.CL]WLV-RIT at SemEval-2021 Task 5: A Neural Transformer Framework for Detecting Toxic Spans
    Tharindu Ranasinghe, Diptanu Sarkar, Marcos Zampieri, Alex Ororbia
    http://arxiv.org/abs/2104.04630v1

    • [cs.CL]ZS-BERT: Towards Zero-Shot Relation Extraction with Attribute Representation Learning
    Chih-Yao Chen, Cheng-Te Li
    http://arxiv.org/abs/2104.04697v1

    • [cs.CR]Supervised Feature Selection Techniques in Network Intrusion Detection: a Critical Review
    Mario Di Mauro, Giovanni Galatro, Giancarlo Fortino, Antonio Liotta
    http://arxiv.org/abs/2104.04958v1

    • [cs.CR]Using a Neural Network to Detect Anomalies given an N-gram Profile
    Byunggu Yu, Junwhan Kim
    http://arxiv.org/abs/2104.05571v1

    • [cs.CV]A Bop and Beyond: A Second Order Optimizer for Binarized Neural Networks
    Cuauhtemoc Daniel Suarez-Ramirez, Miguel Gonzalez-Mendoza, Leonardo Chang-Fernandez, Gilberto Ochoa-Ruiz, Mario Alberto Duran-Vega
    http://arxiv.org/abs/2104.05124v1

    • [cs.CV]A Learnable Self-supervised Task for Unsupervised Domain Adaptation on Point Clouds
    Xiaoyuan Luo, Shaolei Liu, Kexue Fu, Manning Wang, Zhijian Song
    http://arxiv.org/abs/2104.05164v1

    • [cs.CV]A Novel Unified Model for Multi-exposure Stereo Coding Based on Low Rank Tucker-ALS and 3D-HEVC
    Mansi Sharma, Aditya Wadaskar
    http://arxiv.org/abs/2104.04726v1

    • [cs.CV]A-FMI: Learning Attributions from Deep Networks via Feature Map Importance
    An Zhang, Xiang Wang, Chengfang Fang, Jie Shi, Tat-seng Chua, Zehua Chen
    http://arxiv.org/abs/2104.05527v1

    • [cs.CV]Action-Conditioned 3D Human Motion Synthesis with Transformer VAE
    Mathis Petrovich, Michael J. Black, Gül Varol
    http://arxiv.org/abs/2104.05670v1

    • [cs.CV]Adversarial Open Domain Adaption for Sketch-to-Photo Synthesis
    Xiaoyu Xiang, Ding Liu, Xiao Yang, Yiheng Zhu, Xiaohui Shen, Jan P. Allebach
    http://arxiv.org/abs/2104.05703v1

    • [cs.CV]All Labels Are Not Created Equal: Enhancing Semi-supervision via Label Grouping and Co-training
    Islam Nassar, Samitha Herath, Ehsan Abbasnejad, Wray Buntine, Gholamreza Haffari
    http://arxiv.org/abs/2104.05248v1

    • [cs.CV]An MRF-UNet Product of Experts for Image Segmentation
    Mikael Brudfors, Yaël Balbastre, John Ashburner, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso
    http://arxiv.org/abs/2104.05495v1

    • [cs.CV]Approach for modeling single branches of meadow orchard trees with 3D point clouds
    Jonas Straub, David Reiser, Hans W. Griepentrog
    http://arxiv.org/abs/2104.05282v1

    • [cs.CV]Behavioral Research and Practical Models of Drivers’ Attention
    Iuliia Kotseruba, John K. Tsotsos
    http://arxiv.org/abs/2104.05677v1

    • [cs.CV]Blazer: Laser Scanning Simulation using Physically Based Rendering
    Sebastian Grans, Lars Tingelstad
    http://arxiv.org/abs/2104.05430v1

    • [cs.CV]CAPRI-Net: Learning Compact CAD Shapes with Adaptive Primitive Assembly
    Fenggen Yu, Zhiqin Chen, Manyi Li, Aditya Sanghi, Hooman Shayani, Ali Mahdavi-Amiri, Hao Zhang
    http://arxiv.org/abs/2104.05652v1

    • [cs.CV]Class-Balanced Distillation for Long-Tailed Visual Recognition
    Ahmet Iscen, André Araujo, Boqing Gong, Cordelia Schmid
    http://arxiv.org/abs/2104.05279v1

    • [cs.CV]Cloth In
    7180
    teractive Transformer for Virtual Try-On
    Bin Ren, Hao Tang, Fanyang Meng, Runwei Ding, Ling Shao, Philip H. S. Torr, Nicu Sebe
    http://arxiv.org/abs/2104.05519v1

    • [cs.CV]Coastline extraction from ALOS-2 satellite SAR images
    Petr Hurtik, Marek Vajgl
    http://arxiv.org/abs/2104.04722v1

    • [cs.CV]Cross-Modal Contrastive Learning for Abnormality Classification and Localization in Chest X-rays with Radiomics using a Feedback Loop
    Yan Han, Chongyan Chen, Ahmed Tewfik, Benjamin Glicksberg, Ying Ding, Yifan Peng, Zhangyang Wang
    http://arxiv.org/abs/2104.04968v1

    • [cs.CV]Deep Recursive Embedding for High-Dimensional Data
    Zixia Zhou, Yuanyuan Wang, Boudewijn P. F. Lelieveldt, Qian Tao
    http://arxiv.org/abs/2104.05171v1

    • [cs.CV]Deep learning using Havrda-Charvat entropy for classification of pulmonary endomicroscopy
    Thibaud Brochet, Jerome Lapuyade-Lahorgue, Sebastien Bougleux, Mathieu Salaun, Su Ruan
    http://arxiv.org/abs/2104.05450v1

    • [cs.CV]Deformable Capsules for Object Detection
    Rodney Lalonde, Naji Khosravan, Ulas Bagci
    http://arxiv.org/abs/2104.05031v1

    • [cs.CV]Diamond in the rough: Improving image realism by traversing the GAN latent space
    Jeffrey Wen, Fabian Benitez-Quiroz, Qianli Feng, Aleix Martinez
    http://arxiv.org/abs/2104.05518v1

    • [cs.CV]Do as we do: Multiple Person Video-To-Video Transfer
    Mickael Cormier, Houraalsadat Mortazavi Moshkenan, Franz Lörch, Jürgen Metzler, Jürgen Beyerer
    http://arxiv.org/abs/2104.04721v1

    • [cs.CV]Drafting and Revision: Laplacian Pyramid Network for Fast High-Quality Artistic Style Transfer
    Tianwei Lin, Zhuoqi Ma, Fu Li, Dongliang He, Xin Li, Errui Ding, Nannan Wang, Jie Li, Xinbo Gao
    http://arxiv.org/abs/2104.05376v1

    • [cs.CV]Dual Discriminator Adversarial Distillation for Data-free Model Compression
    Haoran Zhao, Xin Sun, Junyu Dong, Hui Yu, Huiyu Zhou
    http://arxiv.org/abs/2104.05382v1

    • [cs.CV]Egocentric Pose Estimation from Human Vision Span
    Hao Jiang, Vamsi Krishna Ithapu
    http://arxiv.org/abs/2104.05167v1

    • [cs.CV]Enhancing Deep Neural Network Saliency Visualizations with Gradual Extrapolation
    Tomasz Szandala
    http://arxiv.org/abs/2104.04945v1

    • [cs.CV]Ensemble Learning based on Classifier Prediction Confidence and Comprehensive Learning Particle Swarm Optimisation for polyp localisation
    Truong Dang, Thanh Nguyen, John McCall, Alan Wee-Chung Liew
    http://arxiv.org/abs/2104.04832v1

    • [cs.CV]Error Propagation in Satellite Multi-image Geometry
    Joseph L Mundy, Hank Theiss
    http://arxiv.org/abs/2104.04843v1

    • [cs.CV]Escaping the Big Data Paradigm with Compact Transformers
    Ali Hassani, Steven Walton, Nikhil Shah, Abulikemu Abuduweili, Jiachen Li, Humphrey Shi
    http://arxiv.org/abs/2104.05704v1

    • [cs.CV]Estimation of BMI from Facial Images using Semantic Segmentation based Region-Aware Pooling
    Nadeem Yousaf, Sarfaraz Hussein, Waqas Sultani
    http://arxiv.org/abs/2104.04733v1

    • [cs.CV]Event-based Timestamp Image Encoding Network for Human Action Recognition and Anticipation
    Chaoxing Huang
    http://arxiv.org/abs/2104.05145v1

    • [cs.CV]Feature Decomposition and Reconstruction Learning for Effective Facial Expression Recognition
    Delian Ruan, YanYan, Shenqi Lai, Zhenhua Chai, Chunhua Shen, Hanzi Wang
    http://arxiv.org/abs/2104.05160v1

    • [cs.CV]Fine-Grained Attention for Weakly Supervised Object Localization
    Junghyo Sohn, Eunjin Jeon, Wonsik Jung, Eunsong Kang, Heung-Il Suk
    http://arxiv.org/abs/2104.04952v1

    • [cs.CV]Fruit Quality and Defect Image Classification with Conditional GAN Data Augmentation
    Jordan J. Bird, Chloe M. Barnes, Luis J. Manso, Anikó Ekárt, Diego R. Faria
    http://arxiv.org/abs/2104.05647v1

    • [cs.CV]GAttANet: Global attention agreement for convolutional neural networks
    Rufin VanRullen, Andrea Alamia
    http://arxiv.org/abs/2104.05575v1

    • [cs.CV]GR-RNN: Global-Context Residual Recurrent Neural Networks for Writer Identification
    Sheng He, Lambert Schomaker
    http://arxiv.org/abs/2104.05036v1

    • [cs.CV]GarmentNets: Category-Level Pose Estimation for Garments via Canonical Space Shape Completion
    Cheng Chi, Shuran Song
    http://arxiv.org/abs/2104.05177v1

    • [cs.CV]Glance and Gaze: Inferring Action-aware Points for One-Stage Human-Object Interaction Detection
    Xubin Zhong, Xian Qu, Changxing Ding, Dacheng Tao
    http://arxiv.org/abs/2104.05269v1

    • [cs.CV]Holistic Image Manipulation Detection using Pixel Co-occurrence Matrices
    Lakshmanan Nataraj, Michael Goebel, Tajuddin Manhar Mohammed, Shivkumar Chandrasekaran, B. S. Manjunath
    http://arxiv.org/abs/2104.05693v1

    • [cs.CV]Hyperspectral Pigment Analysis of Cultural Heritage Artifacts Using the Opaque Form of Kubelka-Munk Theory
    Abu Md Niamul Taufique, David W. Messinger
    http://arxiv.org/abs/2104.04884v1

    • [cs.CV]Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection
    Nadine Chang, Zhiding Yu, Yu-Xiong Wang, Anima Anandkumar, Sanja Fidler, Jose M. Alvarez
    http://arxiv.org/abs/2104.05702v1

    • [cs.CV]Improving Online Performance Prediction
    83e
    for Semantic Segmentation
    Marvin Klingner, Andreas Bär, Marcel Mross, Tim Fingscheidt
    http://arxiv.org/abs/2104.05255v1

    • [cs.CV]Instagram Filter Removal on Fashionable Images
    Furkan Kınlı, Barış Özcan, Furkan Kıraç
    http://arxiv.org/abs/2104.05072v1

    • [cs.CV]Integrating Information Theory and Adversarial Learning for Cross-modal Retrieval
    Wei Chen, Yu Liu, Erwin M. Bakker, Michael S. Lew
    http://arxiv.org/abs/2104.04991v1

    • [cs.CV]Intra-Class Uncertainty Loss Function for Classification
    He Zhu, Shan Yu
    http://arxiv.org/abs/2104.05298v1

    • [cs.CV]Latent Code-Based Fusion: A Volterra Neural Network Approach
    Sally Ghanem, Siddharth Roheda, Hamid Krim
    http://arxiv.org/abs/2104.04829v1

    • [cs.CV]Learning Chebyshev Basis in Graph Convolutional Networks for Skeleton-based Action Recognition
    Hichem Sahbi
    http://arxiv.org/abs/2104.05482v1

    • [cs.CV]Learning Robust Visual-semantic Mapping for Zero-shot Learning
    Jingcai Guo
    http://arxiv.org/abs/2104.05668v1

    • [cs.CV]Learning from 2D: Pixel-to-Point Knowledge Transfer for 3D Pretraining
    Yueh-Cheng Liu, Yu-Kai Huang, Hung-Yueh Chiang, Hung-Ting Su, Zhe-Yu Liu, Chin-Tang Chen, Ching-Yu Tseng, Winston H. Hsu
    http://arxiv.org/abs/2104.04687v1

    • [cs.CV]Learning from Subjective Ratings Using Auto-Decoded Deep Latent Embeddings
    Bowen Li, Xinping Ren, Ke Yan, Le Lu, Guotong Xie, Jing Xiao, Dar-In Tai, Adam P. Harrison
    http://arxiv.org/abs/2104.05570v1

    • [cs.CV]Lip reading using external viseme decoding
    Javad Peymanfard, Mohammad Reza Mohammadi, Hossein Zeinali, Nasser Mozayani
    http://arxiv.org/abs/2104.04784v1

    • [cs.CV]LocalViT: Bringing Locality to Vision Transformers
    Yawei Li, Kai Zhang, Jiezhang Cao, Radu Timofte, Luc Van Gool
    http://arxiv.org/abs/2104.05707v1

    • [cs.CV]Location-Sensitive Visual Recognition with Cross-IOU Loss
    Kaiwen Duan, Lingxi Xie, Honggang Qi, Song Bai, Qingming Huang, Qi Tian
    http://arxiv.org/abs/2104.04899v1

    • [cs.CV]Look Closer to Segment Better: Boundary Patch Refinement for Instance Segmentation
    Chufeng Tang, Hang Chen, Xiao Li, Jianmin Li, Zhaoxiang Zhang, Xiaolin Hu
    http://arxiv.org/abs/2104.05239v1

    • [cs.CV]Memory-guided Unsupervised Image-to-image Translation
    Somi Jeong, Youngjung Kim, Eungbean Lee, Kwanghoon Sohn
    http://arxiv.org/abs/2104.05170v1

    • [cs.CV]MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition
    Jacek Komorowski, Monika Wysoczanska, Tomasz Trzcinski
    http://arxiv.org/abs/2104.05327v1

    • [cs.CV]MobileStyleGAN: A Lightweight Convolutional Neural Network for High-Fidelity Image Synthesis
    Sergei Belousov
    http://arxiv.org/abs/2104.04767v1

    • [cs.CV]Neural Camera Simulators
    Hao Ouyang, Zifan Shi, Chenyang Lei, Ka Lung Law, Qifeng Chen
    http://arxiv.org/abs/2104.05237v1

    • [cs.CV]Object Priors for Classifying and Localizing Unseen Actions
    Pascal Mettes, William Thong, Cees G. M. Snoek
    http://arxiv.org/abs/2104.04715v1

    • [cs.CV]Object-Centric Representation Learning for Video Question Answering
    Long Hoang Dang, Thao Minh Le, Vuong Le, Truyen Tran
    http://arxiv.org/abs/2104.05166v1

    • [cs.CV]Occlusion Guided Self-supervised Scene Flow Estimation on 3D Point Clouds
    Bojun Ouyang, Dan Raviv
    http://arxiv.org/abs/2104.04724v1

    • [cs.CV]One Ring to Rule Them All: a simple solution to multi-view 3D-Reconstruction of shapes with unknown BRDF via a small Recurrent ResNet
    Ziang Cheng, Hongdong Li, Richard Hartley, Yinqiang Zheng, Imari Sato
    http://arxiv.org/abs/2104.05014v1

    • [cs.CV]PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering Network
    Pengfei Wang, Chengquan Zhang, Fei Qi, Shanshan Liu, Xiaoqiang Zhang, Pengyuan Lyu, Junyu Han, Jingtuo Liu, Errui Ding, Guangming Shi
    http://arxiv.org/abs/2104.05458v1

    • [cs.CV]Physically-Consistent Generative Adversarial Networks for Coastal Flood Visualization
    Björn Lütjens, Brandon Leshchinskiy, Christian Requena-Mesa, Farrukh Chishtie, Natalia Díaz-Rodríguez, Océane Boulais, Aruna Sankaranarayanan, Aaron Piña, Yarin Gal, Chedy Raïssi, Alexander Lavin, Dava Newman
    http://arxiv.org/abs/2104.04785v1

    • [cs.CV]Predicting Pedestrian Crossing Intention with Feature Fusion and Spatio-Temporal Attention
    Dongfang Yang, Haolin Zhang, Ekim Yurtsever, Keith Redmill, Ümit Özgüner
    http://arxiv.org/abs/2104.05485v1

    • [cs.CV]Preprocessing Methods of Lane Detection and Tracking for Autonomous Driving
    Akram Heidarizadeh
    http://arxiv.org/abs/2104.04755v1

    • [cs.CV]RPSRNet: End-to-End Trainable Rigid Point Set Registration Network using Barnes-Hut 今日学术视野(2021.4.14) - 图6-Tree Representation
    Sk Aziz Ali, Kerem Kahraman, Gerd Reis, Didier Stricker
    http://arxiv.org/abs/2104.05328v1

    • [cs.CV]Raindrops on Windshield: Dataset and Lightweight Gradient-Based Detection Algorithm
    Vera Soboleva, Oleg Shipitko
    http://arxiv.org/abs/2104.05078v1

    • [cs.CV]RayNet: Real-time Scene Arbitrary-shape Text Detection with Multiple Rays
    Chuang Yang, Mulin Chen, Qi Wang, Xuelong Li
    http://arxiv.org/abs/2104.04903v1

    • [cs.CV]Research on Optimization Method of Multi-scale Fish Target Fast Detection Network
    Yang Liu, Shengmao Zhang, Fei Wang, Wei Fan, Guohua Zou, Jing Bo
    http://arxiv.org/abs/2104.05050v1

    • [cs.CV]Robust Classification from Noisy Labels: Integrating Additional Knowledge for Chest Radiography Abnormality Assessment
    Sebastian Gündel, Arnaud A. A. Setio, Florin C. Ghesu, Sasa Grbic, Bogdan Georgescu, Andreas Maier, Dorin Comaniciu
    http://arxiv.org/abs/2104.05261v1

    • [cs.CV]Robust Egocentric Photo-realistic Facial Expression Transfer for Virtual Reality
    Amin Jourabloo, Fernando De la Torre, Jason Saragih, Shih-En Wei, Te-Li Wang, Stephen Lombardi, Danielle Belko, Autumn Trimble, Hernan Badino
    http://arxiv.org/abs/2104.04794v1

    • [cs.CV]SCPM-Net: An Anchor-free 3D Lung Nodule Detection Network using Sphere Representation and Center Points Matching
    Xiangde Luo, Tao Song, Guotai Wang, Jieneng Chen, Yinan Chen, Kang Li, Dimitris N. Metaxas, Shaoting Zhang
    http://arxiv.org/abs/2104.05215v1

    • [cs.CV]SIGAN: A Novel Image Generation Method for Solar Cell Defect Segmentation and Augmentation
    Binyi Su, Zhong Zhou, Haiyong Chen, Xiaochun Cao
    http://arxiv.org/abs/2104.04953v1

    • [cs.CV]SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Clouds with 1000x Fewer Labels
    Qingyong Hu, Bo Yang, Guangchi Fang, Yulan Guo, Ales Leonardis, Niki Trigoni, Andrew Markham
    http://arxiv.org/abs/2104.04891v1

    • [cs.CV]Self-supervised Multi-view Stereo via Effective Co-Segmentation and Data-Augmentation
    Hongbin Xu, Zhipeng Zhou, Yu Qiao, Wenxiong Kang, Qiuxia Wu
    http://arxiv.org/abs/2104.05374v1

    • [cs.CV]Shuffler: A Large Scale Data Management Tool for ML in Computer Vision
    Evgeny Toropov, Paola A. Buitrago, Jose M. F. Moura
    http://arxiv.org/abs/2104.05125v1

    • [cs.CV]StereoPIFu: Depth Aware Clothed Human Digitization via Stereo Vision
    Yang Hong, Juyong Zhang, Boyi Jiang, Yudong Guo, Ligang Liu, Hujun Bao
    http://arxiv.org/abs/2104.05289v1

    • [cs.CV]Target-Aware Object Discovery and Association for Unsupervised Video Multi-Object Segmentation
    Tianfei Zhou, Jianwu Li, Xueyi Li, Ling Shao
    http://arxiv.org/abs/2104.04782v1

    • [cs.CV]Temporal Consistency Two-Stream CNN for Human Motion Prediction
    Jin Tang, Jin Zhang, Jianqin Yin
    http://arxiv.org/abs/2104.05015v1

    • [cs.CV]Towards Automated and Marker-less Parkinson Disease Assessment: Predicting UPDRS Scores using Sit-stand videos
    Deval Mehta, Umar Asif, Tian Hao, Erhan Bilal, Stefan Von Cavallar, Stefan Harrer, Jeffrey Rogers
    http://arxiv.org/abs/2104.04650v1

    • [cs.CV]Towards Efficient Graph Convolutional Networks for Point Cloud Handling
    Yawei Li, He Chen, Zhaopeng Cui, Radu Timofte, Marc Pollefeys, Gregory Chirikjian, Luc Van Gool
    http://arxiv.org/abs/2104.05706v1

    • [cs.CV]Towards a Collective Agenda on AI for Earth Science Data Analysis
    Devis Tuia, Ribana Roscher, Jan Dirk Wegner, Nathan Jacobs, Xiao Xiang Zhu, Gustau Camps-Valls
    http://arxiv.org/abs/2104.05107v1

    • [cs.CV]Two layer Ensemble of Deep Learning Models for Medical Image Segmentation
    Truong Dang, Tien Thanh Nguyen, John McCall, Eyad Elyan, Carlos Francisco Moreno-García
    http://arxiv.org/abs/2104.04809v1

    • [cs.CV]UNIT-DDPM: UNpaired Image Translation with Denoising Diffusion Probabilistic Models
    Hiroshi Sasaki, Chris G. Willcocks, Toby P. Breckon
    http://arxiv.org/abs/2104.05358v1

    • [cs.CV]USACv20: robust essential, fundamental and homography matrix estimation
    Maksym Ivashechkin, Daniel Barath, Jiri Matas
    http://arxiv.org/abs/2104.05044v1

    • [cs.CV]Unidentified Video Objects: A Benchmark for Dense, Open-World Segmentation
    Weiyao Wang, Matt Feiszli, Heng Wang, Du Tran
    http://arxiv.org/abs/2104.04691v1

    • [cs.CV]Unveiling personnel movement in a larger indoor area with a non-overlapping multi-camera system
    Ping Zhang, Zhenxiang Tao, Wenjie Yang, Minze Chen, Shan Ding, Xiaodong Liu, Rui Yang, Hui Zhang
    http://arxiv.org/abs/2104.04662v1

    • [cs.CV]View-Guided Point Cloud Completion
    Xuancheng Zhang, Yutong Feng, Siqi Li, Changqing Zou, Hai Wan, Xibin Zhao, Yandong Guo, Yue Gao
    http://arxiv.org/abs/2104.05666v1

    • [cs.CV]Visiting the Invisible: Layer-by-Layer Completed Scene Decomposition
    Chuanxia Zheng, Duy-Son Dao, Guoxian Song, Tat-Jen Cham, Jianfei Cai
    http://arxiv.org/abs/2104.05367v1

    • [cs.CV]Volume and leaf area calculation of cabbage with a neural network-based instance segmentation
    Nils Lueling, David Reiser, Hans W. Griepentrog
    http://arxiv.org/abs/2104.05284v1

    • [cs.CV]Zero-Shot Learning on 3D Point Cloud Objects and Beyond
    Ali Cheraghian, Shafinn Rahman, Townim F. Chowdhury, Dylan Campbell, Lars Petersson
    http://arxiv.org/abs/2104.04980v1

    • [cs.CY]A Conceptual Framework for Establishing Trust in Real World Intelligent Systems
    Michael Guckert, Nils Gumpfer, Jennifer Hannig, Till Keller, Neil Urquhart
    http://arxiv.org/abs/2104.05432v1

    • [cs.CY]An Extended Epidemic Model on Interconnected Networks for COVID-19 to Explore the Epidemic Dynamics
    Ou Deng, Kiichi Tago, Qun Jin
    http://arxiv.org/abs/2104.04695v1

    • [cs.CY]Automated Meta-Analysis: A Causal Learning Perspective
    Lu Cheng, Dmitriy A. Katz-Rogozhnikov, Kush R. Varshney, Ioana Baldini
    http://arxiv.org/abs/2104.04633v1

    • [cs.CY]Consideration of resilience for digital farming systems
    Sebastian Boekle, Leon Koenn, David Reiser, Dimitris S. Paraforos, Hans W. Griepentrog
    http://arxiv.org/abs/2104.05287v1

    • [cs.CY]TermAdventure: Interactively Teaching UNIX Command Line, Text Adventure Style
    Marek Šuppa, Ondrej Jariabka, Adrián Matejov, Marek Nagy
    http://arxiv.org/abs/2104.05456v1

    • [cs.CY]Towards Algorithmic Transparency: A Diversity Perspective
    Fausto Giunchiglia, Jahna Otterbacher, Styliani Kleanthous, Khuyagbaatar Batsuren, Veronika Bogin, Tsvi Kuflik, Avital Shulner Tal
    http://arxiv.org/abs/2104.05658v1

    • [cs.DB]Auto-Validate: Unsupervised Data Validation Using Data-Domain Patterns Inferred from Data Lakes
    Jie Song, Yeye He
    http://arxiv.org/abs/2104.04659v1

    • [cs.DB]Discovering Categorical Main and Interaction Effects Based on Association Rule Mining
    Qiuqiang Lin, Chuanhou Gao
    http://arxiv.org/abs/2104.04728v1

    • [cs.DC]A Hybrid Parallelization Approach for Distributed and Scalable Deep Learning
    Samson B. Akintoye, Liangxiu Han, Xin Zhang, Haoming Chen, Daoqiang Zhang
    http://arxiv.org/abs/2104.05035v1

    • [cs.DC]Achieving 100X faster simulations of complex biological phenomena by coupling ML to HPC ensembles
    Alexander Brace, Hyungro Lee, Heng Ma, Anda Trifan, Matteo Turilli, Igor Yaskushin, Todd Munson, Ian Foster, Shantenu Jha, Arvind Ramanathan
    http://arxiv.org/abs/2104.04797v1

    • [cs.DC]Avocado Buying Trends in the United States Using SAC
    Velma Jones, Kendra Keyse, Alfredo Melgoza, Karen Perez, Tammy Qamar, Jason Villalpando, Jongwook Woo
    http://arxiv.org/abs/2104.04649v1

    • [cs.DC]Fed-DDM: A Federated Ledgers based Framework for Hierarchical Decentralized Data Marketplaces
    Ronghua Xu, Yu Chen
    http://arxiv.org/abs/2104.05583v1

    • [cs.DC]High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models
    Dheevatsa Mudigere, Yuchen Hao, Jianyu Huang, Andrew Tulloch, Srinivas Sridharan, Xing Liu, Mustafa Ozdal, Jade Nie, Jongsoo Park, Liang Luo, Jie, Yang, Leon Gao, Dmytro Ivchenko, Aarti Basant, Yuxi Hu, Jiyan Yang, Ehsan K. Ardestani, Xiaodong Wang, Rakesh Komuravelli, Ching-Hsiang Chu, Serhat Yilmaz, Huayu Li, Jiyuan Qian, Zhuobo Feng, Yinbin Ma, Junjie Yang, Ellie Wen, Hong Li, Lin Yang, Chonglin Sun, Whitney Zhao, Krishna Dhulipala, KR Kishore, Tyler Graf, Assaf Eisenman, Kiran Kumar Matam, Adi Gangidi, Pallab Bhattacharya, Guoqiang Jerry Chen, Manoj Krishnan, Krishnakumar Nair, Petr Lapukhov, Maxim Naumov, Lin Qiao, Mikhail Smelyanskiy, Bill Jia, Vijay Rao
    http://arxiv.org/abs/2104.05158v1

    • [cs.DC]LIBRA: An Economical Hybrid Approach for Cloud Applications with Strict SLAs
    Ali Raza, Zongshun Zhang, Nabeel Akhtar, Vatche Isahagian, Ibrahim Matta
    http://arxiv.org/abs/2104.05491v1

    • [cs.DC]LearningCity: Knowledge Generation for Smart Cities
    Dimitrios Amaxilatis, Georgios Mylonas, Evangelos Theodoridis, Luis Diez, Katerina Deligiannidou
    http://arxiv.org/abs/2104.05286v1

    • [cs.DC]ODT FLOW: A Scalable Platform for Extracting, Analyzing, and Sharing Multi-source Multi-scale Human Mobility
    Zhenlong Li, Xiao Huang, Tao Hu, Huan Ning, Xinyue Ye, Xiaoming Li
    http://arxiv.org/abs/2104.05040v1

    • [cs.DC]Optimizing the Whole-life Cost in End-to-end CNN Acceleration
    Jiaqi Zhang, Xiangru Chen, Sandip Ray, Tao Li
    http://arxiv.org/abs/2104.05541v1

    • [cs.DC]Secure and Privacy-Preserving Stored Surveillance Video Sharing atop Permissioned Blockchain
    Alem Fitwi, Yu Chen
    http://arxiv.org/abs/2104.05617v1

    • [cs.DC]The Programming of Deep Learning Accelerators as a Constraint Satisfaction Problem
    Dennis Rieber, Axel Acosta, Holger Fröning
    http://arxiv.org/abs/2104.04731v1

    • [cs.DC]Voting-based probabilistic consensuses and their applications in distributed ledgers
    Serguei Popov, Sebastian Müller
    http://arxiv.org/abs/2104.05313v1

    • [cs.DL]A Graph Convolutional Neural Network based Framework for Estimating Future Citations Count of Research Articles
    Abdul Wahid, Rajesh Sharma, Chandra Sekhara Rao Annavarapu
    http://arxiv.org/abs/2104.04939v1

    • [cs.DL]Breaking Community Boundary: Comparing Academic and Social Communication Preferences regarding Global Pandemics
    Qingqing Zhou, Chengzhi Zhang
    http://arxiv.org/abs/2104.05409v1

    • [cs.DS]Beyond Pointwise Submodularity: Non-Monotone Adaptive Submodular Maximization subject to a Knapsack Constraint
    Shaojie Tang
    http://arxiv.org/abs/2104.04853v1

    • [cs.GR]Fabrication-aware Design for Furniture with Planar Pieces
    Wenzhong Yan, Dawei Zhao, Ankur Mehta
    http://arxiv.org/abs/2104.05052v1

    • [cs.GT]A Non-Negative Matrix Factorization Game
    Satpreet H. Singh
    http://arxiv.org/abs/2104.05069v1

    • [cs.GT]Automated Mechanism Design for Classification with Partial Verification
    Hanrui Zhang, Yu Cheng, Vincent Conitzer
    http://arxiv.org/abs/2104.05182v1

    • [cs.HC]Building Mental Models through Preview of Autopilot Behaviors
    Yuan Shen, Niviru Wijayaratne, Katherine Driggs-Campbell
    http://arxiv.org/abs/2104.05470v1

    • [cs.HC]Student Barriers to Active Learning in Synchronous Online Classes: Characterization, Reflections, and Suggestions
    Reza Hadi Mogavi, Yankun Zhao, Ehsan Ul Haq, Pan Hui, Xiaojuan Ma
    http://arxiv.org/abs/2104.04862v1

    • [cs.IR]A Probabilistic Framework for Lexicon-based Keyword Spotting in Handwritten Text Images
    E. Vidal, A. H. Toselli, J. Puigcerver
    http://arxiv.org/abs/2104.04556v1

    • [cs.IR]Dynamic Modeling of User Preferences for Stable Recommendations
    Oluwafemi Olaleke, Ivan Oseledets, Evgeny Frolov
    http://arxiv.org/abs/2104.05047v1

    • [cs.IR]Fatigued PageRank
    José Devezas, Sérgio Nunes
    http://arxiv.org/abs/2104.05369v1

    • [cs.IR]Fatigued Random Walks in Hypergraphs: A Neuronal Analogy to Improve Retrieval Performance
    José Devezas, Sérgio Nunes
    http://arxiv.org/abs/2104.05364v1

    • [cs.IR]Generating Code with the Help of Retrieved Template Functions and Stack Overflow Answers
    Changran Hu, Dawn Drain, Chen Wu, Mikhail Breslav, Neel Sundaresan
    http://arxiv.org/abs/2104.05310v1

    • [cs.IR]Personalized Bundle Recommendation in Online Games
    Qilin Deng, Kai Wang, Minghao Zhao, Zhene Zou, Runze Wu, Jianrong Tao, Changjie Fan, Liang Chen
    http://arxiv.org/abs/2104.05307v1

    • [cs.IT]Capacity-Driven Low-Interference Fast Beam Synthesis for Next Generation Base Stations
    G. Oliveri, G. Gottardi, N. Anselmi, A. Massa
    http://arxiv.org/abs/2104.05363v1

    • [cs.IT]Distributed coordinated precoding for MIMO cellular network virtualization
    Juncheng Wang, Min Dong, Ben Liang, Gary Boudreau, Hatem Abou-zeid
    http://arxiv.org/abs/2104.04615v1

    • [cs.IT]Energy-Efficient Coverage Enhancement of Indoor THz-MISO Systems: An FD-NOMA Approach
    Omar Maraqa, Aditya S. Rajasekaran, Hamza U. Sokun, Saad Al-Ahmadi, Halim Yanikomeroglu, Sadiq M. Sait
    http://arxiv.org/abs/2104.05391v1

    • [cs.IT]Hovering UAV-Based FSO Communications: Channel Modelling, Performance Analysis, and Parameter Optimization
    Jin-Yuan Wang, Yang Ma, Rong-Rong Lu, Jun-Bo Wang, Min Lin, Julian Cheng
    http://arxiv.org/abs/2104.05368v1

    • [cs.IT]Hybrid Reconfigurable Intelligent Metasurfaces: Enabling Simultaneous Tunable Reflections and Sensing for 6G Wireless Communications
    George C. Alexandropoulos, Nir Shlezinger, Idban Alamzadeh, Mohammadreza F. Imani, Haiyang Zhang, Yonina C. Eldar
    http://arxiv.org/abs/2104.04690v1

    • [cs.IT]Information Rate Optimization for Joint Relay and Link in Non-Regenerative MIMO Channels
    Giorgio Taricco
    http://arxiv.org/abs/2104.05236v1

    • [cs.IT]Iterative Access Point Selection, MMSE Precoding and Power Allocation for Cell-Free Networks
    V. Palhares, A. R. Flores, R. C. de Lamare
    http://arxiv.org/abs/2104.05165v1

    • [cs.IT]Learning the CSI Denoising and Feedback Without Supervision
    Valentina Rizzello, Wolfgang Utschick
    http://arxiv.org/abs/2104.05002v1

    • [cs.IT]MIMO-OFDM-Based Massive Connectivity With Frequency Selectivity Compensation
    Wenjun Jiang, Mingyang Yue, Xiaojun Yuan, Yong Zuo
    http://arxiv.org/abs/2104.05169v1

    • [cs.IT]NOMA for Next-generation Massive IoT: Performance Potential and Technology Directions
    Yifei Yuan, Sen Wang, Yongpeng Wu, H. Vincent Poor, Zhiguo Ding, Xiaohu You, Lajos Hanzo
    http://arxiv.org/abs/2104.04911v1

    • [cs.IT]ON-OFF Privacy Against Correlation Over Time
    Fangwei Ye, Carolina Naim, Salim El Rouayheb
    http://arxiv.org/abs/2104.05135v1

    • [cs.IT]On Two-Stage Guessing
    Robert Graczyk, Igal Sason
    http://arxiv.org/abs/2104.04586v1

    • [cs.IT]Polar-Precoding: A Unitary Finite-Feedback Transmit Precoder for Polar-Coded MIMO Systems
    Jinnan Piao, Kai Niu, Jincheng Dai, Lajos Hanzo
    http://arxiv.org/abs/2104.05178v1

    • [cs.IT]Simple Majority Consensus in Networks with Unreliable Communication
    Ran Tamir, Ariel Livshits, Yonatan Shadmi
    http://arxiv.org/abs/2104.04996v1

    • [cs.IT]Stochastic Binning and Coded Demixing for Unsourced Random Access
    Jamison R. Ebert, Vamsi K. Amalladinne, Stefano Rini, Jean-Francois Chamberland, Krishna R. Narayanan
    http://arxiv.org/abs/2104.05686v1

    • [cs.IT]The Undecidability of Conditional Affine Information Inequalities and Conditional Independence Implication with a Binary Constraint
    Cheuk Ting Li
    http://arxiv.org/abs/2104.05634v1

    • [cs.LG]A Swarm Variant for the Schrödinger Solver
    Urvil Nileshbhai Jivani, Omatharv Bharat Vaidya, Anwesh Bhattacharya, Snehanshu Saha
    http://arxiv.org/abs/2104.04795v1

    • [cs.LG]ALT-MAS: A Data-Efficient Framework for Active Testing of Machine Learning Algorithms
    Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh
    http://arxiv.org/abs/2104.04999v1

    • [cs.LG]Accelerating Neural Network Training with Distributed Asynchronous and Selective Optimization (DASO)
    Daniel Coquelin, Charlotte Debus, Markus Götz, Fabrice von der Lehr, James Kahn, Martin Siggel, Achim Steit
    http://arxiv.org/abs/2104.05588v1

    • [cs.LG]Achieving Model Robustness through Discrete Adversarial Training
    Maor Ivgi, Jonathan Berant
    http://arxiv.org/abs/2104.05062v1

    • [cs.LG]Adversarial Training as Stackelberg Game: An Unrolled Optimization Approach
    Simiao Zuo, Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Jianfeng Gao, Weizhu Chen, Tuo Zhao
    http://arxiv.org/abs/2104.04886v1

    • [cs.LG]Adversarially-Trained Nonnegative Matrix Factorization
    Ting Cai, Vincent Y. F. Tan, Cédric Févotte
    http://arxiv.org/abs/2104.04757v1

    • [cs.LG]Affinity-Based Hierarchical Learning of Dependent Concepts for Human Activity Recognition
    Aomar Osmani, Massinissa Hamidi, Pegah Alizadeh
    http://arxiv.org/abs/2104.04889v1

    • [cs.LG]An Approach to Symbolic Regression Using Feyn
    Kevin René Broløs, Meera Vieira Machado, Chris Cave, Jaan Kasak, Valdemar Stentoft-Hansen, Victor Galindo Batanero, Tom Jelen, Casper Wilstrup
    http://arxiv.org/abs/2104.05417v1

    • [cs.LG]An Efficient 2D Method for Training Super-Large Deep Learning Models
    Qifan Xu, Shenggui Li, Chaoyu Gong, Yang You
    http://arxiv.org/abs/2104.05343v1

    • [cs.LG]An Efficient Algorithm for Deep Stochastic Contextual Bandits
    Tan Zhu, Guannan Liang, Chunjiang Zhu, Haining Li, Jinbo Bi
    http://arxiv.org/abs/2104.05613v1

    • [cs.LG]Approximate Bayesian Computation of Bézier Simplices
    Akinori Tanaka, Akiyoshi Sannai, Ken Kobayashi, Naoki Hamada
    http://arxiv.org/abs/2104.04679v1

    • [cs.LG]Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment
    Philip J. Ball, Cong Lu, Jack Parker-Holder, Stephen Roberts
    http://arxiv.org/abs/2104.05632v1

    • [cs.LG]Auto-weighted Multi-view Feature Selection with Graph Optimization
    Qi Wang, Xu Jiang, Mulin Chen, Xuelong Li
    http://arxiv.org/abs/2104.04906v1

    • [cs.LG]AutoGL: A Library for Automated Graph Learning
    Chaoyu Guan, Ziwei Zhang, Haoyang Li, Heng Chang, Zeyang Zhang, Yijian Qin, Jiyan Jiang, Xin Wang, Wenwu Zhu
    http://arxiv.org/abs/2104.04987v1

    • [cs.LG]Boosted Embeddings for Time Series Forecasting
    Sankeerth Rao Karingula, Nandini Ramanan, Rasool Tahsambi, Mehrnaz Amjadi, Deokwoo Jung, Ricky Si, Charanraj Thimmisetty, Claudionor Nunes Coelho Jr
    http://arxiv.org/abs/2104.04781v1

    • [cs.LG]CoPE: Conditional image generation using Polynomial Expansions
    Grigorios G Chrysos, Yannis Panagakis
    http://arxiv.org/abs/2104.05077v1

    • [cs.LG]Compressive Neural Representations of Volumetric Scalar Fields
    Yuzhe Lu, Kairong Jiang, Joshua A. Levine, Matthew Berger
    http://arxiv.org/abs/2104.04523v1

    • [cs.LG]Consequence-aware Sequential Counterfactual Generation
    Philip Naumann, Eirini Ntoutsi
    http://arxiv.org/abs/2104.05592v1

    • [cs.LG]Data-Free Knowledge Distillation with Soft Targeted Transfer Set Synthesis
    Zi Wang
    http://arxiv.org/abs/2104.04868v1

    • [cs.LG]Deep Learning for IoT
    Tao Lin
    http://arxiv.org/abs/2104.05569v1

    • [cs.LG]Deep Transformer Networks for Time Series Classification: The NPP Safety Case
    Bing Zha, Alessandro Vanni, Yassin Hassan, Tunc Aldemir, Alper Yilmaz
    http://arxiv.org/abs/2104.05448v1

    • [cs.LG]DeepSITH: Efficient Learning via Decomposition of What and When Across Time Scales
    Brandon Jacques, Zoran Tiganj, Marc W. Howard, Per B. Sederberg
    http://arxiv.org/abs/2104.04646v1

    • [cs.LG]Description of Structural Biases and Associated Data in Sensor-Rich Environments
    Massinissa Hamidi, Aomar Osmani
    http://arxiv.org/abs/2104.04885v1

    • [cs.LG]Distributed Learning Systems with First-order Methods
    Ji Liu, Ce Zhang
    http://arxiv.org/abs/2104.05245v1

    • [cs.LG]Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph
    Chen Cai, Nikolaos Vlassis, Lucas Magee, Ran Ma, Zeyu Xiong, Bahador Bahmani, Teng-Fong Wong, Yusu Wang, WaiChing Sun
    http://arxiv.org/abs/2104.05608v1

    • [cs.LG]Generalization bounds via distillation
    Daniel Hsu, Ziwei Ji, Matus Telgarsky, Lan Wang
    http://arxiv.org/abs/2104.05641v1

    • [cs.LG]Group Equivariant Neural Architecture Search via Group Decomposition and Reinforcement Learning
    Sourya Basu, Akshayaa Magesh, Harshit Yadav, Lav R. Varshney
    http://arxiv.org/abs/2104.04848v1

    • [cs.LG]Highly Efficient Knowledge Graph Embedding Learning with Orthogonal Procrustes Analysis
    Xutan Peng, Guanyi Chen, Chenghua Lin, Mark Stevenson
    http://arxiv.org/abs/2104.04676v1

    • [cs.LG]How Sensitive are Meta-Learners to Dataset Imbalance?
    Mateusz Ochal, Massimiliano Patacchiola, Amos Storkey, Jose Vazquez, Sen Wang
    http://arxiv.org/abs/2104.05344v1

    • [cs.LG]Individual Explanations in Machine Learning Models: A Case Study on Poverty Estimation
    Alfredo Carrillo, Luis F. Cantú, Luis Tejerina, Alejandro Noriega
    http://arxiv.org/abs/2104.04148v2

    • [cs.LG]Individual Explanations in Machine Learning Models: A Survey for Practitioners
    Alfredo Carrillo, Luis F. Cantú, Alejandro Noriega
    http://arxiv.org/abs/2104.04144v2

    • [cs.LG]Landmark Regularization: Ranking Guided Super-Net Training in Neural Architecture Search
    Kaicheng Yu, Rene Ranftl, Mathieu Salzmann
    http://arxiv.org/abs/2104.05309v1

    • [cs.LG]Learn Goal-Conditioned Policy with Intrinsic Motivation for Deep Reinforcement Learning
    Jinxin Liu, Donglin Wang, Qiangxing Tian, Zhengyu Chen
    http://arxiv.org/abs/2104.05043v1

    • [cs.LG]Learning from Censored and Dependent Data: The case of Linear Dynamics
    Orestis Plevrakis
    http://arxiv.org/abs/2104.05087v1

    • [cs.LG]Learning representations with end-to-end models for improved remaining useful life prognostics
    Alaaeddine Chaoub, Alexandre Voisin, Christophe Cerisara, Benoît Iung
    http://arxiv.org/abs/2104.05049v1

    • [cs.LG]Meta-Learning Bidirectional Update Rules
    Mark Sandler, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Andrew Jackson, Tom Madams, Blaise Aguera y Arcas
    http://arxiv.org/abs/2104.04657v1

    • [cs.LG]Meta-Regularization: An Approach to Adaptive Choice of the Learning Rate in Gradient Descent
    Guangzeng Xie, Hao Jin, Dachao Lin, Zhihua Zhang
    http://arxiv.org/abs/2104.05447v1

    • [cs.LG]Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx
    Kin G. Olivares, Cristian Challu, Grzegorz Marcjasz, Rafał Weron, Artur Dubrawski
    http://arxiv.org/abs/2104.05522v1

    • [cs.LG]Noether: The More Things Change, the More Stay the Same
    Grzegorz Głuch, Rüdiger Urbanke
    http://arxiv.org/abs/2104.05508v1

    • [cs.LG]On Analyzing Churn Prediction in Mobile Games
    Kihoon Jang, Junwhan Kim, Byunggu Yu
    http://arxiv.org/abs/2104.05554v1

    • [cs.LG]On Universal Black-Box Domain Adaptation
    Bin Deng, Yabin Zhang, Hui Tang, Changxing Ding, Kui Jia
    http://arxiv.org/abs/2104.04665v1

    • [cs.LG]One-class Autoencoder Approach for Optimal Electrode Set-up Identification in Wearable EEG Event Monitoring
    Laura M. Ferrari, Guy Abi Hanna, Paolo Volpe, Esma Ismailova, François Bremond, Maria A. Zuluaga
    http://arxiv.org/abs/2104.04546v1

    • [cs.LG]PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging
    Anthony Sicilia, Xingchen Zhao, Anastasia Sosnovskikh, Seong Jae Hwang
    http://arxiv.org/abs/2104.05600v1

    • [cs.LG]Pure Exploration with Structured Preference Feedback
    Shubham Gupta, Aadirupa Saha, Sumeet Katariya
    http://arxiv.org/abs/2104.05294v1

    • [cs.LG]Pyramidal Reservoir Graph Neural Network
    Filippo Maria Bianchi, Claudio Gallicchio, Alessio Micheli
    http://arxiv.org/abs/2104.04710v1

    • [cs.LG]Rank-R FNN: A Tensor-Based Learning Model for High-Order Data Classification
    Konstantinos Makantasis, Alexandros Georgogiannis, Athanasios Voulodimos, Ioannis Georgoulas, Anastasios Doulamis, Nikolaos Doulamis
    http://arxiv.org/abs/2104.05048v1

    • [cs.LG]Reducing Representation Drift in Online Continual Learning
    Lucas Caccia, Rahaf Aljundi, Tinne Tuytelaars, Joelle Pineau, Eugene Belilovsky
    http://arxiv.org/abs/2104.05025v1

    • [cs.LG]Representation Learning for Networks in Biology and Medicine: Advancements, Challenges, and Opportunities
    Michelle M. Li, Kexin Huang, Marinka Zitnik
    http://arxiv.org/abs/2104.04883v1

    • [cs.LG]SGD Implicitly Regularizes Generalization Error
    Daniel A. Roberts
    http://arxiv.org/abs/2104.04874v1

    • [cs.LG]Saddlepoints in Unsupervised Least Squares
    Samuel Gerber
    http://arxiv.org/abs/2104.05000v1

    • [cs.LG]Scalable Power Control/Beamforming in Heterogeneous Wireless Networks with Graph Neural Networks
    Xiaochen Zhang, Haitao Zhao, Jun Xiong, Li Zhou, Jibo Wei
    http://arxiv.org/abs/2104.05463v1

    • [cs.LG]Smart Vectorizations for Single and Multiparameter Persistence
    Baris Coskunuzer, CUneyt Gurcan Akcora, Ignacio Segovia Dominguez, Zhiwei Zhen, Murat Kantarcioglu, Yulia R. Gel
    http://arxiv.org/abs/2104.04787v1

    • [cs.LG]Sparse Coding Frontend for Robust Neural Networks
    Can Bakiskan, Metehan Cekic, Ahmet Dundar Sezer, Upamanyu Madhow
    http://arxiv.org/abs/2104.05353v1

    • [cs.LG]TedNet: A Pytorch Toolkit for Tensor Decomposition Networks
    Yu Pan, Maolin Wang, Zenglin Xu
    http://arxiv.org/abs/2104.05018v1

    • [cs.LG]The Atari Data Scraper
    Brittany Davis Pierson, Justine Ventura, Matthew E. Taylor
    http://arxiv.org/abs/2104.04893v1

    • [cs.LG]The Many Faces of 1-Lipschitz Neural Networks
    Louis Béthune, Alberto Gonzáles-Sanz, Franck Mamalet, Mathieu Serrurier
    http://arxiv.org/abs/2104.05097v1

    • [cs.LG]The World as a Graph: Improving El Niño Forecasts with Graph Neural Networks
    Salva Rühling Cachay, Emma Erickson, Arthur Fender C. Bucker, Ernest Pokropek, Willa Potosnak, Suyash Bire, Salomey Osei, Björn Lütjens
    http://arxiv.org/abs/2104.05089v1

    • [cs.LG]Traffic Forecasting using Vehicle-to-Vehicle Communication
    Steven Wong, Lejun Jiang, Robin Walters, Tamás G. Molnár, Gábor Orosz, Rose Yu
    http://arxiv.org/abs/2104.05528v1

    • [cs.LG]Uncover Residential Energy Consumption Patterns Using Socioeconomic and Smart Meter Data
    Wenjun Tang, Hao Wang, Xian-Long Lee, Hong-Tzer Yang
    http://arxiv.org/abs/2104.05154v1

    • [cs.LG]Understanding Overparameterization in Generative Adversarial Networks
    Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi
    http://arxiv.org/abs/2104.05605v1

    • [cs.LG]Understanding Prediction Discrepancies in Machine Learning Classifiers
    Xavier Renard, Thibault Laugel, Marcin Detyniecki
    http://arxiv.org/abs/2104.05467v1

    • [cs.LG]Unsupervised Lane-Change Identification for On-Ramp Merge Analysis in Naturalistic Driving Data
    Lars Klitzke, Kay Gimm, Carsten Koch, Frank Köster
    http://arxiv.org/abs/2104.05661v1

    • [cs.LG]Use of Metamorphic Relations as Knowledge Carriers to Train Deep Neural Networks
    Tsong Yueh Chen, Pak-Lok Poon, Kun Qiu, Zheng Zheng, Jinyi Zhou
    http://arxiv.org/abs/2104.04718v1

    • [cs.LG]Weak Form Generalized Hamiltonian Learning
    Kevin L. Course, Trefor W. Evans, Prasanth B. Nair
    http://arxiv.org/abs/2104.05096v1

    • [cs.LG]What Makes an Effective Scalarising Function for Multi-Objective Bayesian Optimisation?
    Clym Stock-Williams, Tinkle Chugh, Alma Rahat, Wei Yu
    http://arxiv.org/abs/2104.04790v1

    • [cs.LO]Actors — A Process Algebra Based Approach
    Yong Wang
    http://arxiv.org/abs/2104.05438v1

    • [cs.LO]Online Machine Learning Techniques for Coq: A Comparison
    Liao Zhang, Lasse Blaauwbroek, Bartosz Piotrowski, Prokop Černý, Cezary Kaliszyk, Josef Urban
    http://arxiv.org/abs/2104.05207v1

    • [cs.MA]A Hierarchical State-Machine-Based Framework for Platoon Manoeuvre Descriptions
    Corvin Deboeser, Jordan Ivanchev, Thomas Braud, Alois Knoll, David Eckhoff, Alberto Sangiovanni-Vincentelli
    http://arxiv.org/abs/2104.05305v1

    • [cs.NE]A coevolutionairy approach to deep multi-agent reinforcement learning
    Daan Klijn, A. E. Eiben
    http://arxiv.org/abs/2104.05610v1

    • [cs.NE]Adaptive conversion of real-valued input into spike trains
    Alexander Hadjiivanov
    http://arxiv.org/abs/2104.05401v1

    • [cs.NE]An error-propagation spiking neural network compatible with neuromorphic processors
    Matteo Cartiglia, Germain Haessig, Giacomo Indiveri
    http://arxiv.org/abs/2104.05241v1

    • [cs.NE]Epigenetic evolution of deep convolutional models
    Alexander Hadjiivanov, Alan Blair
    http://arxiv.org/abs/2104.05411v1

    • [cs.NE]Self-Adjusting Population Sizes for Non-Elitist Evolutionary Algorithms: Why Success Rates Matter
    Mario Alejandro Hevia Fajardo, Dirk Sudholt
    http://arxiv.org/abs/2104.05624v1

    • [cs.NI]Smart and Secure CAV Networks Empowered by AI-Enabled Blockchain: Next Frontier for Intelligent Safe-Driving Assessment
    Le Xia, Yao Sun, Rafiq Swash, Lina Mohjazi, Lei Zhang, Muhammad Ali Imran
    http://arxiv.org/abs/2104.04572v1

    • [cs.PF]PPT-Multicore: Performance Prediction of OpenMP applications using Reuse Profiles and Analytical Modeling
    Atanu Barai, Yehia Arafa, Abdel-Hameed Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan Eidenbenz
    http://arxiv.org/abs/2104.05102v1

    • [cs.PL]A Deep Learning Based Cost Model for Automatic Code Optimization
    Riyadh Baghdadi, Massinissa Merouani, Mohamed-Hicham Leghettas, Kamel Abdous, Taha Arbaoui, Karima Benatchba, Saman Amarasinghe
    http://arxiv.org/abs/2104.04955v1

    • [cs.RO]A multi-sensor robotic platform for ground mapping and estimation beyond the visible spectrum
    Annalisa Milella, Giulio Reina, Michael Nielsen
    http://arxiv.org/abs/2104.05259v1

    • [cs.RO]Ambient awareness for agricultural robotic vehicles
    Giulio Reina, Annalisa Milella, Raphael Rouveure, Michael Nielsen, Rainer Worst, Morten R. Blas
    http://arxiv.org/abs/2104.05270v1

    • [cs.RO]CalQNet — Detection of Calibration Quality for Life-Long Stereo Camera Setups
    Jiapeng Zhong, Zheyu Ye, Andrei Cramariuc, Florian Tschopp, Jen Jen Chung, Roland Siegwart, Cesar Cadena
    http://arxiv.org/abs/2104.04837v1

    • [cs.RO]Context-Aware Task Handling in Resource-Constrained Robots with Virtualization
    Ramyad Hadidi, Nima Shoghi Ghalehshahi, Bahar Asgari, Hyesoon Kim
    http://arxiv.org/abs/2104.04563v1

    • [cs.RO]Deep Weakly Supervised Positioning
    Ruoyu Wang, Xuchu Xu, Li Ding, Yang Huang, Chen Feng
    http://arxiv.org/abs/2104.04866v1

    • [cs.RO]Door Delivery of Packages using Drones
    Shyam Sundar Kannan, Byung-Cheol Min
    http://arxiv.org/abs/2104.05503v1

    • [cs.RO]Efficient Path Planning in Narrow Passages via Closed-Form Minkowski Operations
    Sipu Ruan, Karen L. Poblete, Hongtao Wu, Qianli Ma, Gregory S. Chirikjian
    http://arxiv.org/abs/2104.04658v1

    • [cs.RO]Fast and Efficient Locomotion via Learned Gait Transitions
    Yuxiang Yang, Tingnan Zhang, Erwin Coumans, Jie Tan, Byron Boots
    http://arxiv.org/abs/2104.04644v1

    • [cs.RO]Guided Incremental Local Densification for Accelerated Sampling-based Motion Planning
    Aditya Mandalika, Rosario Scalise, Brian Hou, Sanjiban Choudhury, Siddhartha S. Srinivasa
    http://arxiv.org/abs/2104.05037v1

    • [cs.RO]MPPI-VS: Sampling-Based Model Predictive Control Strategy for Constrained Image-Based and Position-Based Visual Servoing
    Ihab S. Mohamed
    http://arxiv.org/abs/2104.04925v1

    • [cs.RO]MPTP: Motion-Planning-aware Task Planning for Navigation in Belief Space
    Antony Thomas, Fulvio Mastrogiovanni, Marco Baglietto
    http://arxiv.org/abs/2104.04696v1

    • [cs.RO]Point wise or Feature wise? Benchmark Comparison of Public Available LiDAR Odometry Algorithms in Urban Canyons
    Feng Huang, Weisong Wen, Jiachen Zhang, Li-Ta Hsu
    http://arxiv.org/abs/2104.05203v1

    • [cs.RO]Radar SLAM: A Robust SLAM System for All Weather Conditions
    Ziyang Hong, Yvan Petillot, Andrew Wallace, Sen Wang
    http://arxiv.org/abs/2104.05347v1

    • [cs.RO]Risk-Averse Biased Human Policies in Assistive Multi-Armed Bandit Settings
    Michael Koller, Timothy Patten, Markus Vincze
    http://arxiv.org/abs/2104.05334v1

    • [cs.RO]Three Cooperative Robotic Fabrication Methods for the Scaffold-Free Construction of a Masonry Arch
    Edvard P. G. Bruun, Rafael Pastrana, Vittorio Paris, Alessandro Beghini, Attilio Pizzigoni, Stefana Parascho, Sigrid Adriaenssens
    http://arxiv.org/abs/2104.04856v1

    • [cs.RO]Virtual Barriers in Augmented Reality for Safe and Effective Human-Robot Cooperation in Manufacturing
    Khoa Cong Hoang, Wesley P. Chan, Steven Lay, Akansel Cosgun, Elizabeth Croft
    http://arxiv.org/abs/2104.05211v1

    • [cs.SD]End-to-End Mandarin Tone Classification with Short Term Context Information
    Jiyang Tang, Ming Li
    http://arxiv.org/abs/2104.05657v1

    • [cs.SD]Unified Source-Filter GAN: Unified Source-filter Network Based On Factorization of Quasi-Periodic Parallel WaveGAN
    Reo Yoneyama, Yi-Chiao Wu, Tomoki Toda
    http://arxiv.org/abs/2104.04668v1

    • [cs.SE]Assessing and Supplying the Health of Videos Games via Formal Semantics
    Mohammad Reza Besharati, Mohammad Izadi
    http://arxiv.org/abs/2104.04867v1

    • [cs.SE]ManyTypes4Py: A Benchmark Python Dataset for Machine Learning-based Type Inference
    Amir M. Mir, Evaldas Latoskinas, Georgios Gousios
    http://arxiv.org/abs/2104.04706v1

    • [cs.SE]On migration to Perpetual Enterprise System
    Manuel Tomas Carrasco Benitez
    http://arxiv.org/abs/2104.04844v1

    • [cs.SI]Can Author Collaboration Reveal Impact? The Case of h-index
    Giannis Nikolentzos, George Panagopoulos, Iakovos Evdaimon, Michalis Vazirgiannis
    http://arxiv.org/abs/2104.05562v1

    • [cs.SI]Cross-Partisan Discussions on YouTube: Conservatives Talk to Liberals but Liberals Don’t Talk to Conservatives
    Siqi Wu, Paul Resnick
    http://arxiv.org/abs/2104.05365v1

    • [cs.SI]Edgeless-GNN: Unsupervised Inductive Edgeless Network Embedding
    Yong-Min Shin, Cong Tran, Won-Yong Shin, Xin Cao
    http://arxiv.org/abs/2104.05225v1

    • [cs.SI]Evaluation and Control of Opinion Polarization and Disagreement: A Review
    Yuejiang Li, Hong Vicky Zhao
    http://arxiv.org/abs/2104.05007v1

    • [cs.SI]Towards Collaborative Mobile Crowdsourcing
    Aymen Hamrouni, Hakim Ghazzai, Turki Alelyani, Yehia Massoud
    http://arxiv.org/abs/2104.05626v1

    • [econ.EM]Identification of Dynamic Panel Logit Models with Fixed Effects
    Christopher Dobronyi, Jiaying Gu, Kyoo il Kim
    http://arxiv.org/abs/2104.04590v1

    • [eess.AS]Accented Speech Recognition Inspired by Human Perception
    Xiangyun Chu, Elizabeth Combs, Amber Wang, Michael Picheny
    http://arxiv.org/abs/2104.04627v1

    • [eess.AS]L3DAS21 Challenge: Machine Learning for 3D Audio Signal Processing
    Eric Guizzo, Riccardo F. Gramaccioni, Saeid Jamili, Christian Marinoni, Edoardo Massaro, Claudia Medaglia, Giuseppe Nachira, Leonardo Nucciarelli, Ludovica Paglialunga, Marco Pennese, Sveva Pepe, Enrico Rocchi, Aurelio Uncini, Danilo Comminiello
    http://arxiv.org/abs/2104.05499v1

    • [eess.AS]NeMo Toolbox for Speech Dataset Construction
    Evelina Bakhturina, Vitaly Lavrukhin, Boris Ginsburg
    http://arxiv.org/abs/2104.04896v1

    • [eess.IV]Detecting COVID-19 and Community Acquired Pneumonia using Chest CT scan images with Deep Learning
    Shubham Chaudhary, Sadbhawna, Vinit Jakhetiya, Badri N Subudhi, Ujjwal Baid, Sharath Chandra Guntuku
    http://arxiv.org/abs/2104.05121v1

    • [eess.IV]Dual-Octave Convolution for Accelerated Parallel MR Image Reconstruction
    Chun-Mei Feng, Zhanyuan Yang, Geng Chen, Yong Xu, Ling Shao
    http://arxiv.org/abs/2104.05345v1

    • [eess.IV]Edge-Aware Image Compression using Deep Learning-based Super-resolution Network
    Dipti Mishra, Satish Kumar Singh, Rajat Kumar Singh, Krishna Preetham
    http://arxiv.org/abs/2104.04926v1

    • [eess.IV]Efficient Model Monitoring for Quality Control in Cardiac Image Segmentation
    Francesco Galati, Maria A. Zuluaga
    http://arxiv.org/abs/2104.05533v1

    • [eess.IV]Q-matrix Unaware Double JPEG Detection using DCT-Domain Deep BiLSTM Network
    Vinay Verma, Deepak Singh, Nitin Khanna
    http://arxiv.org/abs/2104.04765v1

    • [eess.IV]Unsupervised foreign object detection based on dual-energy absorptiometry in the food industry
    Vladyslav Andriiashen, Robert van Liere, Tristan van Leeuwen, Kees Joost Batenburg
    http://arxiv.org/abs/2104.05326v1

    • [eess.SP]An Optimal Low-Complexity Energy-Efficient ADC Bit Allocation for Massive MIMO
    I. Zakir Ahmed, Hamid Sadjadpour, Shahram Yousefi
    http://arxiv.org/abs/2104.05186v1

    • [eess.SY]ENOS: Energy-Aware Network Operator Search for Hybrid Digital and Compute-in-Memory DNN Accelerators
    Shamma Nasrin, Ahish Shylendra, Yuti Kadakia, Nick Iliev, Wilfred Gomes, Theja Tulabandhula, Amit Ranjan Trivedi
    http://arxiv.org/abs/2104.05217v1

    • [math-ph]Quantum protocols at presence of non-abelian superselection rules in the framework of algebraic model
    A. S. Sitdikov, A. S. Nikitin
    http://arxiv.org/abs/2104.05238v1

    • [math.PR]Asymptotic distributions for weighted power sums of extreme values
    Lillian Achola Oluoch, László Viharos
    http://arxiv.org/abs/2104.04863v1

    • [math.PR]Semi-今日学术视野(2021.4.14) - 图7-normal: a Hybrid between Normal and 今日学术视野(2021.4.14) - 图8-normal
    Yifan Li, Reg Kulperger, Hao Yu
    http://arxiv.org/abs/2104.04910v1

    • [math.PR]Statistical inference of finite-rank tensors
    Hong-Bin Chen, Jean-Christophe Mourrat, Jiaming Xia
    http://arxiv.org/abs/2104.05360v1

    • [math.ST]A symmetric matrix-variate normal local approximation for the Wishart distribution and some applications
    Frédéric Ouimet
    http://arxiv.org/abs/2104.04882v1

    • [math.ST]Analytic and Bootstrap-after-Cross-Validation Methods for Selecting Penalty Parameters of High-Dimensional M-Estimators
    Denis Chetverikov, Jesper Riis-Vestergaard Sørensen
    http://arxiv.org/abs/2104.04716v1

    • [math.ST]Spiked eigenvalues of noncentral Fisher matrix with applications
    Xiaozhuo Zhang, Zhiqiang Hou, Zhidong Bai, Jiang Hu
    http://arxiv.org/abs/2104.04734v1

    • [physics.comp-ph]High Performance Implementation of Boris Particle Pusher on DPC++. A First Look at oneAPI
    Valentin Volokitin, Alexey Bashinov, Evgeny Efimenko, Arkady Gonoskov, Iosif Meyerov
    http://arxiv.org/abs/2104.04579v1

    • [physics.geo-ph]Applications of physics-informed scientific machine learning in subsurface science: A survey
    Alexander Y. Sun, Hongkyu Yoon, Chung-Yan Shih, Zhi Zhong
    http://arxiv.org/abs/2104.04764v1

    • [physics.geo-ph]DuRIN: A Deep-unfolded Sparse Seismic Reflectivity Inversion Network
    Swapnil Mache, Praveen Kumar Pokala, Kusala Rajendran, Chandra Sekhar Seelamantula
    http://arxiv.org/abs/2104.04704v1

    • [physics.soc-ph]On the Accuracy of Deterministic Models for Viral Spread on Networks
    Anirudh Sridhar, Soummya Kar
    http://arxiv.org/abs/2104.04913v1

    • [q-bio.NC]Modelling Brain Connectivity Networks by Graph Embedding for Dyslexia Diagnosis
    Marco A. Formoso, Andrés Ortiz, Francisco J. Martínez-Murcia, Nicolás Gallego-Molina, Juan L. Luque
    http://arxiv.org/abs/2104.05497v1

    • [q-bio.QM]Deep Learning Identifies Neuroimaging Signatures of Alzheimer’s Disease Using Structural and Synthesized Functional MRI Data
    Nanyan Zhu, Chen Liu, Xinyang Feng, Dipika Sikka, Sabrina Gjerswold-Selleck, Scott A. Small, Jia Guo
    http://arxiv.org/abs/2104.04672v1

    • [q-fin.ST]A Fast Evidential Approach for Stock Forecasting
    Tianxiang Zhan, Fuyuan Xiao
    http://arxiv.org/abs/2104.05204v1

    • [quant-ph]Classical-quantum network coding: a story about tensor
    Clément Meignant, Frédéric Grosshans, Damian Markham
    http://arxiv.org/abs/2104.04745v1

    • [quant-ph]QZNs: Quantum Z-numbers
    Jixiang Deng, Yong Deng
    http://arxiv.org/abs/2104.05190v1

    • [quant-ph]Quantum Machine Learning for Power System Stability Assessment
    Yifan Zhou, Peng Zhang
    http://arxiv.org/abs/2104.04855v1

    • [stat.AP]Computer Algebra Systems in R with caracas
    Mikkel Meyer Andersen, Søren Højsgaard
    http://arxiv.org/abs/2104.05292v1

    • [stat.AP]Increased risk of hospitalisation for COVID-19 patients infected with SARS-CoV-2 variant B.1.1.7
    Tommy Nyberg, Katherine A. Twohig, Ross J. Harris, Shaun R. Seaman, Joe Flannagan, Hester Allen, Andre Charlett, Daniela De Angelis, Gavin Dabrera, Anne M. Presanis
    http://arxiv.org/abs/2104.05560v1

    • [stat.AP]Inferring Risks of Coronavirus Transmission from Community Household Data
    Thomas House, Lorenzo Pellis, Koen B. Pouwels, Sebastian Bacon, Arturas Eidukas, Kaveh Jahanshahi, Rosalind M. Eggo, A. Sarah Walker
    http://arxiv.org/abs/2104.04605v1

    • [stat.ME]A dose-effect network meta-analysis model: an application in antidepressants
    Tasnim Hamza, Toshi A. Furukawa, Nicola Orsini, Andrea Cipriani, Cynthia Iglesias, Georgia Salanti
    http://arxiv.org/abs/2104.05414v1

    • [stat.ME]A smoothed and probabilistic PARAFAC model with covariates
    Leying Guan
    http://arxiv.org/abs/2104.05184v1

    • [stat.ME]Bayesian exponential random graph models for populations of networks
    Brieuc Lehmann, Simon White
    http://arxiv.org/abs/2104.05110v1

    • [stat.ME]Conditional Inference: Towards a Hierarchy of Statistical Evidence
    Ying Jin, Dominik Rothenäusler
    http://arxiv.org/abs/2104.04565v1

    • [stat.ME]Couplings for Multinomial Hamiltonian Monte Carlo
    Kai Xu, Tor Erlend Fjelde, Charles Sutton, Hong Ge
    http://arxiv.org/abs/2104.05134v1

    • [stat.ME]CovNet: Covariance Networks for Functional Data on Multidimensional Domains
    Soham Sarkar, Victor M. Panaretos
    http://arxiv.org/abs/2104.05021v1

    • [stat.ME]Exact-corrected confidence interval for risk difference in noninferiority binomial trials
    Nour Hawila, Arthur Berg
    http://arxiv.org/abs/2104.04660v1

    • [stat.ME]Inference from Non-Random Samples Using Bayesian Machine Learning
    Yutao Liu, Andrew Gelman, Qixuan Chen
    http://arxiv.org/abs/2104.05192v1

    • [stat.ME]Model-assisted analyses of cluster-randomized experiments
    Fangzhou Su, Peng Ding
    http://arxiv.org/abs/2104.04647v1

    • [stat.ME]Modeling Time-Varying Random Objects and Dynamic Networks
    Paromita Dubey, Hans-Georg Müller
    http://arxiv.org/abs/2104.04628v1

    • [stat.ME]Nonparametric Method for Clustered Data in Pre-Post Factorial Design
    Solomon W. Harrar, Yue Cui
    http://arxiv.org/abs/2104.04966v1

    • [stat.ME]On the Evaluation of Surrogate Markers in Real World Data Settings
    Larry Han, Xuan Wang, Tianxi Cai
    http://arxiv.org/abs/2104.05513v1

    • [stat.ME]Parallel integrative learning for large-scale multi-response regression with incomplete outcomes
    Ruipeng Dong, Daoji Li, Zemin Zheng
    http://arxiv.org/abs/2104.05076v1

    • [stat.ME]Probabilistic HIV Recency Classification — A Logistic Regression without Labeled Individual Level Training Data
    Ben Sheng, Changcheng Li, Le Bao, Runze Li
    http://arxiv.org/abs/2104.05150v1

    • [stat.ML]Deep Time Series Forecasting with Shape and Temporal Criteria
    Vincent Le Guen, Nicolas Thome
    http://arxiv.org/abs/2104.04610v1

    • [stat.ML]GPflux: A Library for Deep Gaussian Processes
    Vincent Dutordoir, Hugh Salimbeni, Eric Hambro, John McLeod, Felix Leibfried, Artem Artemev, Mark van der Wilk, James Hensman, Marc P. Deisenroth, ST John
    http://arxiv.org/abs/2104.05674v1

    • [stat.ML]Random Intersection Chains
    Qiuqiang Lin, Chuanhou Gao
    http://arxiv.org/abs/2104.04714v1

    • [stat.ML]Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning
    Alexander Immer, Matthias Bauer, Vincent Fortuin, Gunnar Rätsch, Mohammad Emtiyaz Khan
    http://arxiv.org/abs/2104.04975v1

    • [stat.ML]Unsuitability of NOTEARS for Causal Graph Discovery
    Marcus Kaiser, Maksim Sipos
    http://arxiv.org/abs/2104.05441v1