cond-mat.dis-nn - 无序系统与神经网络
    cs.AI - 人工智能
    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.DC - 分布式、并行与集群计算
    cs.DL - 数字图书馆
    cs.HC - 人机接口
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.LG - 自动学习
    cs.MA - 多代理系统
    cs.MM - 多媒体
    cs.NE - 神经与进化计算
    cs.RO - 机器人学
    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.OC - 优化与控制
    math.PR - 概率
    physics.geo-ph - 地球物理学
    q-fin.ST - 统计金融学
    quant-ph - 量子物理
    stat.AP - 应用统计
    stat.CO - 统计计算
    stat.ME - 统计方法论
    stat.ML - (统计)机器学习

    • [cond-mat.dis-nn]Asymptotic properties of one-layer artificial neural networks with sparse connectivity
    • [cs.AI]A Review of SHACL: From Data Validation to Schema Reasoning for RDF Graphs
    • [cs.AI]A Unified Framework for Adversarial Attack and Defense in Constrained Feature Space
    • [cs.AI]Architecting and Visualizing Deep Reinforcement Learning Models
    • [cs.AI]Easy Semantification of Bioassays
    • [cs.AI]EngineKGI: Closed-Loop Knowledge Graph Inference
    • [cs.AI]Evaluation of mathematical questioning strategies using data collected through weak supervision
    • [cs.AI]Finding, Scoring and Explaining Arguments in Bayesian Networks
    • [cs.AI]First Steps of an Approach to the ARC Challenge based on Descriptive Grid Models and the Minimum Description Length Principle
    • [cs.AI]Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL
    • [cs.AI]Indexed Minimum Empirical Divergence for Unimodal Bandits
    • [cs.AI]Maximum Entropy Model-based Reinforcement Learning
    • [cs.AI]Modeling human intention inference in continuous 3D domains by inverse planning and body kinematics
    • [cs.AI]Narrative Cartography with Knowledge Graphs
    • [cs.AI]Personal Comfort Estimation in Partial Observable Environment using Reinforcement Learning
    • [cs.CL]A General Language Assistant as a Laboratory for Alignment
    • [cs.CL]AST-Transformer: Encoding Abstract Syntax Trees Efficiently for Code Summarization
    • [cs.CL]CO-STAR: Conceptualisation of Stereotypes for Analysis and Reasoning
    • [cs.CL]CO2Sum:Contrastive Learning for Factual-Consistent Abstractive Summarization
    • [cs.CL]Changepoint Analysis of Topic Proportions in Temporal Text Data
    • [cs.CL]Context-Dependent Semantic Parsing for Temporal Relation Extraction
    • [cs.CL]DKPLM: Decomposable Knowledge-enhanced Pre-trained Language Model for Natural Language Understanding
    • [cs.CL]Emotions are Subtle: Learning Sentiment Based Text Representations Using Contrastive Learning
    • [cs.CL]From Consensus to Disagreement: Multi-Teacher Distillation for Semi-Supervised Relation Extraction
    • [cs.CL]How not to Lie with a Benchmark: Rearranging NLP Leaderboards
    • [cs.CL]Iconary: A Pictionary-Based Game for Testing Multimodal Communication with Drawings and Text
    • [cs.CL]Improving Controllability of Educational Question Generation by Keyword Provision
    • [cs.CL]KPDrop: An Approach to Improving Absent Keyphrase Generation
    • [cs.CL]LOGEN: Few-shot Logical Knowledge-Conditioned Text Generation with Self-training
    • [cs.CL]ScaleVLAD: Improving Multimodal Sentiment Analysis via Multi-Scale Fusion of Locally Descriptors
    • [cs.CL]Towards generating citation sentences for multiple references with intent control
    • [cs.CL]Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-Sentence Dependency Graph
    • [cs.CR]ReIGNN: State Register Identification Using Graph Neural Networks for Circuit Reverse Engineering
    • [cs.CV]”Just Drive”: Colour Bias Mitigation for Semantic Segmentation in the Context of Urban Driving
    • [cs.CV]3D-Aware Semantic-Guided Generative Model for Human Synthesis
    • [cs.CV]3rd Place Solution for NeurIPS 2021 Shifts Challenge: Vehicle Motion Prediction
    • [cs.CV]A Fast Knowledge Distillation Framework for Visual Recognition
    • [cs.CV]Altering Facial Expression Based on Textual Emotion
    • [cs.CV]Attention based Occlusion Removal for Hybrid Telepresence Systems
    • [cs.CV]BEVT: BERT Pretraining of Video Transformers
    • [cs.CV]Batch Normalization Tells You Which Filter is Important
    • [cs.CV]CLAWS: Contrastive Learning with hard Attention and Weak Supervision
    • [cs.CV]CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer
    • [cs.CV]CloudWalker: 3D Point Cloud Learning by Random Walks for Shape Analysis
    • [cs.CV]Co-domain Symmetry for Complex-Valued Deep Learning
    • [cs.CV]Consensus Graph Representation Learning for Better Grounded Image Captioning
    • [cs.CV]Controllable Video Captioning with an Exemplar Sentence
    • [cs.CV]DenseCLIP: Extract Free Dense Labels from CLIP
    • [cs.CV]DenseCLIP: Language-Guided Dense Prediction with Context-Aware Prompting
    • [cs.CV]Dimensions of Motion: Learning to Predict a Subspace of Optical Flow from a Single Image
    • [cs.CV]Efficient Neural Radiance Fields with Learned Depth-Guided Sampling
    • [cs.CV]Event Neural Networks
    • [cs.CV]FIBA: Frequency-Injection based Backdoor Attack in Medical Image Analysis
    • [cs.CV]Fast automatic deforestation detectors and their extensions for other spatial objects
    • [cs.CV]GANORCON: Are Generative Models Useful for Few-shot Segmentation?
    • [cs.CV]GANSeg: Learning to Segment by Unsupervised Hierarchical Image Generation
    • [cs.CV]GLAMR: Global Occlusion-Aware Human Mesh Recovery with Dynamic Cameras
    • [cs.CV]Generalized Closed-form Formulae for Feature-based Subpixel Alignment in Patch-based Matching
    • [cs.CV]Generating Diverse 3D Reconstructions from a Single Occluded Face Image
    • [cs.CV]Hierarchical Neural Implicit Pose Network for Animation and Motion Retargeting
    • [cs.CV]Improved Multiscale Vision Transformers for Classification and Detection
    • [cs.CV]Inferring Prototypes for Multi-Label Few-Shot Image Classification with Word Vector Guided Attention
    • [cs.CV]InsCLR: Improving Instance Retrieval with Self-Supervision
    • [cs.CV]Interpretable Deep Learning-Based Forensic Iris Segmentation and Recognition
    • [cs.CV]Iterative Frame-Level Representation Learning And Classification For Semi-Supervised Temporal Action Segmentation
    • [cs.CV]Learning Neural Light Fields with Ray-Space Embedding Networks
    • [cs.CV]Learning Spatial-Temporal Graphs for Active Speaker Detection
    • [cs.CV]Leveraging Human Selective Attention for Medical Image Analysis with Limited Training Data
    • [cs.CV]Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks
    • [cs.CV]MTFNet: Mutual-Transformer Fusion Network for RGB-D Salient Object Detection
    • [cs.CV]Machine Learning-Based Classification Algorithms for the Prediction of Coronary Heart Diseases
    • [cs.CV]Masked-attention Mask Transformer for Universal Image Segmentation
    • [cs.CV]Maximum Consensus by Weighted Influences of Monotone Boolean Functions
    • [cs.CV]MegBA: A High-Performance and Distributed Library for Large-Scale Bundle Adjustment
    • [cs.CV]N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras
    • [cs.CV]NeSF: Neural Shading Field for Image Harmonization
    • [cs.CV]Neural Point Light Fields
    • [cs.CV]Neural Weight Step Video Compression
    • [cs.CV]OW-DETR: Open-world Detection Transformer
    • [cs.CV]Object-Centric Unsupervised Image Captioning
    • [cs.CV]Object-aware Monocular Depth Prediction with Instance Convolutions
    • [cs.CV]Object-aware Video-language Pre-training for Retrieval
    • [cs.CV]On Salience-Sensitive Sign Classification in Autonomous Vehicle Path Planning: Experimental Explorations with a Novel Dataset
    • [cs.CV]Overcoming the Domain Gap in Neural Action Representations
    • [cs.CV]PartImageNet: A Large, High-Quality Dataset of Parts
    • [cs.CV]Point Cloud Segmentation Using Sparse Temporal Local Attention
    • [cs.CV]PreViTS: Contrastive Pretraining with Video Tracking Supervision
    • [cs.CV]Probabilistic Approach for Road-Users Detection
    • [cs.CV]Putting 3D Spatially Sparse Networks on a Diet
    • [cs.CV]Recognizing Scenes from Novel Viewpoints
    • [cs.CV]Relational Graph Learning for Grounded Video Description Generation
    • [cs.CV]Routing with Self-Attention for Multimodal Capsule Networks
    • [cs.CV]SCNet: A Generalized Attention-based Model for Crack Fault Segmentation
    • [cs.CV]SEAL: Self-supervised Embodied Active Learning using Exploration and 3D Consistency
    • [cs.CV]Sample Prior Guided Robust Model Learning to Suppress Noisy Labels
    • [cs.CV]Self-supervised Video Transformer
    • [cs.CV]Semantic-Sparse Colorization Network for Deep Exemplar-based Colorization
    • [cs.CV]Stacked Temporal Attention: Improving First-person Action Recognition by Emphasizing Discriminative Clips
    • [cs.CV]Stronger Baseline for Person Re-Identification
    • [cs.CV]StyleMesh: Style Transfer for Indoor 3D Scene Reconstructions
    • [cs.CV]SwinTrack: A Simple and Strong Baseline for Transformer Tracking
    • [cs.CV]Syntax Customized Video Captioning by Imitating Exemplar Sentences
    • [cs.CV]TBN-ViT: Temporal Bilateral Network with Vision Transformer for Video Scene Parsing
    • [cs.CV]TCTN: A 3D-Temporal Convolutional Transformer Network for Spatiotemporal Predictive Learning
    • [cs.CV]TISE: A Toolbox for Text-to-Image Synthesis Evaluation
    • [cs.CV]Temporally Resolution Decrement: Utilizing the Shape Consistency for Higher Computational Efficiency
    • [cs.CV]The Second Place Solution for ICCV2021 VIPriors Instance Segmentation Challenge
    • [cs.CV]TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation
    • [cs.CV]TransMEF: A Transformer-Based Multi-Exposure Image Fusion Framework using Self-Supervised Multi-Task Learning
    • [cs.CV]Unconstrained Face Sketch Synthesis via Perception-Adaptive Network and A New Benchmark
    • [cs.CV]Uni-Perceiver: Pre-training Unified Architecture for Generic Perception for Zero-shot and Few-shot Tasks
    • [cs.CV]Using Deep Image Prior to Assist Variational Selective Segmentation Deep Learning Algorithms
    • [cs.CV]Video Frame Interpolation without Temporal Priors
    • [cs.CV]Video-Text Pre-training with Learned Regions
    • [cs.CV]Vision Pair Learning: An Efficient Training Framework for Image Classification
    • [cs.CV]Visual-Semantic Transformer for Scene Text Recognition
    • [cs.CV]Zero-Shot Text-Guided Object Generation with Dream Fields
    • [cs.CY]”Vironment”: An Art of Wearable Social Distancing
    • cs.CY COVID 19: Genomic surveillance and evaluation of the impact on the population speaker of indigenous language in Mexico
    • [cs.CY]Achieving a Data-driven Risk Assessment Methodology for Ethical AI
    • [cs.CY]Advancing Artificial Intelligence and Machine Learning in the U.S. Government Through Improved Public Competitions
    • [cs.CY]Expose Uncertainty, Instill Distrust, Avoid Explanations: Towards Ethical Guidelines for AI
    • [cs.CY]Lists of Top Artists to Watch computed algorithmically
    • [cs.CY]Models of fairness in federated learning
    • [cs.CY]Ownership and Creativity in Generative Models
    • [cs.CY]Security Monitoring System Using FaceNet For Wireless Sensor Network
    • [cs.CY]The Effect of COVID-19 on the Transit System in Two Regions: Japan and USA
    • [cs.CY]The empirical study of e-learning post-acceptance after the spread of COVID-19: A multi-analytical approach based hybrid SEM-ANN
    • [cs.DC]Grafana plugin for visualising vote based consensus mechanisms, and network P2P overlay networks
    • [cs.DC]Memory-efficient array redistribution through portable collective communication
    • [cs.DC]Simplifying heterogeneous migration between x86 and ARM machines
    • [cs.DL]LDA2Net: Digging under the surface of COVID-19 topics in scientific literature
    • [cs.HC]Collaborative AI Needs Stronger Assurances Driven by Risks
    • [cs.HC]On Two XAI Cultures: A Case Study of Non-technical Explanations in Deployed AI System
    • [cs.HC]Secure and Safety Mobile Network System for Visually Impaired People
    • [cs.IR]ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction
    • [cs.IR]Contrastive Cross-domain Recommendation in Matching
    • [cs.IR]Learning Robust Recommender from Noisy Implicit Feedback
    • [cs.IR]Local Citation Recommendation with Hierarchical-Attention Text Encoder and SciBERT-based Reranking
    • [cs.IR]Tiny-NewsRec: Efficient and Effective PLM-based News Recommendation
    • [cs.IR]Where the Earth is flat and 9/11 is an inside job: A comparative algorithm audit of conspiratorial information in web search results
    • [cs.IT]Age of Information in Prioritized Random Access
    • [cs.IT]Antenna Selection in Polarization Reconfigurable MIMO (PR-MIMO) Communication Systems
    • [cs.IT]Blind Super-resolution of Point Sources via Projected Gradient Descent
    • [cs.IT]Channel Estimation for STAR-RIS-aided Wireless Communication
    • [cs.IT]IMRecoNet: Learn to Detect in Index Modulation Aided MIMO Systems with Complex Valued Neural Networks
    • [cs.IT]Rate-Splitting Meets Cell-Free MIMOCommunications
    • [cs.IT]Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface Assisted NOMA Networks
    • [cs.L
    59d7
    G]Differentially Private SGD with Sparse Gradients
    • [cs.LG]A Communication-efficient Federated learning assisted by Central data: Implementation of vertical training into Horizontal Federated learning
    • [cs.LG]A Discrete-event-based Simulator for Deep Learning at Edge
    • [cs.LG]A Hybrid Science-Guided Machine Learning Approach for Modeling and Optimizing Chemical Processes
    • [cs.LG]Active Learning for Domain Adaptation: An Energy-based Approach
    • [cs.LG]Adversarial Robustness of Deep Reinforcement Learning based Dynamic Recommender Systems
    • [cs.LG]AutoGEL: An Automated Graph Neural Network with Explicit Link Information
    • [cs.LG]Bayesian Optimization over Permutation Spaces
    • [cs.LG]CELLS: Cost-Effective Evolution in Latent Space for Goal-Directed Molecular Generation
    • [cs.LG]Computing Class Hierarchies from Classifiers
    • [cs.LG]Constrained Machine Learning: The Bagel Framework
    • [cs.LG]Context-Aware Online Client Selection for Hierarchical Federated Learning
    • [cs.LG]Contrastive Adaptive Propagation Graph Neural Networks for Efficient Graph Learning
    • [cs.LG]Controlling Conditional Language Models with Distributional Policy Gradients
    • [cs.LG]Counterfactual Explanations via Latent Space Projection and Interpolation
    • [cs.LG]DPVI: A Dynamic-Weight Particle-Based Variational Inference Framework
    • [cs.LG]Data-Driven Interaction Analysis of Line Failure Cascading in Power Grid Networks
    • [cs.LG]Decomposing Representations for Deterministic Uncertainty Estimation
    • [cs.LG]Deep Transfer Learning: A Novel Collaborative Learning Model for Cyberattack Detection Systems in IoT Networks
    • [cs.LG]Deep residential representations: Using unsupervised learning to unlock elevation data for geo-demographic prediction
    • [cs.LG]Detecting Extratropical Cyclones of the Northern Hemisphere with Single Shot Detector
    • [cs.LG]Differentiable Spatial Planning using Transformers
    • [cs.LG]Editing a classifier by rewriting its prediction rules
    • [cs.LG]Efficient Symptom Inquiring and Diagnosis via Adaptive Alignment of Reinforcement Learning and Classification
    • [cs.LG]Embedding Decomposition for Artifacts Removal in EEG Signals
    • [cs.LG]FedRAD: Federated Robust Adaptive Distillation
    • [cs.LG]Federated Learning with Adaptive Batchnorm for Personalized Healthcare
    • [cs.LG]Fighting Fire with Fire: Contrastive Debiasing without Bias-free Data via Generative Bias-transformation
    • [cs.LG]Flood Analytics Information System (FAIS) Version 4.00 Manual
    • [cs.LG]Gaussian Mixture Variational Autoencoder with Contrastive Learning for Multi-Label Classification
    • [cs.LG]Graph4Rec: A Universal Toolkit with Graph Neural Networks for Recommender Systems
    • [cs.LG]Hierarchical Learning to Solve Partial Differential Equations Using Physics-Informed Neural Networks
    • [cs.LG]Homotopy Based Reinforcement Learning with Maximum Entropy for Autonomous Air Combat
    • [cs.LG]How Smart Guessing Strategies Can Yield Massive Scalability Improvements for Sparse Decision Tree Optimization
    • [cs.LG]HyperSPNs: Compact and Expressive Probabilistic Circuits
    • [cs.LG]Incomplete Multi-view Clustering via Cross-view Relation Transfer
    • [cs.LG]Inducing Causal Structure for Interpretable Neural Networks
    • [cs.LG]Large-Scale Data Mining of Rapid Residue Detection Assay Data From HTML and PDF Documents: Improving Data Access and Visualization for Veterinarians
    • [cs.LG]Learning Invariant Representations with Missing Data
    • [cs.LG]Learning Optimal Predictive Checklists
    • [cs.LG]Level set learning with pseudo-reversible neural networks for nonlinear dimension reduction in function approximation
    • [cs.LG]Loss Landscape Dependent Self-Adjusting Learning Rates in Decentralized Stochastic Gradient Descent
    • [cs.LG]Mixing Deep Learning and Multiple Criteria Optimization: An Application to Distributed Learning with Multiple Datasets
    • [cs.LG]Multi-Domain Transformer-Based Counterfactual Augmentation for Earnings Call Analysis
    • [cs.LG]Multi-task Self-distillation for Graph-based Semi-Supervised Learning
    • [cs.LG]Neural Stochastic Dual Dynamic Programming
    • [cs.LG]Newton methods based convolution neural networks using parallel processing
    • [cs.LG]On Large Batch Training and Sharp Minima: A Fokker-Planck Perspective
    • [cs.LG]Optimal regularizations for data generation with probabilistic graphical models
    • [cs.LG]Output-weighted and relative entropy loss functions for deep learning precursors of extreme events
    • [cs.LG]Personalized Federated Learning of Driver Prediction Models for Autonomous Driving
    • [cs.LG]ProtGNN: Towards Self-Explaining Graph Neural Networks
    • [cs.LG]Provable Guarantees for Understanding Out-of-distribution Detection
    • [cs.LG]Quantile Filtered Imitation Learning
    • [cs.LG]Recommending with Recommendations
    • [cs.LG]Residual Pathway Priors for Soft Equivariance Constraints
    • [cs.LG]Reward-Free Attacks in Multi-Agent Reinforcement Learning
    • [cs.LG]Risk-Aware Algorithms for Combinatorial Semi-Bandits
    • [cs.LG]Robust Robotic Control from Pixels using Contrastive Recurrent State-Space Models
    • [cs.LG]Safe Exploration for Constrained Reinforcement Learning with Provable Guarantees
    • [cs.LG]Safe Reinforcement Learning for Grid Voltage Control
    • [cs.LG]Sample Complexity of Robust Reinforcement Learning with a Generative Model
    • [cs.LG]ShuttleNet: Position-aware Fusion of Rally Progress and Player Styles for Stroke Forecasting in Badminton
    • [cs.LG]Source Free Unsupervised Graph Domain Adaptation
    • [cs.LG]Stationary Diffusion State Neural Estimation for Multiview Clustering
    • [cs.LG]Target Propagation via Regularized Inversion
    • [cs.LG]The Impact of Data Distribution on Fairness and Robustness in Federated Learning
    • [cs.LG]TinyML Platforms Benchmarking
    • [cs.LG]Training Efficiency and Robustness in Deep Learning
    • [cs.LG]Trap of Feature Diversity in the Learning of MLPs
    • [cs.LG]Who will dropout from university? Academic risk prediction based on interpretable machine learning
    • [cs.LG]Why Calibration Error is Wrong Given Model Uncertainty: Using Posterior Predictive Checks with Deep Learning
    • [cs.MA]Multi-scale simulation of COVID-19 epidemics
    • [cs.MA]Resonating Minds — Emergent Collaboration Through Hierarchical Active Inference
    • [cs.MM]FNR: A Similarity and Transformer-Based Approachto Detect Multi-Modal FakeNews in Social Media
    • [cs.NE]Adaptive Group Collaborative Artificial Bee Colony Algorithm
    • [cs.NE]Evolving Open Complexity
    • [cs.NE]Frequency Fitness Assignment: Optimization without a Bias for Good Solutions can be Efficient
    • [cs.NE]The (1+1)-ES Reliably Overcomes Saddle Points
    • [cs.NE]ViF-SD2E: A Robust Weakly-Supervised Method for Neural Decoding
    • [cs.RO]Control of over-redundant cooperative manipulation via sampled communication
    • [cs.RO]Distributed Control for a Robotic Swarm to Pass through a Curve Virtual Tube
    • [cs.RO]Effects of Interfaces on Human-Robot Trust: Specifying and Visualizing Physical Zones
    • [cs.RO]Multi-Object Grasping — Estimating the Number of Objects in a Robotic Grasp
    • [cs.RO]Situation-Aware Environment Perception Using a Multi-Layer Attention Map
    • [cs.RO]The Surprising Effectiveness of Representation Learning for Visual Imitation
    • [cs.RO]Wish you were here: Hindsight Goal Selection for long-horizon dexterous manipulation
    • [cs.SE]A Survey on Scenario-Based Testing for Automated Driving Systems in High-Fidelity Simulation
    • [cs.SE]Borrowing from Similar Code: A Deep Learning NLP-Based Approach for Log Statement Automation
    • [cs.SE]Monolith to Microservices: Representing Application Software through Heterogeneous GNN
    • [cs.SI]A New Approach to Detect Important Members that Create the Communities in Bipartite Networks
    • [cs.SI]Are Investors Biased Against Women? Analyzing How Gender Affects Startup Funding in Europe
    • [cs.SI]Learning Large-scale Network Embedding from Representative Subgraph
    • [cs.SI]Perception and Attitude of Reddit Users Towards Use of Face-Masks in Controlling COVID-19
    • [cs.SI]Reconsidering Tweets: Intervening During Tweet Creation Decreases Offensive Content
    • [cs.SI]Sentinel node approach to monitoring online COVID-19 misinformation
    • [cs.SI]Subgraph Contrastive Link Representation Learning
    • [cs.SI]The voice of few, the opinions of many: evidence of social biases in Twitter COVID-19 fake news sharing
    • [cs.SI]Unifying Diffusion Models on Networks and Their Influence Maximisation
    • [econ.EM]Structural Sieves
    • [eess.AS]A Mixture of Expert Based Deep Neural Network for Improved ASR
    • [eess.IV]CDLNet: Noise-Adaptive Convolutional Dictionary Learning Network for Blind Denoising and Demosaicing
    • [eess.IV]DFTS2: Simulating Deep Feature Transmission Over Packet Loss Channels
    • [eess.IV]Deep Learning-Based Carotid Artery Vessel Wall Segmentation in Black-Blood MRI Using Anatomical Priors
    • [eess.IV]Highly accelerated MR parametric mapping by undersampling the k-space and reducing the contrast number simultaneously with deep learning
    • [eess.IV]Multi-task fusion for improving mammography screening data classification
    • [eess.IV]Reference-guided Pseudo-Label Generation for Medical Semantic Segmentation
    • [eess.IV]Total-Body Low-Dose CT Image Denoising using Prior Knowledge Transfer Technique with Contrastive Regularization Mechanism
    • [eess.SP]Analysis of an adaptive lead weighted ResNet for multiclass classification of 12-lead ECGs
    • [eess.SP]Time-Series Estimation from Randomly Time-Warped Observations
    • [eess.SY]Youla-REN: Learning Nonlinear Feedback Policies with Robust Stability Guarantees
    • [math.OC]Near-Optimal Lower Bounds For Convex Optimization For All Orders of Smoothness
    • [math.PR]A Note on the Borel-Cantelli Lemma
    • [math.PR]Interval extropy and weighted interval extropy
    • [physics.geo-ph]Joint Characterization of the Cryospheric Spectral Feature Space
    • [q-fin.ST]Forex Trading Volatility Prediction using NeuralNetwork Models
    • [quant-ph]Quantum advantage in learning from experiments
    • [quant-ph]Revisiting dequantization and quantum advantage in learning tasks
    • [stat.AP]A note on sampling biases in the Bangladesh mask trial
    • [stat.AP]Bradley-Terry Modeling with Multiple Game Outcomes with Applications to College Hockey
    • [stat.AP]Hierarchical Forecasting of Dengue Incidence in Sri Lanka
    • [stat.AP]Hydroclimatic time series features at multiple time scales
    • [stat.AP]Interactive Visualization of Spatial Omics Neighborhoods
    • [stat.AP]Using Ecometric Data to Explore Sources of Cross-Site Impact Variance in Multi-Site Trials
    • [stat.CO]Bridge Simulation on Lie Groups and Homogeneous Spaces with Application to Parameter Estimation
    • [stat.ME]Diffusion Mean Estimation on the Diagonal of Product Manifolds
    • [stat.ME]Hierarchical clustering: visualization, feature importance and model selection
    • [stat.ME]Intervention treatment distributions that depend on the observed treatment process and model double robustness in causal survival analysis
    • [stat.ME]Investigating an Alternative for Estimation from a Nonprobability Sample: Matching plus Calibration
    • [stat.ME]Maximum Likelihood Estimation for Brownian Motion Tree Models Based on One Sample
    • [stat.ME]On the optimization of hyperparameters in Gaussian process regression
    • [stat.ME]On the robustness and precision of mixed-model analysis of covariance in cluster-randomized trials
    • [stat.ME]Prior knowledge elicitation: The past, present, and future
    • [stat.ME]Sequential Spatially Balanced Sampling
    • [stat.ME]Subgroup Analysis for Longitudinal data via Semiparametric Additive Mixed Effect Model
    • [stat.ML]Convergence of batch Greenkhorn for Regularized Multimarginal Optimal Transport
    • [stat.ML]Generalizing Off-Policy Learning under Sample Selection Bias
    • [stat.ML]Robust and Adaptive Temporal-Difference Learning Using An Ensemble of Gaussian Processes

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

    • [cond-mat.dis-nn]Asymptotic properties of one-layer artificial neural networks with sparse connectivity
    Christian Hirsch, Matthias Neumann, Volker Schmidt
    http://arxiv.org/abs/2112.00732v1

    • [cs.AI]A Review of SHACL: From Data Validation to Schema Reasoning for RDF Graphs
    Paolo Pareti, George Konstantinidis
    http://arxiv.org/abs/2112.01441v1

    • [cs.AI]A Unified Framework for Adversarial Attack and Defense in Constrained Feature Space
    Thibault Simonetto, Salijona Dyrmishi, Salah Ghamizi, Maxime Cordy, Yves Le Traon
    http://arxiv.org/abs/2112.01156v1

    • [cs.AI]Architecting and Visualizing Deep Reinforcement Learning Models
    Alexander Neuwirth, Derek Riley
    http://arxiv.org/abs/2112.01451v1

    • [cs.AI]Easy Semantification of Bioassays
    Marco Anteghini, Jennifer D’Souza, Vitor A. P. Martins dos Santos, Sören Auer
    http://arxiv.org/abs/2111.15182v2

    • [cs.AI]EngineKGI: Closed-Loop Knowledge Graph Inference
    Guanglin Niu, Bo Li, Yongfei Zhang, Shiliang Pu
    http://arxiv.org/abs/2112.01040v1

    • [cs.AI]Evaluation of mathematical questioning strategies using data collected through weak supervision
    Debajyoti Datta, Maria Phillips, James P Bywater, Jennifer Chiu, Ginger S. Watson, Laura E. Barnes, Donald E Brown
    http://arxiv.org/abs/2112.00985v1

    • [cs.AI]Finding, Scoring and Explaining Arguments in Bayesian Networks
    Jaime Sevilla
    http://arxiv.org/abs/2112.00799v1

    • [cs.AI]First Steps of an Approach to the ARC Challenge based on Descriptive Grid Models and the Minimum Description Length Principle
    Sébastien Ferré
    http://arxiv.org/abs/2112.00848v1

    • [cs.AI]Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL
    Charles Packer, Pieter Abbeel, Joseph E. Gonzalez
    http://arxiv.org/abs/2112.00901v1

    • [cs.AI]Indexed Minimum Empirical Divergence for Unimodal Bandits
    Hassan Saber, Pierre Ménard, Odalric-Ambrym Maillard
    http://arxiv.org/abs/2112.01452v1

    • [cs.AI]Maximum Entropy Model-based Reinforcement Learning
    Oleg Svidchenko, Aleksei Shpilman
    http://arxiv.org/abs/2112.01195v1

    • [cs.AI]Modeling human intention inference in continuous 3D domains by inverse planning and body kinematics
    Yingdong Qian, Marta Kryven, Tao Gao, Hanbyul Joo, Josh Tenenbaum
    http://arxiv.org/abs/2112.00903v1

    • [cs.AI]Narrative Cartography with Knowledge Graphs
    Gengchen Mai, Weiming Huang, Ling Cai, Rui Zhu, Ni Lao
    http://arxiv.org/abs/2112.00970v1

    • [cs.AI]Personal Comfort Estimation in Partial Observable Environment using Reinforcement Learning
    Shashi Suman, Ali Etemad, Francois Rivest
    http://arxiv.org/abs/2112.00971v1

    • [cs.CL]A General Language Assistant as a Laboratory for Alignment
    Amanda Askell, Yuntao Bai, Anna Chen, Dawn Drain, Deep Ganguli, Tom Henighan, Andy Jones, Nicholas Joseph, Ben Mann, Nova DasSarma, Nelson Elhage, Zac Hatfield-Dodds, Danny Hernandez, Jackson Kernion, Kamal Ndousse, Catherine Olsson, Dario Amodei, Tom Brown, Jack Clark, Sam McCandlish, Chris Olah, Jared Kaplan
    http://arxiv.org/abs/2112.00861v1

    • [cs.CL]AST-Transformer: Encoding Abstract Syntax Trees Efficiently for Code Summarization
    Ze Tang, Chuanyi Li, Jidong Ge, Xiaoyu Shen, Zheling Zhu, Bin Luo
    http://arxiv.org/abs/2112.01184v1

    • [cs.CL]CO-STAR: Conceptualisation of Stereotypes for Analysis and Reasoning
    Teyun Kwon, Anandha Gopalan
    http://arxiv.org/abs/2112.00819v1

    • [cs.CL]CO2Sum:Contrastive Learning for Factual-Consistent Abstractive Summarization
    Wei Liu, Huanqin Wu, Wenjing Mu, Zhen Li, Tao Chen, Dan Nie
    http://arxiv.org/abs/2112.01147v1

    • [cs.CL]Changepoint Analysis of Topic Proportions in Temporal Text Data
    Avinandan Bose, Soumendu Sundar Mukherjee
    http://arxiv.org/abs/2112.00827v1

    • [cs.CL]Context-Dependent Semantic Parsing for Temporal Relation Extraction
    Bo-Ying Su, Shang-Ling Hsu, Kuan-Yin Lai, Jane Yung-jen Hsu
    http://arxiv.org/abs/2112.00894v1

    • [cs.CL]DKPLM: Decomposable Knowledge-enhanced Pre-trained Language Model for Natural Language Understanding
    Taolin Zhang, Chengyu Wang, Nan Hu, Minghui Qiu, Chengguang Tang, Xiaofeng He, Jun Huang
    http://arxiv.org/abs/2112.01047v1

    • [cs.CL]Emotions are Subtle: Learning Sentiment Based Text Representations Using Contrastive Learning
    Ipsita Mohanty, Ankit Goyal, Alex Dotterweich
    http://arxiv.org/abs/2112.01054v1

    • [cs.CL]From Consensus to Disagreement: Multi-Teacher Distillation for Semi-Supervised Relation Extraction
    Wanli Li, Tieyun Qian
    http://arxiv.org/abs/2112.01048v1

    • [cs.CL]How not to Lie with a Benchmark: Rearranging NLP Leaderboards
    Shavrina Tatiana, Malykh Valentin
    http://arxiv.org/abs/2112.01342v1

    • [cs.CL]Iconary: A Pictionary-Based Game for Testing Multimodal Communication with Drawings and Text
    Christopher Clark, Jordi Salvador, Dustin Schwenk, Derrick Bonafilia, Mark Yatskar, Eric Kolve, Alvaro Herrasti, Jonghyun Choi, Sachin Mehta, Sam Skjonsberg, Carissa Schoenick, Aaron Sarnat, Hannaneh Hajishirzi, Aniruddha Kembhavi, Oren Etzioni, Ali Farhadi
    http://arxiv.org/abs/2112.00800v1

    • [cs.CL]Improving Controllability of Educational Question Generation by Keyword Provision
    Ying-Hong Chan, Ho-Lam Chung, Yao-Chung Fan
    http://arxiv.org/abs/2112.01012v1

    • [cs.CL]KPDrop: An Approach to Improving Absent Keyphrase Generation
    Seoyeon Park, Jishnu Ray Chowdhury, Tuhin Kundu, Cornelia Caragea
    http://arxiv.org/abs/2112.01476v1

    • [cs.CL]LOGEN: Few-shot Logical Knowledge-Conditioned Text Generation with Self-training
    Ningyu Zhang, Hongbin Ye, Jiacheng Yang, Shumin Deng, Chuanqi Tan, Mosha Chen, Songfang Huang, Fei Huang, Huajun Chen
    http://arxiv.org/abs/2112.01404v1

    • [cs.CL]ScaleVLAD: Improving Multimodal Sentiment Analysis via Multi-Scale Fusion of Locally Descriptors
    Huaishao Luo, Lei Ji, Yanyong Huang, Bin Wang, Shenggong Ji, Tianrui Li
    http://arxiv.org/abs/2112.01368v1

    • [cs.CL]Towards generating citation sentences for multiple references with intent control
    Jia-Yan Wu, Alexander Te-Wei Shieh, Shih-Ju Hsu, Yun-Nung Chen
    http://arxiv.org/abs/2112.01332v1

    • [cs.CL]Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-Sentence Dependency Graph
    Liyan Xu, Xuchao Zhang, Bo Zong, Yanchi Liu, Wei Cheng, Jingchao Ni, Haifeng Chen, Liang Zhao, Jinho D. Choi
    http://arxiv.org/abs/2112.00503v2

    • [cs.CR]ReIGNN: State Register Identification Using Graph Neural Networks for Circuit Reverse Engineering
    Subhajit Dutta Chowdhury, Kaixin Yang, Pierluigi Nuzzo
    http://arxiv.org/abs/2112.00806v1

    • [cs.CV]“Just Drive”: Colour Bias Mitigation for Semantic Segmentation in the Context of Urban Driving
    Jack Stelling, Amir Atapour-Abarghouei
    http://arxiv.org/abs/2112.01121v1

    • [cs.CV]3D-Aware Semantic-Guided Generative Model for Human Synthesis
    Jichao Zhang, Enver Sangineto, Hao Tang, Aliaksandr Siarohin, Zhun Zhong, Nicu Sebe, Wei Wang
    http://arxiv.org/abs/2112.01422v1

    • [cs.CV]3rd Place Solution for NeurIPS 2021 Shifts Challenge: Vehicle Motion Prediction
    Ching-Yu Tseng, Po-Shao Lin, Yu-Jia Liou, Kuan-Chih Huang, Winston H. Hsu
    http://arxiv.org/abs/2112.01348v1

    • [cs.CV]A Fast Knowledge Distillation Framework for Visual Recognition
    Zhiqiang Shen, Eric Xing
    http://arxiv.org/abs/2112.01528v1

    • [cs.CV]Altering Facial Expression Based on Textual Emotion
    Mohammad Imrul Jubair, Md. Masud Rana, Md. Amir Hamza, Mohsena Ashraf, Fahim Ahsan Khan, Ahnaf Tahseen Prince
    http://arxiv.org/abs/2112.01454v1

    • [cs.CV]Attention based Occlusion Removal for Hybrid Telepresence Systems
    Surabhi Gupta, Ashwath Shetty, Avinash Sharma
    http://arxiv.org/abs/2112.01098v1

    • [cs.CV]BEVT: BERT Pretraining of Video Transformers
    Rui Wang, Dongdong Chen, Zuxuan Wu, Yinpeng Chen, Xiyang Dai, Mengchen Liu, Yu-Gang Jiang, Luowei Zhou, Lu Yuan
    http://arxiv.org/abs/2112.01529v1

    • [cs.CV]Batch Normalization Tells You Which Filter is Important
    Junghun Oh, Heewon Kim, Sungyong Baik, Cheeun Hong, Kyoung Mu Lee
    http://arxiv.org/abs/2112.01155v1

    • [cs.CV]CLAWS: Contrastive Learning with hard Attention and Weak Supervision
    Jansel Herrera-Gerena, Ramakrishnan Sundareswaran, John Just, Matthew Darr, Ali Jannesari
    http://arxiv.org/abs/2112.00847v1

    • [cs.CV]CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer
    Moein Sorkhei, Yue Liu, Hossein Azizpour, Edward Azavedo, Karin Dembrower, Dimitra Ntoula, Athanasios Zouzos, Fredrik Strand, Kevin Smith
    http://arxiv.org/abs/2112.01330v1

    • [cs.CV]CloudWalker: 3D Point Cloud Learning by Random Walks for Shape Analysis
    Adi Mesika, Yizhak Ben-Shabat, Ayellet Tal
    http://arxiv.org/abs/2112.01050v1

    • [cs.CV]Co-domain Symmetry for Complex-Valued Deep Learning
    Utkarsh Singhal, Yifei Xing, Stella X. Yu
    http://arxiv.org/abs/2112.01525v1

    • [cs.CV]Consensus Graph Representation Learning for Better Grounded Image Captioning
    Wenqiao Zhang, Haochen Shi, Siliang Tang, Jun Xiao, Qiang Yu, Yueting Zhuang
    http://arxiv.org/abs/2112.00974v1

    • [cs.CV]Controllable Video Captioning with an Exemplar Sentence
    Yitian Yuan, Lin Ma, Jingwen Wang, Wenwu Zhu
    http://arxiv.org/abs/2112.01073v1

    • [cs.CV]DenseCLIP: Extract Free Dense Labels from CLIP
    Chong Zhou, Chen Change Loy, Bo Dai
    http://arxiv.org/abs/2112.01071v1

    • [cs.CV]DenseCLIP: Language-Guided Dense Prediction with Context-Aware Prompting
    Yongming Rao, Wenliang Zhao, Guangyi Chen, Yansong Tang, Zheng Zhu, Guan Huang, Jie Zhou, Jiwen Lu
    http://arxiv.org/abs/2112.01518v1

    • [cs.CV]Dimensions of Motion: Learning to Predict a Subspace of Optical Flow from a Single Image
    Richard Strong Bowen, Richard Tucker, Ramin Zabih, Noah Snavely
    http://arxiv.org/abs/2112.01502v1

    • [cs.CV]Efficient Neural Radiance Fields with Learned Depth-Guided Sampling
    Haotong Lin, Sida Peng, Zhen Xu, Hujun Bao, Xiaowei Zhou
    http://arxiv.org/abs/2112.01517v1

    • [cs.CV]Event Neural Networks
    Matthew Dutson, Mohit Gupta
    http://arxiv.org/abs/2112.00891v1

    • [cs.CV]FIBA: Frequency-Injection based Backdoor Attack in Medical Image Analysis
    Yu Feng, Benteng Ma, Jing Zhang, Shanshan Zhao, Yong Xia, Dacheng Tao
    http://arxiv.org/abs/2112.01148v1

    • [cs.CV]Fast automatic deforestation detectors and their extensions for other spatial objects
    Jesper Muren, Vilhelm Niklasson, Dmitry Otryakhin, Maxim Romashin
    http://arxiv.org/abs/2112.01063v1

    • [cs.CV]GANORCON: Are Generative Models Useful for Few-shot Segmentation?
    Oindrila Saha, Zezhou Cheng, Subhransu Maji
    http://arxiv.org/abs/2112.00854v1

    • [cs.CV]GANSeg: Learning to Segment by Unsupervised Hierarchical Image Generation
    Xingzhe He, Bastian Wandt, Helge Rhodin
    http://arxiv.org/abs/2112.01036v1

    • [cs.CV]GLAMR: Global Occlusion-Aware Human Mesh Recovery with Dynamic Cameras
    Ye Yuan, Umar Iqbal, Pavlo Molchanov, Kris Kitani, Jan Kautz
    http://arxiv.org/abs/2112.01524v1

    • [cs.CV]Generalized Closed-form Formulae for Feature-based Subpixel Alignment in Patch-based Matching
    Laurent Valentin Jospin, Farid Boussaid, Hamid Laga, Mohammed Bennamoun
    http://arxiv.org/abs/2112.00941v1

    • [cs.CV]Generating Diverse 3D Reconstructions from a Single Occluded Face Image
    Rahul Dey, Vishnu Naresh Boddeti
    http://arxiv.org/abs/2112.00879v1

    • [cs.CV]Hierarchical Neural Implicit Pose Network for Animation and Motion Retargeting
    Sourav Biswas, Kangxue Yin, Maria Shugrina, Sanja Fidler, Sameh Khamis
    http://arxiv.org/abs/2112.00958v1

    • [cs.CV]Improved Multiscale Vision Transformers for Classification and Detection
    Yanghao Li, Chao-Yuan Wu, Haoqi Fan, Karttikeya Mangalam, Bo Xiong, Jitendra Malik, Christoph Feichtenhofer
    http://arxiv.org/abs/2112.01526v1

    • [cs.CV]Inferring Prototypes for Multi-Label Few-Shot Image Classification with Word Vector Guided Attention
    Kun Yan, Chenbin Zhang, Jun Hou, Ping Wang, Zied Bouraoui, Shoaib Jameel, Steven Schockaert
    http://arxiv.org/abs/2112.01037v1

    • [cs.CV]InsCLR: Improving Instance Retrieval with Self-Supervision
    Zelu Deng, Yujie Zhong, Sheng Guo, Weilin Huang
    http://arxiv.org/abs/2112.01390v1

    • [cs.CV]Interpretable Deep Learning-Based Forensic Iris Segmentation and Recognition
    Andrey Kuehlkamp, Aidan Boyd, Adam Czajka, Kevin Bowyer, Patrick Flynn, Dennis Chute, Eric Benjamin
    http://arxiv.org/abs/2112.00849v1

    • [cs.CV]Iterative Frame-Level Representation Learning And Classification For Semi-Supervised Temporal Action Segmentation
    Dipika Singhania, Rahul Rahaman, Angela Yao
    http://arxiv.org/abs/2112.01402v1

    • [cs.CV]Learning Neural Light Fields with Ray-Space Embedding Networks
    Benjamin Attal, Jia-Bin Huang, Michael Zollhoefer, Johannes Kopf, Changil Kim
    http://arxiv.org/abs/2112.01523v1

    • [cs.CV]Learning Spatial-Temporal Graphs for Active Speaker Detection
    Sourya Roy, Kyle Min, Subarna Tripathi, Tanaya Guha, Somdeb Majumdar
    http://arxiv.org/abs/2112.01479v1

    • [cs.CV]Leveraging Human Selective Attention for Medical Image Analysis with Limited Training Data
    Yifei Huang, Xiaoxiao Li, Lijin Yang, Lin Gu, Yingying Zhu, Hirofumi Seo, Qiuming Meng, Tatsuya Harada, Yoichi Sato
    http://arxiv.org/abs/2112.01034v1

    • [cs.CV]Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks
    Biyang Liu, Huimin Yu, Yangqi Long
    http://arxiv.org/abs/2112.01011v1

    • [cs.CV]MTFNet: Mutual-Transformer Fusion Network for RGB-D Salient Object Detection
    Xixi Wang, Bo Jiang, Xiao Wang, Bin Luo
    http://arxiv.org/abs/2112.01177v1

    • [cs.CV]Machine Learning-Based Classification Algorithms for the Prediction of Coronary Heart Diseases
    Kelvin Kwakye, Emmanuel Dadzie
    http://arxiv.org/abs/2112.01503v1

    • [cs.CV]Masked-attention Mask Transformer for Universal Image Segmentation
    Bowen Cheng, Ishan Misra, Alexander G. Schwing, Alexander Kirillov, Rohit Girdhar
    http://arxiv.org/abs/2112.01527v1

    • [cs.CV]Maximum Consensus by Weighted Influences of Monotone Boolean Functions
    Erchuan Zhang, David Suter, Ruwan Tennakoon, Tat-Jun Chin, Alireza Bab-Hadiashar, Giang Truong, Syed Zulqarnain Gilani
    http://arxiv.org/abs/2112.00953v1

    • [cs.CV]MegBA: A High-Performance and Distributed Library for Large-Scale Bundle Adjustment
    Jie Ren, Wenteng Liang, Ran Yan, Luo Mai, Shiwen Liu, Xiao Liu
    http://arxiv.org/abs/2112.01349v1

    • [cs.CV]N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras
    Junho Kim, Jaehyeok Bae, Gangin Park, Young Min Kim
    http://arxiv.org/abs/2112.01041v1

    • [cs.CV]NeSF: Neural Shading Field for Image Harmonization
    Zhongyun Hu, Ntumba Elie Nsampi, Xue Wang, Qing Wang
    http://arxiv.org/abs/2112.01314v1

    • [cs.CV]Neural Point Light Fields
    Julian Ost, Issam Laradji, Alejandro Newell, Yuval Bahat, Felix Heide
    http://arxiv.org/abs/2112.01473v1

    • [cs.CV]Neural Weight Step Video Compression
    Mikolaj Czerkawski, Javier Cardona, Robert Atkinson, Craig Michie, Ivan Andonovic, Carmine Clemente, Christos Tachtatzis
    http://arxiv.org/abs/2112.01504v1

    • [cs.CV]OW-DETR: Open-world Detection Transformer
    Akshita Gupta, Sanath Narayan, K J Joseph, Salman Khan, Fahad Shahbaz Khan, Mubarak Shah
    http://arxiv.org/abs/2112.01513v1

    • [cs.CV]Object-Centric Unsupervised Image Captioning
    Zihang Meng, David Yang, Xuefei Cao, Ashish Shah, Ser-Nam Lim
    http://arxiv.org/abs/2112.00969v1

    • [cs.CV]Object-aware Monocular Depth Prediction with Instance Convolutions
    Enis Simsar, Evin Pınar Örnek, Fabian Manhardt, Helisa Dhamo, Nassir Navab, Federico Tombari
    http://arxiv.org/abs/2112.01521v1

    • [cs.CV]Object-aware Video-language Pre-training for Retrieval
    Alex Jinpeng Wang, Yixiao Ge, Guanyu Cai, Rui Yan, Xudong Lin, Ying Shan, Xiaohu Qie, Mike Zheng Shou
    http://arxiv.org/abs/2112.00656v2

    • [cs.CV]On Salience-Sensitive Sign Classification in Autonomous Vehicle Path Planning: Experimental Explorations with a Novel Dataset
    Ross Greer, Jason Isa, Nachiket Deo, Akshay Rangesh, Mohan M. Trivedi
    http://arxiv.org/abs/2112.00942v1

    • [cs.CV]Overcoming the Domain Gap in Neural Action Representations
    Semih Günel, Florian Aymanns, Sina Honari, Pavan Ramdya, Pascal Fua
    http://arxiv.org/abs/2112.01176v1

    • [cs.CV]PartImageNet: A Large, High-Quality Dataset of Parts
    Ju He, Shuo Yang, Shaokang Yang, Adam Kortylewski, Xiaoding Yuan, Jie-Neng Chen, Shuai Liu, Cheng Yang, Alan Yuille
    http://arxiv.org/abs/2112.00933v1

    • [cs.CV]Point Cloud Segmentation Using Sparse Temporal Local Attention
    Joshua Knights, Peyman Moghadam, Clinton Fookes, Sridha Sridharan
    http://arxiv.org/abs/2112.00289v2

    • [cs.CV]PreViTS: Contrastive Pretraining with Video Tracking Supervision
    Brian Chen, Ramprasaath R. Selvaraju, Shih-Fu Chang, Juan Carlos Niebles, Nikhil Naik
    http://arxiv.org/abs/2112.00804v1

    • [cs.CV]Probabilistic Approach for Road-Users Detection
    G. Melotti, W. Lu, D. Zhao, A. Asvadi, N. Gonçalves, C. Premebida
    http://arxiv.org/abs/2112.01360v1

    • [cs.CV]Putting 3D Spatially Sparse Networks on a Diet
    Junha Lee, Christopher Choy, Jaesik Park
    http://arxiv.org/abs/2112.01316v1

    • [cs.CV]Recognizing Scenes from Novel Viewpoints
    Shengyi Qian, Alexander Kirillov, Nikhila Ravi, Devendra Singh Chaplot, Justin Johnson, David F. Fouhey, Georgia Gkioxari
    http://arxiv.org/abs/2112.01520v1

    • [cs.CV]Relational Graph Learning for Grounded Video Description Generation
    Wenqiao Zhang, Xin Eric Wang, Siliang Tang, Haizhou Shi, Haocheng Shi, Jun Xiao, Yueting Zhuang, William Yang Wang
    http://arxiv.org/abs/2112.00967v1

    • [cs.CV]Routing with Self-Attention for Multimodal Capsule Networks
    Kevin Duarte, Brian Chen, Nina Shvetsova, Andrew Rouditchenko, Samuel Thomas, Alexander Liu, David Harwath, James Glass, Hilde Kuehne, Mubarak Shah
    http://arxiv.org/abs/2112.00775v1

    • [cs.CV]SCNet: A Generalized Attention-based Model for Crack Fault Segmentation
    Hrishikesh Sharma, Prakhar Pradhan, Balamuralidhar P
    http://arxiv.org/abs/2112.01426v1

    • [cs.CV]SEAL: Self-supervised Embodied Active Learning using Exploration and 3D Consistency
    Devendra Singh Chaplot, Murtaza Dalal, Saurabh Gupta, Jitendra Malik, Ruslan Salakhutdinov
    http://arxiv.org/abs/2112.01001v1

    • [cs.CV]Sample Prior Guided Robust Model Learning to Suppress Noisy Labels
    Wenkai Chen, Chuang Zhu, Yi Chen
    http://arxiv.org/abs/2112.01197v1

    • [cs.CV]Self-supervised Video Transformer
    Kanchana Ranasinghe, Muzammal Naseer, Salman Khan, Fahad Shahbaz Khan, Michael Ryoo
    http://arxiv.org/abs/2112.01514v1

    • [cs.CV]Semantic-Sparse Colorization Network for Deep Exemplar-based Colorization
    Yunpeng Bai, Chao Dong, Zenghao Chai, Andong Wang, Zhengzhuo Xu, Chun Yuan
    http://arxiv.org/abs/2112.01335v1

    • [cs.CV]Stacked Temporal Attention: Improving First-person Action Recognition by Emphasizing Discriminative Clips
    Lijin Yang, Yifei Huang, Yusuke Sugano, Yoichi Sato
    http://arxiv.org/abs/2112.01038v1

    • [cs.CV]Stronger Baseline for Person Re-Identification
    Fengliang Qi, Bo Yan, Leilei Cao, Hongbin Wang
    http://arxiv.org/abs/2112.01059v1

    • [cs.CV]StyleMesh: Style Transfer for Indoor 3D Scene Reconstructions
    Lukas Höllein, Justin Johnson, Matthias Nießner
    http://arxiv.org/abs/2112.01530v1

    • [cs.CV]SwinTrack: A Simple and Strong Baseline for Transformer Tracking
    Liting Lin, Heng Fan, Yong Xu, Haibin Ling
    http://arxiv.org/abs/2112.00995v1

    • [cs.CV]Syntax Customized Video Captioning by Imitating Exemplar Sentences
    Yitian Yuan, Lin Ma, Wenwu Zhu
    http://arxiv.org/abs/2112.01062v1

    • [cs.CV]TBN-ViT: Temporal Bilateral Network with Vision Transformer for Video Scene Parsing
    Bo Yan, Leilei Cao, Hongbin Wang
    http://arxiv.org/abs/2112.01033v1

    • [cs.CV]TCTN: A 3D-Temporal Convolutional Transformer Network for Spatiotemporal Predictive Learning
    Ziao Yang, Xiangrui Yang, Qifeng Lin
    http://arxiv.org/abs/2112.01085v1

    • [cs.CV]TISE: A Toolbox for Text-to-Image Synthesis Evaluation
    Tan M. Dinh, Rang Nguyen, Binh-Son Hua
    http://arxiv.org/abs/2112.01398v1

    • [cs.CV]Temporally Resolution Decrement: Utilizing the Shape Consistency for Higher Computational Efficiency
    Tianshu Xie, Xuan Cheng, Minghui Liu, Jiali Deng, Xiaomin Wang, Ming Liu
    http://arxiv.org/abs/2112.00954v1

    • [cs.CV]The Second Place Solution for ICCV2021 VIPriors Instance Segmentation Challenge
    Bo Yan, Fengliang Qi, Leilei Cao, Hongbin Wang
    http://arxiv.org/abs/2112.01072v1

    • [cs.CV]TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation
    Zhaoyuan Yin, Pichao Wang, Fan Wang, Xianzhe Xu, Hanling Zhang, Hao Li, Rong Jin
    http://arxiv.org/abs/2112.01515v1

    • [cs.CV]TransMEF: A Transformer-Based Multi-Exposure Image Fusion Framework using Self-Supervised Multi-Task Learning
    Linhao Qu, Shaolei Liu, Manning Wang, Zhijian Song
    http://arxiv.org/abs/2112.01030v1

    • [cs.CV]Unconstrained Face Sketch Synthesis via Perception-Adaptive Network and A New Benchmark
    Lin Nie, Lingbo Liu, Zhengtao Wu, Wenxiong Kang
    http://arxiv.org/abs/2112.01019v1

    • [cs.CV]Uni-Perceiver: Pre-training Unified Architecture for Generic Perception for Zero-shot and Few-shot Tasks
    Xizhou Zhu, Jinguo Zhu, Hao Li, Xiaoshi Wu, Xiaogang Wang, Hongsheng Li, Xiaohua Wang, Jifeng Dai
    http://arxiv.org/abs/2112.01522v1

    • [cs.CV]Using Deep Image Prior to Assist Variational Selective Segmentation Deep Learning Algorithms
    Liam Burrows, Ke Chen, Francesco Torella
    http://arxiv.org/abs/2112.00793v1

    • [cs.CV]Video Frame Interpolation without Temporal Priors
    Youjian Zhang, Chaoyue Wang, Dacheng Tao
    http://arxiv.org/abs/2112.01161v1

    • [cs.CV]Video-Text Pre-training with Learned Regions
    Rui Yan, Mike Zheng Shou, Yixiao Ge, Alex Jinpeng Wang, Xudong Lin, Guanyu Cai, Jinhui Tang
    http://arxiv.org/abs/2112.01194v1

    • [cs.CV]Vision Pair Learning: An Efficient Training Framework for Image Classification
    Bei Tong, Xiaoyuan Yu
    http://arxiv.org/abs/2112.00965v1

    • [cs.CV]Visual-Semantic Transformer for Scene Text Recognition
    Xin Tang, Yongquan Lai, Ying Liu, Yuanyuan Fu, Rui Fang
    http://arxiv.org/abs/2112.00948v1

    • [cs.CV]Zero-Shot Text-Guided Object Generation with Dream Fields
    Ajay Jain, Ben Mildenhall, Jonathan T. Barron, Pieter Abbeel, Ben Poole
    http://arxiv.org/abs/2112.01455v1

    • [cs.CY]“Vironment”: An Art of Wearable Social Distancing
    Steve Mann, Cayden Pierce, Christopher Tong, Christina Mann
    http://arxiv.org/abs/2112.00093v2

    • [cs.CY](SARS-CoV-2) COVID 19: Genomic surveillance and evaluation of the impact on the population speaker of indigenous language in Mexico
    Medel-Ramírez Carlos, Medel-López Hilario, Lara-Mérida Jennifer
    http://arxiv.org/abs/2112.01276v1

    • [cs.CY]Achieving a Data-driven Risk Assessment Methodology for Ethical AI
    Anna Felländer, Jonathan Rebane, Stefan Larsson, Mattias Wiggberg, Fredrik Heintz
    http://arxiv.org/abs/2112.01282v1

    • [cs.CY]Advancing Artificial Intelligence and Machine Learning in the U.S. Government Through Improved Public Competitions
    Ezekiel J. Maier
    http://arxiv.org/abs/2112.01275v1

    • [cs.CY]Expose Uncertainty, Instill Distrust, Avoid Explanations: Towards Ethical Guidelines for AI
    Claudio S. Pinhanez
    http://arxiv.org/abs/2112.01281v1

    • [cs.CY]Lists of Top Artists to Watch computed algorithmically
    Tomasz Imielinski
    http://arxiv.org/abs/2112.01321v1

    • [cs.CY]Models of fairness in federated learning
    Kate Donahue, Jon Kleinberg
    http://arxiv.org/abs/2112.00818v1

    • [cs.CY]Ownership and Creativity in Generative Models
    Omri Avrahami, Bar Tamir
    http://arxiv.org/abs/2112.01516v1

    • [cs.CY]Security Monitoring System Using FaceNet For Wireless Sensor Network
    Preetha S, Sheela S V
    http://arxiv.org/abs/2112.01305v1

    • [cs.CY]The Effect of COVID-19 on the Transit System in Two Regions: Japan and USA
    Ismail Arai, Samy El-Tawab, Ahmad Salman, Ahmed Elnoshokaty
    http://arxiv.org/abs/2112.01198v1

    • [cs.CY]The empirical study of e-learning post-acceptance after the spread of COVID-19: A multi-analytical approach based hybrid SEM-ANN
    Ashraf Elnagar, Imad Afyouni, Ismail Shahin, Ali Bou Nassif, Said A. Salloum
    http://arxiv.org/abs/2112.01293v1

    • [cs.DC]Grafana plugin for visualising vote based consensus mechanisms, and network P2P overlay networks
    Daniil Baldouski, Aleksandar Tošić
    http://arxiv.org/abs/2112.01082v1

    • [cs.DC]Memory-efficient array redistribution through portable collective communication
    Norman A. Rink, Adam Paszke, Dimitrios Vytiniotis, Georg Stefan Schmid
    http://arxiv.org/abs/2112.01075v1

    • [cs.DC]Simplifying heterogeneous migration between x86 and ARM machines
    Nikolaos Mavrogeorgis
    http://arxiv.org/abs/2112.01189v1

    • [cs.DL]LDA2Net: Digging under the surface of COVID-19 topics in scientific literature
    Giorgia Minello, Carlo R. M. A. Santagiustina, Massimo Warglien
    http://arxiv.org/abs/2112.01181v1

    • [cs.HC]Collaborative AI Needs Stronger Assurances Driven by Risks
    Jubril Gbolahan Adigun, Matteo Camilli, Michael Felderer, Andrea Giusti, Dominik T Matt, Anna Perini, Barbara Russo, Angelo Susi
    http://arxiv.org/abs/2112.00740v1

    • [cs.HC]On Two XAI Cultures: A Case Study of Non-technical Explanations in Deployed AI System
    Helen Jiang, Erwen Senge
    http://arxiv.org/abs/2112.01016v1

    • [cs.HC]Secure and Safety Mobile Network System for Visually Impaired People
    Shyama Kumari Arunachalam, Roopa V, Meena H B, Vijayalakshmi, T Malavika
    http://arxiv.org/abs/2112.00875v1

    • [cs.IR]ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction
    Keshav Santhanam, Omar Khattab, Jon Saad-Falcon, Christopher Potts, Matei Zaharia
    http://arxiv.org/abs/2112.01488v1

    • [cs.IR]Contrastive Cross-domain Recommendation in Matching
    Ruobing Xie, Qi Liu, Liangdong Wang, Shukai Liu, Bo Zhang, Leyu Lin
    http://arxiv.org/abs/2112.00999v1

    • [cs.IR]Learning Robust Recommender from Noisy Implicit Feedback
    Wenjie Wang, Fuli Feng, Xiangnan He, Liqiang Nie, Tat-Seng Chua
    http://arxiv.org/abs/2112.01160v1

    • [cs.IR]Local Citation Recommendation with Hierarchical-Attention Text Encoder and SciBERT-based Reranking
    Nianlong Gu, Yingqiang Gao, Richard H. R. Hahnloser
    http://arxiv.org/abs/2112.01206v1

    • [cs.IR]Tiny-NewsRec: Efficient and Effective PLM-based News Recommendation
    Yang Yu, Fangzhao Wu, Chuhan Wu, Jingwei Yi, Tao Qi, Qi Liu
    http://arxiv.org/abs/2112.00944v1

    • [cs.IR]Where the Earth is flat and 9/11 is an inside job: A comparative algorithm audit of conspiratorial information in web search results
    Aleksandra Urman, Mykola Makhortykh, Roberto Ulloa, Juhi Kulshrestha
    http://arxiv.org/abs/2112.01278v1

    • [cs.IT]Age of Information in Prioritized Random Access
    Khac-Hoang Ngo, Giuseppe Durisi, Alexandre Graell i Amat
    http://arxiv.org/abs/2112.01182v1

    • [cs.IT]Antenna Selection in Polarization Reconfigurable MIMO (PR-MIMO) Communication Systems
    Paul S. Oh, Sean S. Kwon, Andreas F. Molisch
    http://arxiv.org/abs/2112.00931v1

    • [cs.IT]Blind Super-resolution of Point Sources via Projected Gradient Descent
    Sihan Mao, Jinchi Chen
    http://arxiv.org/abs/2112.01077v1

    • [cs.IT]Channel Estimation for STAR-RIS-aided Wireless Communication
    Chenyu Wu, Changsheng You, Yuanwei Liu, Xuemai Gu, Yunlong Cai
    http://arxiv.org/abs/2112.01413v1

    • [cs.IT]IMRecoNet: Learn to Detect in Index Modulation Aided MIMO Systems with Complex Valued Neural Networks
    Chenwu Zhang, Hancheng Lu, Jinxue Liu
    http://arxiv.org/abs/2112.00910v1

    • [cs.IT]Rate-Splitting Meets Cell-Free MIMOCommunications
    André Flores, Rodrigo C. de Lamare, Kumar Vijay Mishra
    http://arxiv.org/abs/2112.00884v1

    • [cs.IT]Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface Assisted NOMA Networks
    Xinwei Yue, Jin Xie, Yuanwei Liu, Zhihao Han, Rongke Liu, Zhiguo Ding
    http://arxiv.org/abs/2112.01336v1

    • [cs.L
    59d7
    G]Differentially Private SGD with Sparse Gradients
    Junyi Zhu, Matthew Blaschko
    http://arxiv.org/abs/2112.00845v1

    • [cs.LG]A Communication-efficient Federated learning assisted by Central data: Implementation of vertical training into Horizontal Federated learning
    Shuo Wan, Jiaxun Lu, Pingyi Fan, Yunfeng Shao, Chenghui Peng, Khaled B. Letaief
    http://arxiv.org/abs/2112.01039v1

    • [cs.LG]A Discrete-event-based Simulator for Deep Learning at Edge
    Xiaoyan Liu, Zhiwei Xu, Yana Qin, Jie Tian
    http://arxiv.org/abs/2112.00952v1

    • [cs.LG]A Hybrid Science-Guided Machine Learning Approach for Modeling and Optimizing Chemical Processes
    Niket Sharma, Y. A. Liu
    http://arxiv.org/abs/2112.01475v1

    • [cs.LG]Active Learning for Domain Adaptation: An Energy-based Approach
    Binhui Xie, Longhui Yuan, Shuang Li, Chi Harold Liu, Xinjing Cheng, Guoren Wang
    http://arxiv.org/abs/2112.01406v1

    • [cs.LG]Adversarial Robustness of Deep Reinforcement Learning based Dynamic Recommender Systems
    Siyu Wang, Yuanjiang Cao, Xiaocong Chen, Lina Yao, Xianzhi Wang, Quan Z. Sheng
    http://arxiv.org/abs/2112.00973v1

    • [cs.LG]AutoGEL: An Automated Graph Neural Network with Explicit Link Information
    Zhili Wang, Shimin Di, Lei Chen
    http://arxiv.org/abs/2112.01064v1

    • [cs.LG]Bayesian Optimization over Permutation Spaces
    Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa, Dae Hyun Kim
    http://arxiv.org/abs/2112.01049v1

    • [cs.LG]CELLS: Cost-Effective Evolution in Latent Space for Goal-Directed Molecular Generation
    Zhiyuan Chen, Xiaomin Fang, Fan Wang, Xiaotian Fan, Hua Wu, Haifeng Wang
    http://arxiv.org/abs/2112.00905v1

    • [cs.LG]Computing Class Hierarchies from Classifiers
    Kai Kang, Fangzhen Lin
    http://arxiv.org/abs/2112.01187v1

    • [cs.LG]Constrained Machine Learning: The Bagel Framework
    Guillaume Perez, Sebastian Ament, Carla Gomes, Arnaud Lallouet
    http://arxiv.org/abs/2112.01088v1

    • [cs.LG]Context-Aware Online Client Selection for Hierarchical Federated Learning
    Zhe Qu, Rui Duan, Lixing Chen, Jie Xu, Zhuo Lu, Yao Liu
    http://arxiv.org/abs/2112.00925v1

    • [cs.LG]Contrastive Adaptive Propagation Graph Neural Networks for Efficient Graph Learning
    Jun Hu, Shengsheng Qian, Quan Fang, Changsheng Xu
    http://arxiv.org/abs/2112.01110v1

    • [cs.LG]Controlling Conditional Language Models with Distributional Policy Gradients
    Tomasz Korbak, Hady Elsahar, German Kruszewski, Marc Dymetman
    http://arxiv.org/abs/2112.00791v1

    • [cs.LG]Counterfactual Explanations via Latent Space Projection and Interpolation
    Brian Barr, Matthew R. Harrington, Samuel Sharpe, C. Bayan Bruss
    http://arxiv.org/abs/2112.00890v1

    • [cs.LG]DPVI: A Dynamic-Weight Particle-Based Variational Inference Framework
    Chao Zhang, Zhijian Li, Hui Qian, Xin Du
    http://arxiv.org/abs/2112.00945v1

    • [cs.LG]Data-Driven Interaction Analysis of Line Failure Cascading in Power Grid Networks
    Abdorasoul Ghasemi, Holger Kantz
    http://arxiv.org/abs/2112.01061v1

    • [cs.LG]Decomposing Representations for Deterministic Uncertainty Estimation
    Haiwen Huang, Joost van Amersfoort, Yarin Gal
    http://arxiv.org/abs/2112.00856v1

    • [cs.LG]Deep Transfer Learning: A Novel Collaborative Learning Model for Cyberattack Detection Systems in IoT Networks
    Tran Viet Khoa, Dinh Thai Hoang, Nguyen Linh Trung, Cong T. Nguyen, Tran Thi Thuy Quynh, Diep N. Nguyen, Nguyen Viet Ha, Eryk Dutkiewicz
    http://arxiv.org/abs/2112.00988v1

    • [cs.LG]Deep residential representations: Using unsupervised learning to unlock elevation data for geo-demographic prediction
    Matthew Stevenson, Christophe Mues, Cristián Bravo
    http://arxiv.org/abs/2112.01421v1

    • [cs.LG]Detecting Extratropical Cyclones of the Northern Hemisphere with Single Shot Detector
    Minjing Shi, Pengfei He, Yuli Shi
    http://arxiv.org/abs/2112.01283v1

    • [cs.LG]Differentiable Spatial Planning using Transformers
    Devendra Singh Chaplot, Deepak Pathak, Jitendra Malik
    http://arxiv.org/abs/2112.01010v1

    • [cs.LG]Editing a classifier by rewriting its prediction rules
    Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, Aleksander Madry
    http://arxiv.org/abs/2112.01008v1

    • [cs.LG]Efficient Symptom Inquiring and Diagnosis via Adaptive Alignment of Reinforcement Learning and Classification
    Hongyi Yuan, Sheng Yu
    http://arxiv.org/abs/2112.00733v1

    • [cs.LG]Embedding Decomposition for Artifacts Removal in EEG Signals
    Junjie Yu, Chenyi Li, Kexin Lou, Chen Wei, Quanying Liu
    http://arxiv.org/abs/2112.00989v1

    • [cs.LG]FedRAD: Federated Robust Adaptive Distillation
    Stefán Páll Sturluson, Samuel Trew, Luis Muñoz-González, Matei Grama, Jonathan Passerat-Palmbach, Daniel Rueckert, Amir Alansary
    http://arxiv.org/abs/2112.01405v1

    • [cs.LG]Federated Learning with Adaptive Batchnorm for Personalized Healthcare
    Yiqiang Chen, Wang Lu, Jindong Wang, Xin Qin, Tao Qin
    http://arxiv.org/abs/2112.00734v1

    • [cs.LG]Fighting Fire with Fire: Contrastive Debiasing without Bias-free Data via Generative Bias-transformation
    Yeonsung Jung, Hajin Shim, June Yong Yang, Eunho Yang
    http://arxiv.org/abs/2112.01021v1

    • [cs.LG]Flood Analytics Information System (FAIS) Version 4.00 Manual
    Vidya Samadi
    http://arxiv.org/abs/2112.01375v1

    • [cs.LG]Gaussian Mixture Variational Autoencoder with Contrastive Learning for Multi-Label Classification
    Junwen Bai, Shufeng Kong, Carla P. Gomes
    http://arxiv.org/abs/2112.00976v1

    • [cs.LG]Graph4Rec: A Universal Toolkit with Graph Neural Networks for Recommender Systems
    Weibin Li, Mingkai He, Zhengjie Huang, Xianming Wang, Shikun Feng, Weiyue Su, Yu Sun
    http://arxiv.org/abs/2112.01035v1

    • [cs.LG]Hierarchical Learning to Solve Partial Differential Equations Using Physics-Informed Neural Networks
    Jihun Han, Yoonsang Lee
    http://arxiv.org/abs/2112.01254v1

    • [cs.LG]Homotopy Based Reinforcement Learning with Maximum Entropy for Autonomous Air Combat
    Yiwen Zhu, Zhou Fang, Yuan Zheng, Wenya Wei
    http://arxiv.org/abs/2112.01328v1

    • [cs.LG]How Smart Guessing Strategies Can Yield Massive Scalability Improvements for Sparse Decision Tree Optimization
    Hayden McTavish, Chudi Zhong, Reto Achermann, Ilias Karimalis, Jacques Chen, Cynthia Rudin, Margo Seltzer
    http://arxiv.org/abs/2112.00798v1

    • [cs.LG]HyperSPNs: Compact and Expressive Probabilistic Circuits
    Andy Shih, Dorsa Sadigh, Stefano Ermon
    http://arxiv.org/abs/2112.00914v1

    • [cs.LG]Incomplete Multi-view Clustering via Cross-view Relation Transfer
    Yiming Wang, Dongxia Chang, Zhiqiang Fu, Yao Zhao
    http://arxiv.org/abs/2112.00739v1

    • [cs.LG]Inducing Causal Structure for Interpretable Neural Networks
    Atticus Geiger, Zhengxuan Wu, Hanson Lu, Josh Rozner, Elisa Kreiss, Thomas Icard, Noah D. Goodman, Christopher Potts
    http://arxiv.org/abs/2112.00826v1

    • [cs.LG]Large-Scale Data Mining of Rapid Residue Detection Assay Data From HTML and PDF Documents: Improving Data Access and Visualization for Veterinarians
    Majid Jaberi-Douraki, Soudabeh Taghian Dinani, Nuwan Indika Millagaha Gedara, Xuan Xu, Emily Richards, Fiona Maunsell, Nader Zad, Lisa Ann Tell
    http://arxiv.org/abs/2112.00962v1

    • [cs.LG]Learning Invariant Representations with Missing Data
    Mark Goldstein, Jörn-Henrik Jacobsen, Olina Chau, Adriel Saporta, Aahlad Puli, Rajesh Ranganath, Andrew C. Miller
    http://arxiv.org/abs/2112.00881v1

    • [cs.LG]Learning Optimal Predictive Checklists
    Haoran Zhang, Quaid Morris, Berk Ustun, Marzyeh Ghassemi
    http://arxiv.org/abs/2112.01020v1

    • [cs.LG]Level set learning with pseudo-reversible neural networks for nonlinear dimension reduction in function approximation
    Yuankai Teng, Zhu Wang, Lili Ju, Anthony Gruber, Guannan Zhang
    http://arxiv.org/abs/2112.01438v1

    • [cs.LG]Loss Landscape Dependent Self-Adjusting Learning Rates in Decentralized Stochastic Gradient Descent
    Wei Zhang, Mingrui Liu, Yu Feng, Xiaodong Cui, Brian Kingsbury, Yuhai Tu
    http://arxiv.org/abs/2112.01433v1

    • [cs.LG]Mixing Deep Learning and Multiple Criteria Optimization: An Application to Distributed Learning with Multiple Datasets
    Davide La Torre, Danilo Liuzzi, Marco Repetto, Matteo Rocca
    http://arxiv.org/abs/2112.01358v1

    • [cs.LG]Multi-Domain Transformer-Based Counterfactual Augmentation for Earnings Call Analysis
    Zixuan Yuan, Yada Zhu, Wei Zhang, Ziming Huang, Guangnan Ye, Hui Xiong
    http://arxiv.org/abs/2112.00963v1

    • [cs.LG]Multi-task Self-distillation for Graph-based Semi-Supervised Learning
    Yating Ren, Junzhong Ji, Lingfeng Niu, Minglong Lei
    http://arxiv.org/abs/2112.01174v1

    • [cs.LG]Neural Stochastic Dual Dynamic Programming
    Hanjun Dai, Yuan Xue, Zia Syed, Dale Schuurmans, Bo Dai
    http://arxiv.org/abs/2112.00874v1

    • [cs.LG]Newton methods based convolution neural networks using parallel processing
    Ujjwal Thakur, Anuj Sharma
    http://arxiv.org/abs/2112.01401v1

    • [cs.LG]On Large Batch Training and Sharp Minima: A Fokker-Planck Perspective
    Xiaowu Dai, Yuhua Zhu
    http://arxiv.org/abs/2112.00987v1

    • [cs.LG]Optimal regularizations for data generation with probabilistic graphical models
    Arnaud Fanthomme, F Rizzato, S Cocco, R Monasson
    http://arxiv.org/abs/2112.01292v1

    • [cs.LG]Output-weighted and relative entropy loss functions for deep learning precursors of extreme events
    Samuel Rudy, Themistoklis Sapsis
    http://arxiv.org/abs/2112.00825v1

    • [cs.LG]Personalized Federated Learning of Driver Prediction Models for Autonomous Driving
    Manabu Nakanoya, Junha Im, Hang Qiu, Sachin Katti, Marco Pavone, Sandeep Chinchali
    http://arxiv.org/abs/2112.00956v1

    • [cs.LG]ProtGNN: Towards Self-Explaining Graph Neural Networks
    Zaixi Zhang, Qi Liu, Hao Wang, Chengqiang Lu, Cheekong Lee
    http://arxiv.org/abs/2112.00911v1

    • [cs.LG]Provable Guarantees for Understanding Out-of-distribution Detection
    Peyman Morteza, Yixuan Li
    http://arxiv.org/abs/2112.00787v1

    • [cs.LG]Quantile Filtered Imitation Learning
    David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna
    http://arxiv.org/abs/2112.00950v1

    • [cs.LG]Recommending with Recommendations
    Naveen Durvasula, Franklyn Wang, Scott Duke Kominers
    http://arxiv.org/abs/2112.00979v1

    • [cs.LG]Residual Pathway Priors for Soft Equivariance Constraints
    Marc Finzi, Gregory Benton, Andrew Gordon Wilson
    http://arxiv.org/abs/2112.01388v1

    • [cs.LG]Reward-Free Attacks in Multi-Agent Reinforcement Learning
    Ted Fujimoto, Timothy Doster, Adam Attarian, Jill Brandenberger, Nathan Hodas
    http://arxiv.org/abs/2112.00940v1

    • [cs.LG]Risk-Aware Algorithms for Combinatorial Semi-Bandits
    Shaarad Ayyagari, Ambedkar Dukkipati
    http://arxiv.org/abs/2112.01141v1

    • [cs.LG]Robust Robotic Control from Pixels using Contrastive Recurrent State-Space Models
    Nitish Srivastava, Walter Talbott, Martin Bertran Lopez, Shuangfei Zhai, Josh Susskind
    http://arxiv.org/abs/2112.01163v1

    • [cs.LG]Safe Exploration for Constrained Reinforcement Learning with Provable Guarantees
    Archana Bura, Aria HasanzadeZonuzy, Dileep Kalathil, Srinivas Shakkottai, Jean-Francois Chamberland
    http://arxiv.org/abs/2112.00885v1

    • [cs.LG]Safe Reinforcement Learning for Grid Voltage Control
    Thanh Long Vu, Sayak Mukherjee, Renke Huang, Qiuhua Huang
    http://arxiv.org/abs/2112.01484v1

    • [cs.LG]Sample Complexity of Robust Reinforcement Learning with a Generative Model
    Kishan Panaganti, Dileep Kalathil
    http://arxiv.org/abs/2112.01506v1

    • [cs.LG]ShuttleNet: Position-aware Fusion of Rally Progress and Player Styles for Stroke Forecasting in Badminton
    Wei-Yao Wang, Hong-Han Shuai, Kai-Shiang Chang, Wen-Chih Peng
    http://arxiv.org/abs/2112.01044v1

    • [cs.LG]Source Free Unsupervised Graph Domain Adaptation
    Haitao Mao, Lun Du, Yujia Zheng, Qiang Fu, Zelin Li, Xu Chen, Han Shi, Dongmei Zhang
    http://arxiv.org/abs/2112.00955v1

    • [cs.LG]Stationary Diffusion State Neural Estimation for Multiview Clustering
    Chenghua Liu, Zhuolin Liao, Yixuan Ma, Kun Zhan
    http://arxiv.org/abs/2112.01334v1

    • [cs.LG]Target Propagation via Regularized Inversion
    Vincent Roulet, Zaid Harchaoui
    http://arxiv.org/abs/2112.01453v1

    • [cs.LG]The Impact of Data Distribution on Fairness and Robustness in Federated Learning
    Mustafa Safa Ozdayi, Murat Kantarcioglu
    http://arxiv.org/abs/2112.01274v1

    • [cs.LG]TinyML Platforms Benchmarking
    Anas Osman, Usman Abid, Luca Gemma, Matteo Perotto, Davide Brunelli
    http://arxiv.org/abs/2112.01319v1

    • [cs.LG]Training Efficiency and Robustness in Deep Learning
    Fartash Faghri
    http://arxiv.org/abs/2112.01423v1

    • [cs.LG]Trap of Feature Diversity in the Learning of MLPs
    Dongrui Liu, Shaobo Wang, Jie Ren, Kangrui Wang, Sheng Yin, Quanshi Zhang
    http://arxiv.org/abs/2112.00980v1

    • [cs.LG]Who will dropout from university? Academic risk prediction based on interpretable machine learning
    Shudong Yang
    http://arxiv.org/abs/2112.01079v1

    • [cs.LG]Why Calibration Error is Wrong Given Model Uncertainty: Using Posterior Predictive Checks with Deep Learning
    Achintya Gopal
    http://arxiv.org/abs/2112.01477v1

    • [cs.MA]Multi-scale simulation of COVID-19 epidemics
    Benoit Doussin, Carole Adam, Didier Georges
    http://arxiv.org/abs/2112.01167v1

    • [cs.MA]Resonating Minds — Emergent Collaboration Through Hierarchical Active Inference
    Jan Pöppel, Sebastian Kahl, Stefan Kopp
    http://arxiv.org/abs/2112.01210v1

    • [cs.MM]FNR: A Similarity and Transformer-Based Approachto Detect Multi-Modal FakeNews in Social Media
    Faeze Ghorbanpour, Maryam Ramezani, Mohammad A. Fazli, Hamid R. Rabiee
    http://arxiv.org/abs/2112.01131v1

    • [cs.NE]Adaptive Group Collaborative Artificial Bee Colony Algorithm
    Haiquan Wang, Hans-DietrichHaasis, Panpan Du, Xiaobin Xu, Menghao Su, Shengjun Wen, Wenxuan Yue, Shanshan Zhang
    http://arxiv.org/abs/2112.01215v1

    • [cs.NE]Evolving Open Complexity
    W. B. Langdon
    http://arxiv.org/abs/2112.00812v1

    • [cs.NE]Frequency Fitness Assignment: Optimization without a Bias for Good Solutions can be Efficient
    Thomas Weise, Zhize Wu, Xinlu Li, Yan Chen, Jörg Lässig
    http://arxiv.org/abs/2112.00229v2

    • [cs.NE]The (1+1)-ES Reliably Overcomes Saddle Points
    Tobias Glasmachers
    http://arxiv.org/abs/2112.00888v1

    • [cs.NE]ViF-SD2E: A Robust Weakly-Supervised Method for Neural Decoding
    Jingyi Feng, Yong Luo, Shuang Song
    http://arxiv.org/abs/2112.01261v1

    • [cs.RO]Control of over-redundant cooperative manipulation via sampled communication
    Enrica Rossi, Marco Tognon, Ruggero Carli, Antonio Franchi, Luca Schenato
    http://arxiv.org/abs/2112.01107v1

    • [cs.RO]Distributed Control for a Robotic Swarm to Pass through a Curve Virtual Tube
    Quan Quan, Yan Gao, Chenggang Bai
    http://arxiv.org/abs/2112.01006v1

    • [cs.RO]Effects of Interfaces on Human-Robot Trust: Specifying and Visualizing Physical Zones
    Marisa Hudspeth, Sogol Balali, Cindy Grimm, Ross Sowell
    http://arxiv.org/abs/2112.00779v1

    • [cs.RO]Multi-Object Grasping — Estimating the Number of Objects in a Robotic Grasp
    Tianze Chen, Adheesh Shenoy, Anzhelika Kolinko, Syed Shah, Yu Sun
    http://arxiv.org/abs/2112.01270v1

    • [cs.RO]Situation-Aware Environment Perception Using a Multi-Layer Attention Map
    Matti Henning, Johannes Müller, Fabian Gies, Michael Buchholz, Klaus Dietmayer
    http://arxiv.org/abs/2112.01126v1

    • [cs.RO]The Surprising Effectiveness of Representation Learning for Visual Imitation
    Jyothish Pari, Nur Muhammad, Shafiullah, Sridhar Pandian Arunachalam, Lerrel Pinto
    http://arxiv.org/abs/2112.01511v1

    • [cs.RO]Wish you were here: Hindsight Goal Selection for long-horizon dexterous manipulation
    Todor Davchev, Oleg Sushkov, Jean-Baptiste Regli, Stefan Schaal, Yusuf Aytar, Markus Wulfmeier, Jon Scholz
    http://arxiv.org/abs/2112.00597v2

    • [cs.SE]A Survey on Scenario-Based Testing for Automated Driving Systems in High-Fidelity Simulation
    Ziyuan Zhong, Yun Tang, Yuan Zhou, Vania de Oliveira Neves, Yang Liu, Baishakhi Ray
    http://arxiv.org/abs/2112.00964v1

    • [cs.SE]Borrowing from Similar Code: A Deep Learning NLP-Based Approach for Log Statement Automation
    Sina Gholamian, Paul A. S. Ward
    http://arxiv.org/abs/2112.01259v1

    • [cs.SE]Monolith to Microservices: Representing Application Software through Heterogeneous GNN
    Alex Mathai, Sambaran Bandyopadhyay, Utkarsh Desai, Srikanth Tamilselvam
    http://arxiv.org/abs/2112.01317v1

    • [cs.SI]A New Approach to Detect Important Members that Create the Communities in Bipartite Networks
    Ali Hojjat, Ghazaleh Haddad
    http://arxiv.org/abs/2112.01383v1

    • [cs.SI]Are Investors Biased Against Women? Analyzing How Gender Affects Startup Funding in Europe
    Michael Färber, Alexander Klein
    http://arxiv.org/abs/2112.00859v1

    • [cs.SI]Learning Large-scale Network Embedding from Representative Subgraph
    Junsheng Kong, Weizhao Li, Ben Liao, Jiezhong Qiu, Chang-Yu, Hsieh, Yi Cai, Jinhui Zhu, Shengyu Zhang
    http://arxiv.org/abs/2112.01442v1

    • [cs.SI]Perception and Attitude of Reddit Users Towards Use of Face-Masks in Controlling COVID-19
    G. N. Singh, D. Bhattacharyya, A. Bandyopadhyay
    http://arxiv.org/abs/2112.01159v1

    • [cs.SI]Reconsidering Tweets: Intervening During Tweet Creation Decreases Offensive Content
    Matthew Katsaros, Kathy Yang, Lauren Fratamico
    http://arxiv.org/abs/2112.00773v1

    • [cs.SI]Sentinel node approach to monitoring online COVID-19 misinformation
    Matthew T. Osborne, Samuel S. Malloy, Erik C. Nisbet, Robert M. Bond, Joseph H. Tien
    http://arxiv.org/abs/2112.01379v1

    • [cs.SI]Subgraph Contrastive Link Representation Learning
    Jiajun Zhou, Qi Xuan
    http://arxiv.org/abs/2112.01165v1

    • [cs.SI]The voice of few, the opinions of many: evidence of social biases in Twitter COVID-19 fake news sharing
    Piergiorgio Castioni, Giulia Andrighetto, Riccardo Gallotti, Eugenia Polizzi, Manlio De Domenico
    http://arxiv.org/abs/2112.01304v1

    • [cs.SI]Unifying Diffusion Models on Networks and Their Influence Maximisation
    Yu Tian, Renaud Lambiotte
    http://arxiv.org/abs/2112.01465v1

    • [econ.EM]Structural Sieves
    Konrad Menzel
    http://arxiv.org/abs/2112.01377v1

    • [eess.AS]A Mixture of Expert Based Deep Neural Network for Improved ASR
    Vishwanath Pratap Singh, Shakti P. Rath, Abhishek Pandey
    http://arxiv.org/abs/2112.01025v1

    • [eess.IV]CDLNet: Noise-Adaptive Convolutional Dictionary Learning Network for Blind Denoising and Demosaicing
    Nikola Janjušević, Amirhossein Kalilian-Gourtani, Yao Wang
    http://arxiv.org/abs/2112.00913v1

    • [eess.IV]DFTS2: Simulating Deep Feature Transmission Over Packet Loss Channels
    Ashiv Dhondea, Robert A. Cohen, Ivan V. Bajić
    http://arxiv.org/abs/2112.00794v1

    • [eess.IV]Deep Learning-Based Carotid Artery Vessel Wall Segmentation in Black-Blood MRI Using Anatomical Priors
    Dieuwertje Alblas, Christoph Brune, Jelmer M. Wolterink
    http://arxiv.org/abs/2112.01137v1

    • [eess.IV]Highly accelerated MR parametric mapping by undersampling the k-space and reducing the contrast number simultaneously with deep learning
    Yanjie Zhu, Haoxiang Li, Yuanyuan Liu, Muzi Guo, Guanxun Cheng, Gang Yang, Haifeng Wang, Dong Liang
    http://arxiv.org/abs/2112.00730v1

    • [eess.IV]Multi-task fusion for improving mammography screening data classification
    Maria Wimmer, Gert Sluiter, David Major, Dimitrios Lenis, Astrid Berg, Theresa Neubauer, Katja Bühler
    http://arxiv.org/abs/2112.01320v1

    • [eess.IV]Reference-guided Pseudo-Label Generation for Medical Semantic Segmentation
    Constantin Seibold, Simon Reiß, Jens Kleesiek, Rainer Stiefelhagen
    http://arxiv.org/abs/2112.00735v1

    • [eess.IV]Total-Body Low-Dose CT Image Denoising using Prior Knowledge Transfer Technique with Contrastive Regularization Mechanism
    Minghan Fu, Yanhua Duan, Zhaoping Cheng, Wenjian Qin, Ying Wang, Dong Liang, Zhanli Hu
    http://arxiv.org/abs/2112.00729v1

    • [eess.SP]Analysis of an adaptive lead weighted ResNet for multiclass classification of 12-lead ECGs
    Zhibin Zhao, Darcy Murphy, Hugh Gifford, Stefan Williams, Annie Darlington, Samuel D. Relton, Hui Fang, David C. Wong
    http://arxiv.org/abs/2112.01496v1

    • [eess.SP]Time-Series Estimation from Randomly Time-Warped Observations
    İlker Bayram
    http://arxiv.org/abs/2112.01464v1

    • [eess.SY]Youla-REN: Learning Nonlinear Feedback Policies with Robust Stability Guarantees
    Ruigang Wang, Ian R. Manchester
    http://arxiv.org/abs/2112.01253v1

    • [math.OC]Near-Optimal Lower Bounds For Convex Optimization For All Orders of Smoothness
    Ankit Garg, Robin Kothari, Praneeth Netrapalli, Suhail Sherif
    http://arxiv.org/abs/2112.01118v1

    • [math.PR]A Note on the Borel-Cantelli Lemma
    Narayanaswamy Balakrishnan, Alexei Stepanov
    http://arxiv.org/abs/2112.00741v1

    • [math.PR]Interval extropy and weighted interval extropy
    Francesco Buono, Osman Kamari, Maria Longobardi
    http://arxiv.org/abs/2112.01152v1

    • [physics.geo-ph]Joint Characterization of the Cryospheric Spectral Feature Space
    Christopher Small, Daniel Sousa
    http://arxiv.org/abs/2112.01416v1

    • [q-fin.ST]Forex Trading Volatility Prediction using NeuralNetwork Models
    Shujian Liao, Jian Chen, Hao Ni
    http://arxiv.org/abs/2112.01166v1

    • [quant-ph]Quantum advantage in learning from experiments
    Hsin-Yuan Huang, Michael Broughton, Jordan Cotler, Sitan Chen, Jerry Li, Masoud Mohseni, Hartmut Neven, Ryan Babbush, Richard Kueng, John Preskill, Jarrod R. McClean
    http://arxiv.org/abs/2112.00778v1

    • [quant-ph]Revisiting dequantization and quantum advantage in learning tasks
    Jordan Cotler, Hsin-Yuan Huang, Jarrod R. McClean
    http://arxiv.org/abs/2112.00811v1

    • [stat.AP]A note on sampling biases in the Bangladesh mask trial
    Maria Chikina, Wesley Pegden, Benjamin Recht
    http://arxiv.org/abs/2112.01296v1

    • [stat.AP]Bradley-Terry Modeling with Multiple Game Outcomes with Applications to College Hockey
    John T. Whelan, Jacob E. Klein
    http://arxiv.org/abs/2112.01267v1

    • [stat.AP]Hierarchical Forecasting of Dengue Incidence in Sri Lanka
    L. S. Madushani, Thiyanga S. Talagala
    http://arxiv.org/abs/2112.00992v1

    • [stat.AP]Hydroclimatic time series features at multiple time scales
    Georgia Papacharalampous, Hristos Tyralis, Yannis Markonis, Martin Hanel
    http://arxiv.org/abs/2112.01447v1

    • [stat.AP]Interactive Visualization of Spatial Omics Neighborhoods
    Tinghui Xu, Kris Sankaran
    http://arxiv.org/abs/2112.00902v1

    • [stat.AP]Using Ecometric Data to Explore Sources of Cross-Site Impact Variance in Multi-Site Trials
    David R. Judkins, Gabriel Durham
    http://arxiv.org/abs/2112.01338v1

    • [stat.CO]Bridge Simulation on Lie Groups and Homogeneous Spaces with Application to Parameter Estimation
    Mathias Højgaard Jensen, Lennard Hilgendorf, Sarang Joshi, Stefan Sommer
    http://arxiv.org/abs/2112.00866v1

    • [stat.ME]Diffusion Mean Estimation on the Diagonal of Product Manifolds
    Mathias Højgaard Jensen, Stefan Sommer
    http://arxiv.org/abs/2112.00871v1

    • [stat.ME]Hierarchical clustering: visualization, feature importance and model selection
    Luben M. C. Cabezas, Rafael Izbicki, Rafael B. Stern
    http://arxiv.org/abs/2112.01372v1

    • [stat.ME]Intervention treatment distributions that depend on the observed treatment process and model double robustness in causal survival analysis
    Lan Wen, Julia Marcus, Jessica Young
    http://arxiv.org/abs/2112.00807v1

    • [stat.ME]Investigating an Alternative for Estimation from a Nonprobability Sample: Matching plus Calibration
    Zhan Liu, Richard Valliant
    http://arxiv.org/abs/2112.00855v1

    • [stat.ME]Maximum Likelihood Estimation for Brownian Motion Tree Models Based on One Sample
    Michael Truell, Jan-Christian Hütter, Chandler Squires, Piotr Zwiernik, Caroline Uhler
    http://arxiv.org/abs/2112.00816v1

    • [stat.ME]On the optimization of hyperparameters in Gaussian process regression
    Sergei Manzhos, Manabu Ihara
    http://arxiv.org/abs/2112.01374v1

    • [stat.ME]On the robustness and precision of mixed-model analysis of covariance in cluster-randomized trials
    Bingkai Wang, Michael O. Harhay, Dylan S. Small, Tim P. Morris, Fan Li
    http://arxiv.org/abs/2112.00832v1

    • [stat.ME]Prior knowledge elicitation: The past, present, and future
    Petrus Mikkola, Osvaldo A. Martin, Suyog Chandramouli, Marcelo Hartmann, Oriol Abril Pla, Owen Thomas, Henri Pesonen, Jukka Corander, Aki Vehtari, Samuel Kaski, Paul-Christian Bürkner, Arto Klami
    http://arxiv.org/abs/2112.01380v1

    • [stat.ME]Sequential Spatially Balanced Sampling
    Raphaël Jauslin, Bardia Panahbehagh, Yves Tillé
    http://arxiv.org/abs/2112.01164v1

    • [stat.ME]Subgroup Analysis for Longitudinal data via Semiparametric Additive Mixed Effect Model
    Xiaolin Bo, Weiping Zhang
    http://arxiv.org/abs/2112.00453v1

    • [stat.ML]Convergence of batch Greenkhorn for Regularized Multimarginal Optimal Transport
    Vladimir Kostic, Saverio Salzo, Massimilano Pontil
    http://arxiv.org/abs/2112.00838v1

    • [stat.ML]Generalizing Off-Policy Learning under Sample Selection Bias
    Tobias Hatt, Daniel Tschernutter, Stefan Feuerriegel
    http://arxiv.org/abs/2112.01387v1

    • [stat.ML]Robust and Adaptive Temporal-Difference Learning Using An Ensemble of Gaussian Processes
    Qin Lu, Georgios B. Giannakis
    http://arxiv.org/abs/2112.00882v1