cond-mat.mtrl-sci - 材料科学
    cond-mat.stat-mech - 统计数学
    cs.AI - 人工智能
    cs.CL - 计算与语言
    cs.CV - 机器视觉与模式识别
    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.GT - 计算机科学与博弈论
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.NE - 神经与进化计算
    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
    hep-ex - 高能物理实验
    math.OC - 优化与控制
    math.PR - 概率
    math.ST - 统计理论
    physics.chem-ph -化学物理
    physics.data-an - 数据分析、 统计和概率
    q-bio.NC - 神经元与认知
    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]BIGDML: Towards Exact Machine Learning Force Fields for Materials
    • [cond-mat.stat-mech]Nonequilibrium Thermodynamics in Measuring Carbon Footprints: Disentangling Structure and Artifact in Input-Output Accounting
    • [cs.AI]Coarse-to-Fine Curriculum Learning
    • [cs.AI]Definitions of intent suitable for algorithms
    • [cs.AI]Differentiable Quality Diversity
    • [cs.AI]Exploration and preference satisfaction trade-off in reward-free learning
    • [cs.AI]Giving Commands to a Self-Driving Car: How to Deal with Uncertain Situations?
    • [cs.AI]Learning to Guide a Saturation-Based Theorem Prover
    • [cs.AI]Multi-Agent Cooperative Bidding Games for Multi-Objective Optimization in e-Commercial Sponsored Search
    • [cs.AI]North Carolina COVID-19 Agent-Based Model Framework for Hospitalization Forecasting Overview, Design Concepts, and Details Protocol
    • [cs.AI]Reconciling Rewards with Predictive State Representations
    • [cs.AI]Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond
    • [cs.AI]Towards interval uncertainty propagation control in bivariate aggregation processes and the introduction of width-limited interval-valued overlap functions
    • [cs.CL]A Falta de Pan, Buenas Son Tortas: The Efficacy of Predicted UPOS Tags for Low Resource UD Parsing
    • [cs.CL]A Modest Pareto Optimisation Analysis of Dependency Parsers in 2021
    • [cs.CL]A Unified Generative Framework for Aspect-Based Sentiment Analysis
    • [cs.CL]Adversarial Training for Machine Reading Comprehension with Virtual Embeddings
    • [cs.CL]Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection
    • [cs.CL]Attention Temperature Matters in Abstractive Summarization Distillation
    • [cs.CL]CAiRE in DialDoc21: Data Augmentation for Information-Seeking Dialogue System
    • [cs.CL]CLTR: An End-to-End, Transformer-Based System for Cell Level TableRetrieval and Table Question Answering
    • [cs.CL]Cheap and Good? Simple and Effective Data Augmentation for Low Resource Machine Reading
    • [cs.CL]Cyberbullying Detection Using Deep Neural Network from Social Media Comments in Bangla Language
    • [cs.CL]Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering
    • [cs.CL]Exploiting Language Relatedness for Low Web-Resource Language Model Adaptation: An Indic Languages Study
    • [cs.CL]Expressivity of Emergent Language is a Trade-off between Contextual Complexity and Unpredictability
    • [cs.CL]Generating Hypothetical Events for Abductive Inference
    • [cs.CL]Hyperbolic Temporal Knowledge Graph Embeddings with Relational and Time Curvatures
    • [cs.CL]Insight from NLP Analysis: COVID-19 Vaccines Sentiments on Social Media
    • [cs.CL]Interpretable agent communication from scratch(with a generic visual processor emerging on the side)
    • [cs.CL]Interpretable and Low-Resource Entity Matching via Decoupling Feature Learning from Decision Making
    • [cs.CL]Investigating Transfer Learning in Multilingual Pre-trained Language Models through Chinese Natural Language Inference
    • [cs.CL]Itihasa: A large-scale corpus for Sanskrit to English translation
    • [cs.CL]Learning compositional structures for semantic graph parsing
    • [cs.CL]Lexicon Learning for Few-Shot Neural Sequence Modeling
    • [cs.CL]Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions
    • [cs.CL]Measuring and Improving BERT’s Mathematical Abilities by Predicting the Order of Reasoning
    • [cs.CL]Meta-Learning to Compositionally Generalize
    • [cs.CL]Neural Abstractive Unsupervised Summarization of Online News Discussions
    • [cs.CL]Obtaining Better Static Word Embeddings Using Contextual Embedding Models
    • [cs.CL]One Semantic Parser to Parse Them All: Sequence to Sequence Multi-Task Learning on Semantic Parsing Datasets
    • [cs.CL]Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks
    • [cs.CL]Position Bias Mitigation: A Knowledge-Aware Graph Model for Emotion Cause Extraction
    • [cs.CL]Predicting Different Types of Subtle Toxicity in Unhealthy Online Conversations
    • [cs.CL]Question Generation for Adaptive Education
    • [cs.CL]Reading StackOverflow Encourages Cheating: Adding Question Text Improves Extractive Code Generation
    • [cs.CL]Realistic Evaluation Principles for Cross-document Coreference Resolution
    • [cs.CL]RewardsOfSum: Exploring Reinforcement Learning Rewards for Summarisation
    • [cs.CL]SIGTYP 2021 Shared Task: Robust Spoken Language Identification
    • [cs.CL]Self-supervised and Supervised Joint Training for Resource-rich Machine Translation
    • [cs.CL]Structured Reordering for Modeling Latent Alignments in Sequence Transduction
    • [cs.CL]Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality
    • [cs.CL]TIMEDIAL: Temporal Commonsense Reasoning in Dialog
    • [cs.CL]Translate, then Parse! A strong baseline for Cross-Lingual AMR Parsing
    • [cs.CL]Turing: an Accurate and Interpretable Multi-Hypothesis Cross-Domain Natural Language Database Interface
    • [cs.CL]Ultra-Fine Entity Typing with Weak Supervision from a Masked Language Model
    • [cs.CL]Unsupervised Word Segmentation from Discrete Speech Units in Low-Resource Settings
    • [cs.CL]XtremeDistilTransformers: Task Transfer for Task-agnostic Distillation
    • [cs.CV]A Synchronized Reprojection-based Model for 3D Human Pose Estimation
    • [cs.CV]Adversarial Semantic Hallucination for Domain Generalized Semantic Segmentation
    • [cs.CV]Affinity Attention Graph Neural Network for Weakly Supervised Semantic Segmentation
    • [cs.CV]An Intelligent Hybrid Model for Identity Document Classification
    • [cs.CV]Are VQA Systems RAD? Measuring Robustness to Augmented Data with Focused Interventions
    • [cs.CV]CSRNet: Cascaded Selective Resolution Network for Real-time Semantic Segmentation
    • [cs.CV]Chasing Sparsity in Vision Transformers:An End-to-End Exploration
    • [cs.CV]Contrastive Representation Learning for Hand Shape Estimation
    • [cs.CV]Conversational Fashion Image Retrieval via Multiturn Natural Language Feedback
    • [cs.CV]Cross-Domain Gradient Discrepancy Minimization for Unsupervised Domain Adaptation
    • [cs.CV]DETReg: Unsupervised Pretraining with Region Priors for Object Detection
    • [cs.CV]Data-Efficient Instance Generation from Instance Discrimination
    • [cs.CV]Demystifying Local Vision Transformer: Sparse Connectivity, Weight Sharing, and Dynamic Weight
    • [cs.CV]Design of Low-Artifact Interpolation Kernels by Means of Computer Algebra
    • [cs.CV]Discriminative Triad Matching and Reconstruction for Weakly Referring Expression Grounding
    • [cs.CV]Diverse Part Discovery: Occluded Person Re-identification with Part-Aware Transformer
    • [cs.CV]DoubleField: Bridging the Neural Surface and Radiance Fields for High-fidelity Human Rendering
    • [cs.CV]Efficient training for future video generation based on hierarchical disentangled representation of latent variables
    • [cs.CV]Few-Shot Action Localization without Knowing Boundaries
    • [cs.CV]Fully Transformer Networks for Semantic Image Segmentation
    • [cs.CV]Grapevine Winter Pruning Automation: On Potential Pruning Points Detection through 2D Plant Modeling using Grapevine Segmentation
    • [cs.CV]HPRNet: Hierarchical Point Regression for Whole-Body Human Pose Estimation
    • [cs.CV]Harnessing Unrecognizable Faces for Face Recognition
    • [cs.CV]Hierarchical Lovász Embeddings for Proposal-free Panoptic Segmentation
    • [cs.CV]Highly accurate digital traffic recording as a basis for future mobility research: Methods and concepts of the research project HDV-Mess
    • [cs.CV]How to Design a Three-Stage Architecture for Audio-Visual Active Speaker Detection in the Wild
    • [cs.CV]Image Deformation Estimation via Multi-Objective Optimization
    • [cs.CV]Image2Point: 3D Point-Cloud Understanding with Pretrained 2D ConvNets
    • [cs.CV]Interpreting Deep Learning based Cerebral Palsy Prediction with Channel Attention
    • [cs.CV]Learning by Distillation: A Self-Supervised Learning Framework for Optical Flow Estimation
    • [cs.CV]Left Ventricle Contouring in Cardiac Images Based on Deep Reinforcement Learning
    • [cs.CV]LipSync3D: Data-Efficient Learning of Personalized 3D Talking Faces from Video using Pose and Lighting Normalization
    • [cs.CV]LocalTrans: A Multiscale Local Transformer Network for Cross-Resolution Homography Estimation
    • [cs.CV]Low-Rank Subspaces in GANs
    • [cs.CV]MViT: Mask Vision Transformer for Facial Expression Recognition in the wild
    • [cs.CV]MoCo-Flow: Neural Motion Consensus Flow for Dynamic Humans in Stationary Monocular Cameras
    • [cs.CV]Multi-dataset Pretraining: A Unified Model for Semantic Segmentation
    • [cs.CV]Multi-frame sequence generator of 4D human body motion
    • [cs.CV]Multi-task Transformation Learning for Robust Out-of-Distribution Detection
    • [cs.CV]Novel View Video Prediction Using a Dual Representation
    • [cs.CV]On Improving Adversarial Transferability of Vision Transformers
    • [cs.CV]On the relation between statistical learning and perceptual distances
    • [cs.CV]On the role of feedback in visual processing: a predictive coding perspective
    • [cs.CV]On the use of automatically generated synthetic image datasets for benchmarking face recognition
    • [cs.CV]Person Re-Identification with a Locally Aware Transformer
    • [cs.CV]Progressive Multi-scale Fusion Network for RGB-D Salient Object Detection
    • [cs.CV]Progressive Spatio-Temporal Bilinear Network with Monte Carlo Dropout for Landmark-based Facial Expression Recognition with Uncertainty Estimation
    • [cs.CV]RobustNav: Towards Benchmarking Robustness in Embodied Navigation
    • [cs.CV]SDGMNet: Statistic-based Dynamic Gradient Modulation for Local Descriptor Learning
    • [cs.CV]Salvage of Supervision in Weakly Supervised Detection
    • [cs.CV]Scaling Vision Transformers
    • [cs.CV]Segmentation and ABCD rule extraction for skin tumors classification
    • [cs.CV]Self-Supervised Structure-from-Motion through Tightly-Coupled Depth and Egomotion Networks
    • [cs.CV]Semantically Controllable Scene Generation with Guidance of Explicit Knowledge
    • [cs.CV]Simulated Adversarial Testing of Face Recognition Models
    • [cs.CV]SpaceMeshLab: Spatial Context Memoization and Meshgrid Atrous Convolution Consensus for Semantic Segmentation
    • [cs.CV]Subject-Independent Brain-Computer Interface for Decoding High-Level Visual Imagery Tasks
    • [cs.CV]SynthRef: Generation of Synthetic Referring Expressions for Object Segmentation
    • [cs.CV]Task-Generic Hierarchical Human Motion Prior using VAEs
    • [cs.CV]Variational AutoEncoder for Reference based Image Super-Resolution
    • [cs.CV]Weakly Supervised Volumetric Image Segmentation with Deformed Templates
    • [cs.CV]White Paper Assistance: A Step Forward Beyond the Shortcut Learning
    • [cs.DB]A highly scalable repository of waveform and vital signs data from bedside monitoring devices
    • [cs.DC]Assessing Open Interfaces and Protocols of PLCs for Computation Offloading at Field Level
    • [cs.DC]Asynchronous Distributed Optimization with Redundancy in Cost Functions
    • [cs.DC]CloudChain: A Cloud Blockchain Using Shared Memory Consensus and RDMA
    • [cs.DC]GearV: A Two-Gear Hypervisor for Mixed-Criticality IoT Systems
    • [cs.DC]Launchpad: A Programming Model for Distributed Machine Learning Research
    • [cs.DC]Near-Optimal Dispersion on Arbitrary Anonymous Graphs
    • [cs.DC]PAIO: A Software-Defined Storage Data Plane Framework
    • [cs.DL]ConSTR: A Contextual Search Term Recommender
    • [cs.DS]Low-Congestion Shortcuts in Constant Diameter Graphs
    • [cs.DS]Sketch-Based Streaming Anomaly Detection in Dynamic Graphs
    • [cs.GT]Improving Social Welfare While Preserving Autonomy via a Pareto Mediator
    • [cs.IR]Defining definition: a Text mining Approach to Define Innovative Technological Fields
    • [cs.IR]Exploring Periodicity and Interactivity in Multi-Interest Framework for Sequential Recommendation
    • [cs.IR]HieRec: Hierarchical User Interest Modeling for Personalized News Recommendation
    • [cs.IR]MindReader: Recommendation over Knowledge Graph Entities with Explicit User Ratings
    • [cs.IR]Optimization of Service Addition in Multilevel Index Model for Edge Computing
    • [cs.IR]Review Polarity-wise Recommender
    • [cs.IT]A Perspective on Time towards Wireless 6G
    • [cs.IT]A Sequence Selection Bound for the Capacity of the Nonlinear Fiber Channel
    • [cs.IT]Contention-based Grant-free Transmission with Extremely Sparse Orthogonal Pilot Scheme
    • [cs.IT]Dilated Convolution based CSI Feedback Compression for Massive MIMO Systems
    • [cs.IT]Low-complexity Voronoi shaping for the Gaussian channel
    • [cs.IT]Modeling Uplink Coverage Performance in Hybrid Satellite-Terrestrial Networks
    • [cs.IT]On the Linear Capacity of Conditional Disclosure of Secrets
    • [cs.IT]On the Outage Capacity of the Massive MIMO Diversity Channel
    • [cs.IT]Optimized Rate-Profiling for PAC Codes
    • [cs.IT]Optimizing a Binary Intelligent Reflecting Surface for OFDM Communications under Mutual Coupling
    • [cs.IT]Outage Performance of Multi-UAV Relaying-based Imperfect Hardware Hybrid Satellite-Terrestrial Networks
    • [cs.IT]Principal Bit Analysis: Autoencoding with Schur-Concave Loss
    • [cs.IT]Private Multi-Group Aggregation
    • [cs.IT]Proof methods for robust low-rank matrix recovery
    • [cs.LG]A Deep Value-network Based Approach for Multi-Driver Order Dispatching
    • [cs.LG]A Survey of Transformers
    • [cs.LG]A critical look at the current train/test split in machine learning
    • [cs.LG]A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs
    • [cs.LG]Adaptive Machine Unlearning
    • [cs.LG]Amortized Generation of Sequential Counterfactual Explanations for Black-box Models
    • [cs.LG]Automatic Generation of Machine Learning Synthetic Data Using ROS
    • [cs.LG]Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future
    • [cs.LG]Breaking the Limits of Message Passing Graph Neural Networks
    • [cs.LG]Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks
    • [cs.LG]Chow-Liu++: Optimal Prediction-Centric Learning of Tree Ising Models
    • [cs.LG]Closed-Form Analytical Results for Maximum Entropy Reinforcement Learning
    • [cs.LG]Cooperative Stochastic Multi-agent Multi-armed Bandits Robust to Adversarial Corruptions
    • [cs.LG]Coresets for Classification — Simplified and Strengthened
    • [cs.LG]Correcting Momentum in Temporal Difference Learning
    • [cs.LG]Deep Learning Statistical Arbitrage
    • [cs.LG]Deep Proxy Causal Learning and its Application to Confounded Bandit Policy Evaluation
    • [cs.LG]Detecting Anomalous Event Sequences with Temporal Point Processes
    • [cs.LG]Differentiable Multiple Shooting Layers
    • [cs.LG]Dynamic Sparse Training for Deep Reinforcement Learning
    • [cs.LG]Efficient Online Learning for Dynamic k-Clustering
    • [cs.LG]Enhancing Robustness of Neural Networks through Fourier Stabilization
    • [cs.LG]Evaluating Meta-Feature Selection for the Algorithm Recommendation Problem
    • [cs.LG]FEAR: A Simple Lightweight Method to Rank Architectures
    • [cs.LG]Fast Federated Learning in the Presence of Arbitrary Device Unavailability
    • [cs.LG]Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing
    • [cs.LG]Fine-grained Out-of-Distribution Detection with Mixup Outlier Exposure
    • [cs.LG]Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation
    • [cs.LG]Generative Flows with Invertible Attentions
    • [cs.LG]Graph-MLP: Node Classification without Message Passing in Graph
    • [cs.LG]Hash Layers For Large Sparse Models
    • [cs.LG]Householder-Absolute Neural Layers For High Variability and Deep Trainability
    • [cs.LG]Hybrid Method Based on NARX models and Machine Learning for Pattern Recognition
    • [cs.LG]Incentive Mechanism for Privacy-Preserving Federated Learning
    • [cs.LG]Incorporating NODE with Pre-trained Neural Differential Operator for Learning Dynamics
    • [cs.LG]Interactive Label Cleaning with Example-based Explanations
    • [cs.LG]LEADS: Learning Dynamical Systems that Generalize Across Environments
    • [cs.LG]LaplaceNet: A Hybrid Energy-Neural Model for Deep Semi-Supervised Classification
    • [cs.LG]Learning Markov State Abstractions for Deep Reinforcement Learning
    • [cs.LG]Learning from Multiple Noisy Partial Labelers
    • [cs.LG]Linear Convergence of Entropy-Regularized Natural Policy Gradient with Linear Function Approximation
    • [cs.LG]Manifold Topology Divergence: a Framework for Comparing Data Manifolds
    • [cs.LG]Meta Learning for Knowledge Distillation
    • [cs.LG]Muddling Label Regularization: Deep Learning for Tabular Datasets
    • [cs.LG]Multi-output Gaussian Processes for Uncertainty-aware Recommender Systems
    • [cs.LG]Neural Hybrid Automata: Learning Dynamics with Multiple Modes and Stochastic Transitions
    • [cs.LG]Nonsmooth Implicit Differentiation for Machine Learning and Optimization
    • [cs.LG]Offline Policy Comparison under Limited Historical Agent-Environment Interactions
    • [cs.LG]Parameter Inference with Bifurcation Diagrams
    • [cs.LG]PlayVirtual: Augmenting Cycle-Consistent Virtual Trajectories for Reinforcement Learning
    • [cs.LG]Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss
    • [cs.LG]Provably Robust Detection of Out-of-distribution Data (almost) for free
    • [cs.LG]RECOWNs: Probabilistic Circuits for Trustworthy Time Series Forecasting
    • [cs.LG]Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization
    • [cs.LG]Rethinking Graph Transformers with Spectral Attention
    • [cs.LG]Robust Generalization despite Distribution Shift via Minimum Discriminating Information
    • [cs.LG]Self-supervised Graph-level Representation Learning with Local and Global Structure
    • [cs.LG]Stability and Generalization of Bilevel Programming in Hyperparameter Optimization
    • [cs.LG]Staircase Attention for Recurrent Processing of Sequences
    • [cs.LG]Supervised Machine Learning with Plausible Deniability
    • [cs.LG]The Fast Kernel Transform
    • [cs.LG]The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation
    • [cs.LG]The Randomness of Input Data Spaces is an A Priori Predictor for Generalization
    • [cs.LG]The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition
    • [cs.LG]There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning
    • [cs.LG]Time-series Imputation of Temporally-occluded Multiagent Trajectories
    • [cs.LG]Towards Practical Credit Assignment for Deep Reinforcement Learning
    • [cs.LG]Towards a Theoretical Framework of Out-of-Distribution Generalization
    • [cs.LG]Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning
    • [cs.LG]Understanding (Generalized) Label Smoothing whenLearning with Noisy Labels
    • [cs.LG]What Data Augmentation Do We Need for Deep-Learning-Based Finance?
    • [cs.LG]What Makes Multimodal Learning Better than Single (Provably)
    • [cs.LG]What training reveals about neural network complexity
    • [cs.LG]When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting
    • [cs.NE]GSGP-CUDA — a CUDA framework for Geometric Semantic Genetic Programming
    • [cs.NE]JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design
    • [cs.RO]A novel partially-decoupled translational parallel manipulator with symbolic kinematics, singularity identification and workspace determination
    • [cs.RO]Acoustic Power for Swarms of Microscopic Robots
    • [cs.RO]Efficient Sampling in POMDPs with Lipschitz Bandits for Motion Planning in Continuous Spaces
    • [cs.RO]Game-Theoretic Model Predictive Control with Data-Driven Identification of Vehicle Model for Head-to-Head Autonomous Racing
    • [cs.RO]H-ModQuad: Modular Multi-Rotors with 4, 5, and 6 Controllable DOF
    • [cs.RO]Learning Riemannian Manifolds for Geodesic Motion Skills
    • [cs.RO]Learning to Detect Multi-Modal Grasps for Dexterous Grasping in Dense Clutter
    • [cs.RO]Model Predictive Robot-Environment Interaction Control for Mobile Manipulation Tasks
    • [cs.RO]Planning Multimodal Exploratory Actions for Online Robot Attribute Learning
    • [cs.RO]Property-Aware Robot Object Manipulation: a Generative Approach
    • [cs.RO]Residual Feedback Learning for Contact-Rich Manipulation Tasks with Uncertainty
    • [cs.RO]Risk Ranked Recall: Collision Safety Metric for Object Detection Systems in Autonomous Vehicles
    • [cs.RO]Safe Deep Q-Network for Autonomous Vehicles at Unsignalized Intersection
    • [cs.RO]XIRL: Cross-embodiment Inverse Reinforcement Learning
    • [cs.SD]Broadcasted Residual Learning for Efficient Keyword Spotting
    • [cs.SD]Efficient Speech Emotion Recognition Using Multi-Scale CNN and Attention
    • [cs.SD]NWT: Towards natural audio-to-video generation with representation learning
    • [cs.SD]PILOT: Introducing Transformers for Probabilistic Sound Event Localization
    • [cs.SD]Raw Waveform Encoder with Multi-Scale Globally Attentive Locally Recurrent Networks for End-to-End Speech Recognition
    • [cs.SE]How to Bake Quantum into Your Pet Petri Nets and Have Your Net Theory Too
    • [cs.SI]Designing Toxic Content Classification for a Diversity of Perspectives
    • [cs.SI]News consumption and social media regulations policy
    • [cs.SI]Principled Hyperedge Prediction with Structural Spectral Features and Neural Networks
    • [cs.SI]Surveillance of COVID-19 Pandemic using Social Media: A Reddit Study in North Carolina
    • [econ.EM]Testing Monotonicity of Mean Potential Outcomes in a Continuous Treatment
    • [eess.AS]Description and Discussion on DCASE 2021 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring under Domain Shifted Conditions
    • [eess.IV]AutoPtosis
    • [eess.IV]EnMcGAN: Adversarial Ensemble Learning for 3D Complete Renal Structures Segmentation
    • [eess.IV]Generative adversarial network with object detector discriminator for enhanced defect detection on ultrasonic B-scans
    • [eess.IV]PolypGen: A multi-center polyp detection and segmentation dataset for generalisability assessment
    • [hep-ex]SPANet: Generalized Permutationless Set Assignment for Particle Physics using Symmetry Preserving Attention
    • [math.OC]Efficient solution method based on inverse dynamics for optimal control problems of rigid body systems
    • [math.OC]Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks
    • [math.OC]Optimized Data Rate Allocation for Dynamic Sensor Fusion over Resource Constrained Communication Networks
    • [math.OC]Unbalanced Optimal Transport through Non-negative Penalized Linear Regression
    • [math.OC]Using a New Nonlinear Gradient Method for Solving Large Scale Convex Optimization Problems with an Application on Arabic Medical Text
    • [math.PR]Markov Chains Generated by Convolutions of Orthogonality Measures
    • [math.PR]Maximum likelihood estimation for sub-fractional Vasicek model
    • [math.ST]Bridge Simulation and Metric Estimation on Lie Groups
    • [math.ST]Minimax and adaptive tests for detecting abrupt and possibly transitory changes in a Poisson process
    • [math.ST]Process of the slope components of 今日学术视野(2021.6.10) - 图1-regression quantile
    • [physics.chem-ph]Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations
    • [physics.data-an]Granger causality in the frequency domain: derivation and applications
    • [q-bio.NC]Credit Assignment Through Broadcasting a Global Error Vector
    • [q-bio.NC]Object Based Attention Through Internal Gating
    • [quant-ph]Encoding-dependent generalization bounds for parametrized quantum circuits
    • [quant-ph]NISQ Algorithm for Semidefinite Programming
    • [stat.AP]Scalar on time-by-distribution regression and its application for modelling associations between daily-living physical activity and cognitive functions in Alzheimer’s Disease
    • [stat.AP]Sensitivity analysis for random measurement error using regression calibration and simulation-extrapolation
    • [stat.ME]A Unified Approach to Robust Inference for Genetic Covariance
    • [stat.ME]A likelihood based sensitivity analysis for publication bias on summary ROC in meta-analysis of diagnostic test accuracy
    • [stat.ME]Clustering with missing data: which imputation model for which cluster analysis method?
    • [stat.ME]Context-Specific Causal Discovery for Categorical Data Using Staged Trees
    • [stat.ME]Do forecasts of bankruptcy cause bankruptcy? A machine learning sensitivity analysis
    • [stat.ME]Efficient Estimation For The Joint Model of Survival and Longitudinal Data
    • [stat.ME]Inference for Network Regression Models with Community Structure
    • [stat.ME]Methodological considerations for estimating policy effects in the context of co-occurring policies
    • [stat.ME]Searching for consistent associations with a multi-environment knockoff filter
    • [stat.ME]Singhing with Confidence: Visualising the Performance of Confidence Structures
    • [stat.ML]Adaptive transfer learning
    • [stat.ML]Batch Normalization Orthogonalizes Representations in Deep Random Networks
    • [stat.ML]Conditional Deep Inverse Rosenblatt Transports
    • [stat.ML]Decentralized Learning in Online Queuing Systems
    • [stat.ML]Intrinsic Dimension Estimation
    • [stat.ML]Seismic Inverse Modeling Method based on Generative Adversarial Network
    • [stat.ML]Targeted Active Learning for Bayesian Decision-Making
    • [stat.ML]The Future is Log-Gaussian: ResNets and Their Infinite-Depth-and-Width Limit at Initialization
    • [stat.ML]Weighted Sparse Subspace Representation: A Unified Framework for Subspace Clustering, Constrained Clustering, and Active Learning

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

    • [cond-mat.mtrl-sci]BIGDML: Towards Exact Machine Learning Force Fields for Materials
    Huziel E. Sauceda, Luis E. Gálvez-González, Stefan Chmiela, Lauro Oliver Paz-Borbón, Klaus-Robert Müller, Alexandre Tkatchenko
    http://arxiv.org/abs/2106.04229v1

    • [cond-mat.stat-mech]Nonequilibrium Thermodynamics in Measuring Carbon Footprints: Disentangling Structure and Artifact in Input-Output Accounting
    Samuel P. Loomis, Mark Cooper, James P. Crutchfield
    http://arxiv.org/abs/2106.03948v1

    • [cs.AI]Coarse-to-Fine Curriculum Learning
    Otilia Stretcu, Emmanouil Antonios Platanios, Tom M. Mitchell, Barnabás Póczos
    http://arxiv.org/abs/2106.04072v1

    • [cs.AI]Definitions of intent suitable for algorithms
    Hal Ashton
    http://arxiv.org/abs/2106.04235v1

    • [cs.AI]Differentiable Quality Diversity
    Matthew C. Fontaine, Stefanos Nikolaidis
    http://arxiv.org/abs/2106.03894v1

    • [cs.AI]Exploration and preference satisfaction trade-off in reward-free learning
    Noor Sajid, Panagiotis Tigas, Alexey Zakharov, Zafeirios Fountas, Karl Friston
    http://arxiv.org/abs/2106.04316v1

    • [cs.AI]Giving Commands to a Self-Driving Car: How to Deal with Uncertain Situations?
    Thierry Deruyttere, Victor Milewski, Marie-Francine Moens
    http://arxiv.org/abs/2106.04232v1

    • [cs.AI]Learning to Guide a Saturation-Based Theorem Prover
    Ibrahim Abdelaziz, Maxwell Crouse, Bassem Makni, Vernon Austil, Cristina Cornelio, Shajith Ikbal, Pavan Kapanipathi, Ndivhuwo Makondo, Kavitha Srinivas, Michael Witbrock, Achille Fokoue
    http://arxiv.org/abs/2106.03906v1

    • [cs.AI]Multi-Agent Cooperative Bidding Games for Multi-Objective Optimization in e-Commercial Sponsored Search
    Ziyu Guan, Hongchang Wu, Qingyu Cao, Hao Liu, Wei Zhao, Sheng Li, Cai Xu, Guang Qiu, Jian Xu, Bo Zheng
    http://arxiv.org/abs/2106.04075v1

    • [cs.AI]North Carolina COVID-19 Agent-Based Model Framework for Hospitalization Forecasting Overview, Design Concepts, and Details Protocol
    Kasey Jones, Emily Hadley, Sandy Preiss, Caroline Kery, Peter Baumgartner, Marie Stoner, Sarah Rhea
    http://arxiv.org/abs/2106.04461v1

    • [cs.AI]Reconciling Rewards with Predictive State Representations
    Andrea Baisero, Christopher Amato
    http://arxiv.org/abs/2106.03926v1

    • [cs.AI]Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond
    Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik
    http://arxiv.org/abs/2106.04033v1

    • [cs.AI]Towards interval uncertainty propagation control in bivariate aggregation processes and the introduction of width-limited interval-valued overlap functions
    Tiago da Cruz Asmus, Graçaliz Pereira Dimuro, Benjamín Bedregal, José Antonio Sanz, Radko Mesiar, Humberto Bustince
    http://arxiv.org/abs/2106.04233v1

    • [cs.CL]A Falta de Pan, Buenas Son Tortas: The Efficacy of Predicted UPOS Tags for Low Resource UD Parsing
    Mark Anderson, Mathieu Dehouck, Carlos Gómez Rodríguez
    http://arxiv.org/abs/2106.04222v1

    • [cs.CL]A Modest Pareto Optimisation Analysis of Dependency Parsers in 2021
    Mar Anderson, Carlos Gómez Rodríguez
    http://arxiv.org/abs/2106.04216v1

    • [cs.CL]A Unified Generative Framework for Aspect-Based Sentiment Analysis
    Hang Yan, Junqi Dai, Tuo ji, Xipeng Qiu, Zheng Zhang
    http://arxiv.org/abs/2106.04300v1

    • [cs.CL]Adversarial Training for Machine Reading Comprehension with Virtual Embeddings
    Ziqing Yang, Yiming Cui, Chenglei Si, Wanxiang Che, Ting Liu, Shijin Wang, Guoping Hu
    http://arxiv.org/abs/2106.04437v1

    • [cs.CL]Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection
    Jian-Guo Zhang, Kazuma Hashimoto, Yao Wan, Ye Liu, Caiming Xiong, Philip S. Yu
    http://arxiv.org/abs/2106.04564v1

    • [cs.CL]Attention Temperature Matters in Abstractive Summarization Distillation
    Shengqiang Zhang, Xingxing Zhang, Hangbo Bao, Furu Wei
    http://arxiv.org/abs/2106.03441v2

    • [cs.CL]CAiRE in DialDoc21: Data Augmentation for Information-Seeking Dialogue System
    Etsuko Ishii, Yan Xu, Genta Indra Winata, Zhaojiang Lin, Andrea Madotto, Zihan Liu, Peng Xu, Pascale Fung
    http://arxiv.org/abs/2106.03530v2

    • [cs.CL]CLTR: An End-to-End, Transformer-Based System for Cell Level TableRetrieval and Table Question Answering
    Feifei Pan, Mustafa Canim, Michael Glass, Alfio Gliozzo, Peter Fox
    http://arxiv.org/abs/2106.04441v1

    • [cs.CL]Cheap and Good? Simple and Effective Data Augmentation for Low Resource Machine Reading
    Hoang Van, Vikas Yadav, Mihai Surdeanu
    http://arxiv.org/abs/2106.04134v1

    • [cs.CL]Cyberbullying Detection Using Deep Neural Network from Social Media Comments in Bangla Language
    Md Faisal Ahmed, Zalish Mahmud, Zarin Tasnim Biash, Ahmed Ann Noor Ryen, Arman Hossain, Faisal Bin Ashraf
    http://arxiv.org/abs/2106.04506v1

    • [cs.CL]Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering
    Aditya Gupta, Jiacheng Xu, Shyam Upadhyay, Diyi Yang, Manaal Faruqui
    http://arxiv.org/abs/2106.04016v1

    • [cs.CL]Exploiting Language Relatedness for Low Web-Resource Language Model Adaptation: An Indic Languages Study
    Yash Khemchandani, Sarvesh Mehtani, Vaidehi Patil, Abhijeet Awasthi, Partha Talukdar, Sunita Sarawagi
    http://arxiv.org/abs/2106.03958v1

    • [cs.CL]Expressivity of Emergent Language is a Trade-off between Contextual Complexity and Unpredictability
    Shangmin Guo, Yi Ren, Kory Mathewson, Simon Kirby, Stefano V. Albrecht, Kenny Smith
    http://arxiv.org/abs/2106.03982v1

    • [cs.CL]Generating Hypothetical Events for Abductive Inference
    Debjit Paul, Anette Frank
    http://arxiv.org/abs/2106.03973v1

    • [cs.CL]Hyperbolic Temporal Knowledge Graph Embeddings with Relational and Time Curvatures
    Sebastien Montella, Lina Rojas-Barahona, Johannes Heinecke
    http://arxiv.org/abs/2106.04311v1

    • [cs.CL]Insight from NLP Analysis: COVID-19 Vaccines Sentiments on Social Media
    Tao Na, Wei Cheng, Dongming Li, Wanyu Lu, Hongjiang Li
    http://arxiv.org/abs/2106.04081v1

    • [cs.CL]Interpretable agent communication from scratch(with a generic visual processor emerging on the side)
    Roberto Dessì, Eugene Kharitonov, Marco Baroni
    http://arxiv.org/abs/2106.04258v1

    • [cs.CL]Interpretable and Low-Resource Entity Matching via Decoupling Feature Learning from Decision Making
    Zijun Yao, Chengjiang Li, Tiansi Dong, Xin Lv, Jifan Yu, Lei Hou, Juanzi Li, Yichi Zhang, Zelin Dai
    http://arxiv.org/abs/2106.04174v1

    • [cs.CL]Investigating Transfer Learning in Multilingual Pre-trained Language Models through Chinese Natural Language Inference
    Hai Hu, He Zhou, Zuoyu Tian, Yiwen Zhang, Yina Ma, Yanting Li, Yixin Nie, Kyle Richardson
    http://arxiv.org/abs/2106.03983v1

    • [cs.CL]Itihasa: A large-scale corpus for Sanskrit to English translation
    Rahul Aralikatte, Miryam de Lhoneux, Anoop Kunchukuttan, Anders Søgaard
    http://arxiv.org/abs/2106.03269v2

    • [cs.CL]Learning compositional structures for semantic graph parsing
    Jonas Groschwitz, Meaghan Fowlie, Alexander Koller
    http://arxiv.org/abs/2106.04398v1

    • [cs.CL]Lexicon Learning for Few-Shot Neural Sequence Modeling
    Ekin Akyürek, Jacob Andreas
    http://arxiv.org/abs/2106.03993v1

    • [cs.CL]Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions
    Dorottya Demszky, Jing Liu, Zid Mancenido, Julie Cohen, Heather Hill, Dan Jurafsky, Tatsunori Hashimoto
    http://arxiv.org/abs/2106.03873v1

    • [cs.CL]Measuring and Improving BERT’s Mathematical Abilities by Predicting the Order of Reasoning
    Piotr Piękos, Henryk Michalewski, Mateusz Malinowski
    http://arxiv.org/abs/2106.03921v1

    • [cs.CL]Meta-Learning to Compositionally Generalize
    Henry Conklin, Bailin Wang, Kenny Smith, Ivan Titov
    http://arxiv.org/abs/2106.04252v1

    • [cs.CL]Neural Abstractive Unsupervised Summarization of Online News Discussions
    Ignacio Tampe Palma, Marcelo Mendoza, Evangelos Milios
    http://arxiv.org/abs/2106.03953v1

    • [cs.CL]Obtaining Better Static Word Embeddings Using Contextual Embedding Models
    Prakhar Gupta, Martin Jaggi
    http://arxiv.org/abs/2106.04302v1

    • [cs.CL]One Semantic Parser to Parse Them All: Sequence to Sequence Multi-Task Learning on Semantic Parsing Datasets
    Marco Damonte, Emilio Monti
    http://arxiv.org/abs/2106.04476v1

    • [cs.CL]Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks
    Rabeeh Karimi Mahabadi, Sebastian Ruder, Mostafa Dehghani, James Henderson
    http://arxiv.org/abs/2106.04489v1

    • [cs.CL]Position Bias Mitigation: A Knowledge-Aware Graph Model for Emotion Cause Extraction
    Hanqi Yan, Lin Gui, Gabriele Pergola, Yulan He
    http://arxiv.org/abs/2106.03518v2

    • [cs.CL]Predicting Different Types of Subtle Toxicity in Unhealthy Online Conversations
    Shlok Gilda, Mirela Silva, Luiz Giovanini, Daniela Oliveira
    http://arxiv.org/abs/2106.03952v1

    • [cs.CL]Question Generation for Adaptive Education
    Megha Srivastava, Noah Goodman
    http://arxiv.org/abs/2106.04262v1

    • [cs.CL]Reading StackOverflow Encourages Cheating: Adding Question Text Improves Extractive Code Generation
    Gabriel Orlanski, Alex Gittens
    http://arxiv.org/abs/2106.04447v1

    • [cs.CL]Realistic Evaluation Principles for Cross-document Coreference Resolution
    Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan
    http://arxiv.org/abs/2106.04192v1

    • [cs.CL]RewardsOfSum: Exploring Reinforcement Learning Rewards for Summarisation
    Jacob Parnell, Inigo Jauregi Unanue, Massimo Piccardi
    http://arxiv.org/abs/2106.04080v1

    • [cs.CL]SIGTYP 2021 Shared Task: Robust Spoken Language Identification
    Elizabeth Salesky, Badr M. Abdullah, Sabrina J. Mielke, Elena Klyachko, Oleg Serikov, Edoardo Ponti, Ritesh Kumar, Ryan Cotterell, Ekaterina Vylomova
    http://arxiv.org/abs/2106.03895v1

    • [cs.CL]Self-supervised and Supervised Joint Training for Resource-rich Machine Translation
    Yong Cheng, Wei Wang, Lu Jiang, Wolfgang Macherey
    http://arxiv.org/abs/2106.04060v1

    • [cs.CL]Structured Reordering for Modeling Latent Alignments in Sequence Transduction
    Bailin Wang, Mirella Lapata, Ivan Titov
    http://arxiv.org/abs/2106.03257v2

    • [cs.CL]Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality
    Mina Lee, Chris Donahue, Alexander Iyabor, Robin Jia, Percy Liang
    http://arxiv.org/abs/2106.04102v1

    • [cs.CL]TIMEDIAL: Temporal Commonsense Reasoning in Dialog
    Lianhui Qin, Aditya Gupta, Shyam Upadhyay, Luheng He, Yejin Choi, Manaal Faruqui
    http://arxiv.org/abs/2106.04571v1

    • [cs.CL]Translate, then Parse! A strong baseline for Cross-Lingual AMR Parsing
    Sarah Uhrig, Yoalli Rezepka Garcia, Juri Opitz, Anette Frank
    http://arxiv.org/abs/2106.04565v1

    • [cs.CL]Turing: an Accurate and Interpretable Multi-Hypothesis Cross-Domain Natural Language Database Interface
    Peng Xu, Wenjie Zi, Hamidreza Shahidi, Ákos Kádár, Keyi Tang, Wei Yang, Jawad Ateeq, Harsh Barot, Meidan Alon, Yanshuai Cao
    http://arxiv.org/abs/2106.04559v1

    • [cs.CL]Ultra-Fine Entity Typing with Weak Supervision from a Masked Language Model
    Hongliang Dai, Yangqiu Song, Haixun Wang
    http://arxiv.org/abs/2106.04098v1

    • [cs.CL]Unsupervised Word Segmentation from Discrete Speech Units in Low-Resource Settings
    Marcely Zanon Boito, Bolaji Yusuf, Lucas Ondel, Aline Villavicencio, Laurent Besacier
    http://arxiv.org/abs/2106.04298v1

    • [cs.CL]XtremeDistilTransformers: Task Transfer for Task-agnostic Distillation
    Subhabrata Mukherjee, Ahmed Hassan Awadallah, Jianfeng Gao
    http://arxiv.org/abs/2106.04563v1

    • [cs.CV]A Synchronized Reprojection-based Model for 3D Human Pose Estimation
    Yicheng Deng, Cheng Sun, Yongqi Sun, Jiahui Zhu
    http://arxiv.org/abs/2106.04274v1

    • [cs.CV]Adversarial Semantic Hallucination for Domain Generalized Semantic Segmentation
    Gabriel Tjio, Ping Liu, Joey Tianyi Zhou, Rick Siow Mong Goh
    http://arxiv.org/abs/2106.04144v1

    • [cs.CV]Affinity Attention Graph Neural Network for Weakly Supervised Semantic Segmentation
    Bingfeng Zhang, Jimin Xiao, Jianbo Jiao, Yunchao Wei, Yao Zhao
    http://arxiv.org/abs/2106.04054v1

    • [cs.CV]An Intelligent Hybrid Model for Identity Document Classification
    Nouna Khandan
    http://arxiv.org/abs/2106.04345v1

    • [cs.CV]Are VQA Systems RAD? Measuring Robustness to Augmented Data with Focused Interventions
    Daniel Rosenberg, Itai Gat, Amir Feder, Roi Reichart
    http://arxiv.org/abs/2106.04484v1

    • [cs.CV]CSRNet: Cascaded Selective Resolution Network for Real-time Semantic Segmentation
    Jingjing Xiong, Lai-Man Po, Wing-Yin Yu, Chang Zhou, Pengfei Xian, Weifeng Ou
    http://arxiv.org/abs/2106.04400v1

    • [cs.CV]Chasing Sparsity in Vision Transformers:An End-to-End Exploration
    Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang, Zhangyang Wang
    http://arxiv.org/abs/2106.04533v1

    • [cs.CV]Contrastive Representation Learning for Hand Shape Estimation
    Christian Zimmermann, Max Argus, Thomas Brox
    http://arxiv.org/abs/2106.04324v1

    • [cs.CV]Conversational Fashion Image Retrieval via Multiturn Natural Language Feedback
    Yifei Yuan, Wai Lam
    http://arxiv.org/abs/2106.04128v1

    • [cs.CV]Cross-Domain Gradient Discrepancy Minimization for Unsupervised Domain Adaptation
    Zhekai Du, Jingjing Li, Hongzu Su, Lei Zhu, Ke Lu
    http://arxiv.org/abs/2106.04151v1

    • [cs.CV]DETReg: Unsupervised Pretraining with Region Priors for Object Detection
    Amir Bar, Xin Wang, Vadim Kantorov, Colorado J Reed, Roei Herzig, Gal Chechik, Anna Rohrbach, Trevor Darrell, Amir Globerson
    http://arxiv.org/abs/2106.04550v1

    • [cs.CV]Data-Efficient Instance Generation from Instance Discrimination
    Ceyuan Yang, Yujun Shen, Yinghao Xu, Bolei Zhou
    http://arxiv.org/abs/2106.04566v1

    • [cs.CV]Demystifying Local Vision Transformer: Sparse Connectivity, Weight Sharing, and Dynamic Weight
    Qi Han, Zejia Fan, Qi Dai, Lei Sun, Ming-Ming Cheng, Jiaying Liu, Jingdong Wang
    http://arxiv.org/abs/2106.04263v1

    • [cs.CV]Design of Low-Artifact Interpolation Kernels by Means of Computer Algebra
    Peter Karpov
    http://arxiv.org/abs/2106.04104v1

    • [cs.CV]Discriminative Triad Matching and Reconstruction for Weakly Referring Expression Grounding
    Mingjie Sun, Jimin Xiao, Eng Gee Lim, Si Liu, John Y. Goulermas
    http://arxiv.org/abs/2106.04053v1

    • [cs.CV]Diverse Part Discovery: Occluded Person Re-identification with Part-Aware Transformer
    Yulin Li, Jianfeng He, Tianzhu Zhang, Xiang Liu, Yongdong Zhang, Feng Wu
    http://arxiv.org/abs/2106.04095v1

    • [cs.CV]DoubleField: Bridging the Neural Surface and Radiance Fields for High-fidelity Human Rendering
    Ruizhi Shao, Hongwen Zhang, He Zhang, Yanpei Cao, Tao Yu, Yebin Liu
    http://arxiv.org/abs/2106.03798v2

    • [cs.CV]Efficient training for future video generation based on hierarchical disentangled representation of latent variables
    Naoya Fushishita, Antonio Tejero-de-Pablos, Yusuke Mukuta, Tatsuya Harada
    http://arxiv.org/abs/2106.03502v2

    • [cs.CV]Few-Shot Action Localization without Knowing Boundaries
    Ting-Ting Xie, Christos Tzelepis, Fan Fu, Ioannis Patras
    http://arxiv.org/abs/2106.04150v1

    • [cs.CV]Fully Transformer Networks for Semantic Image Segmentation
    Sitong Wu, Tianyi Wu, Fangjian Lin, Shengwei Tian, Guodong Guo
    http://arxiv.org/abs/2106.04108v1

    • [cs.CV]Grapevine Winter Pruning Automation: On Potential Pruning Points Detection through 2D Plant Modeling using Grapevine Segmentation
    Miguel Fernandes, Antonello Scaldaferri, Giuseppe Fiameni, Tao Teng, Matteo Gatti, Stefano Poni, Claudio Semini, Darwin Caldwell, Fei Chen
    http://arxiv.org/abs/2106.04208v1

    • [cs.CV]HPRNet: Hierarchical Point Regression for Whole-Body Human Pose Estimation
    Nermin Samet, Emre Akbas
    http://arxiv.org/abs/2106.04269v1

    • [cs.CV]Harnessing Unrecognizable Faces for Face Recognition
    Siqi Deng, Yuanjun Xiong, Meng Wang, Wei Xia, Stefano Soatto
    http://arxiv.org/abs/2106.04112v1

    • [cs.CV]Hierarchical Lovász Embeddings for Proposal-free Panoptic Segmentation
    Tommi Kerola, Jie Li, Atsushi Kanehira, Yasunori Kudo, Alexis Vallet, Adrien Gaidon
    http://arxiv.org/abs/2106.04555v1

    • [cs.CV]Highly accurate digital traffic recording as a basis for future mobility research: Methods and concepts of the research project HDV-Mess
    Laurent Kloeker, Fabian Thomsen, Lutz Eckstein, Philip Trettner, Tim Elsner, Julius Nehring-Wirxel, Kersten Schuster, Leif Kobbelt, Michael Hoesch
    http://arxiv.org/abs/2106.04175v1

    • [cs.CV]How to Design a Three-Stage Architecture for Audio-Visual Active Speaker Detection in the Wild
    Okan Köpüklü, Maja Taseska, Gerhard Rigoll
    http://arxiv.org/abs/2106.03932v1

    • [cs.CV]Image Deformation Estimation via Multi-Objective Optimization
    Takumi Nakane, Xuequan Lu, Haoran Xie, Chao Zhang
    http://arxiv.org/abs/2106.04139v1

    • [cs.CV]Image2Point: 3D Point-Cloud Understanding with Pretrained 2D ConvNets
    Chenfeng Xu, Shijia Yang, Bohan Zhai, Bichen Wu, Xiangyu Yue, Wei Zhan, Peter Vajda, Kurt Keutzer, Masayoshi Tomizuka
    http://arxiv.org/abs/2106.04180v1

    • [cs.CV]Interpreting Deep Learning based Cerebral Palsy Prediction with Channel Attention
    Manli Zhu, Qianhui Men, Edmond S. L. Ho, Howard Leung, Hubert P. H. Shum
    http://arxiv.org/abs/2106.04471v1

    • [cs.CV]Learning by Distillation: A Self-Supervised Learning Framework for Optical Flow Estimation
    Pengpeng Liu, Michael R. Lyu, Irwin King, Jia Xu
    http://arxiv.org/abs/2106.04195v1

    • [cs.CV]Left Ventricle Contouring in Cardiac Images Based on Deep Reinforcement Learning
    Sixing Yin, Yameng Han, Shufang Li
    http://arxiv.org/abs/2106.04127v1

    • [cs.CV]LipSync3D: Data-Efficient Learning of Personalized 3D Talking Faces from Video using Pose and Lighting Normalization
    Avisek Lahiri, Vivek Kwatra, Christian Frueh, John Lewis, Chris Bregler
    http://arxiv.org/abs/2106.04185v1

    • [cs.CV]LocalTrans: A Multiscale Local Transformer Network for Cross-Resolution Homography Estimation
    Ruizhi Shao, Gaochang Wu, Yuemei Zhou, Ying Fu, Lu Fang, Yebin Liu
    http://arxiv.org/abs/2106.04067v1

    • [cs.CV]Low-Rank Subspaces in GANs
    Jiapeng Zhu, Ruili Feng, Yujun Shen, Deli Zhao, Zhengjun Zha, Jingren Zhou, Qifeng Chen
    http://arxiv.org/abs/2106.04488v1

    • [cs.CV]MViT: Mask Vision Transformer for Facial Expression Recognition in the wild
    Hanting Li, Mingzhe Sui, Feng Zhao, Zhengjun Zha, Feng Wu
    http://arxiv.org/abs/2106.04520v1

    • [cs.CV]MoCo-Flow: Neural Motion Consensus Flow for Dynamic Humans in Stationary Monocular Cameras
    Xuelin Chen, Weiyu Li, Daniel Cohen-Or, Niloy J. Mitra, Baoquan Chen
    http://arxiv.org/abs/2106.04477v1

    • [cs.CV]Multi-dataset Pretraining: A Unified Model for Semantic Segmentation
    Bowen Shi, Xiaopeng Zhang, Haohang Xu, Wenrui Dai, Junni Zou, Hongkai Xiong, Qi Tian
    http://arxiv.org/abs/2106.04121v1

    • [cs.CV]Multi-frame sequence generator of 4D human body motion
    Marsot Mathieu, Wuhrer Stefanie, Franco Jean-Sebastien, Durocher Stephane
    http://arxiv.org/abs/2106.04387v1

    • [cs.CV]Multi-task Transformation Learning for Robust Out-of-Distribution Detection
    Sina Mohseni, Arash Vahdat, Jay Yadawa
    http://arxiv.org/abs/2106.03899v1

    • [cs.CV]Novel View Video Prediction Using a Dual Representation
    Sarah Shiraz, Krishna Regmi, Shruti Vyas, Yogesh S. Rawat, Mubarak Shah
    http://arxiv.org/abs/2106.03956v1

    • [cs.CV]On Improving Adversarial Transferability of Vision Transformers
    Muzammal Naseer, Kanchana Ranasinghe, Salman Khan, Fahad Shahbaz Khan, Fatih Porikli
    http://arxiv.org/abs/2106.04169v1

    • [cs.CV]On the relation between statistical learning and perceptual distances
    Alexander Hepburn, Valero Laparra, Raul Santos-Rodriguez, Johannes Ballé, Jesús Malo
    http://arxiv.org/abs/2106.04427v1

    • [cs.CV]On the role of feedback in visual processing: a predictive coding perspective
    Andrea Alamia, Milad Mozafari, Bhavin Choksi, Rufin VanRullen
    http://arxiv.org/abs/2106.04225v1

    • [cs.CV]On the use of automatically generated synthetic image datasets for benchmarking face recognition
    Laurent Colbois, Tiago de Freitas Pereira, Sébastien Marcel
    http://arxiv.org/abs/2106.04215v1

    • [cs.CV]Person Re-Identification with a Locally Aware Transformer
    Charu Sharma, Siddhant R. Kapil, David Chapman
    http://arxiv.org/abs/2106.03720v2

    • [cs.CV]Progressive Multi-scale Fusion Network for RGB-D Salient Object Detection
    Guangyu Ren, Yanchu Xie, Tianhong Dai, Tania Stathaki
    http://arxiv.org/abs/2106.03941v1

    • [cs.CV]Progressive Spatio-Temporal Bilinear Network with Monte Carlo Dropout for Landmark-based Facial Expression Recognition with Uncertainty Estimation
    Negar Heidari, Alexandros Iosifidis
    http://arxiv.org/abs/2106.04332v1

    • [cs.CV]RobustNav: Towards Benchmarking Robustness in Embodied Navigation
    Prithvijit Chattopadhyay, Judy Hoffman, Roozbeh Mottaghi, Aniruddha Kembhavi
    http://arxiv.org/abs/2106.04531v1

    • [cs.CV]SDGMNet: Statistic-based Dynamic Gradient Modulation for Local Descriptor Learning
    Jiayi Ma, Yuxin Deng
    http://arxiv.org/abs/2106.04434v1

    • [cs.CV]Salvage of Supervision in Weakly Supervised Detection
    Lin Sui, Chen-Lin Zhang, Jianxin Wu
    http://arxiv.org/abs/2106.04073v1

    • [cs.CV]Scaling Vision Transformers
    Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer
    http://arxiv.org/abs/2106.04560v1

    • [cs.CV]Segmentation and ABCD rule extraction for skin tumors classification
    Mahammed Messadi, Hocine Cherifi, Abdelhafid Bessaid
    http://arxiv.org/abs/2106.04372v1

    • [cs.CV]Self-Supervised Structure-from-Motion through Tightly-Coupled Depth and Egomotion Networks
    Brandon Wagstaff, Valentin Peretroukhin, Jonathan Kelly
    http://arxiv.org/abs/2106.04007v1

    • [cs.CV]Semantically Controllable Scene Generation with Guidance of Explicit Knowledge
    Wenhao Ding, Bo Li, Kim Ji Eun, Ding Zhao
    http://arxiv.org/abs/2106.04066v1

    • [cs.CV]Simulated Adversarial Testing of Face Recognition Models
    Nataniel Ruiz, Adam Kortylewski, Weichao Qiu, Cihang Xie, Sarah Adel Bargal, Alan Yuille, Stan Sclaroff
    http://arxiv.org/abs/2106.04569v1

    • [cs.CV]SpaceMeshLab: Spatial Context Memoization and Meshgrid Atrous Convolution Consensus for Semantic Segmentation
    Taehun Kim, Jinseong Kim, Daijin Kim
    http://arxiv.org/abs/2106.04025v1

    • [cs.CV]Subject-Independent Brain-Computer Interface for Decoding High-Level Visual Imagery Tasks
    Dae-Hyeok Lee, Dong-Kyun Han, Sung-Jin Kim, Ji-Hoon Jeong, Seong-Whan Lee
    http://arxiv.org/abs/2106.04026v1

    • [cs.CV]SynthRef: Generation of Synthetic Referring Expressions for Object Segmentation
    Ioannis Kazakos, Carles Ventura, Miriam Bellver, Carina Silberer, Xavier Giro-i-Nieto
    http://arxiv.org/abs/2106.04403v1

    • [cs.CV]Task-Generic Hierarchical Human Motion Prior using VAEs
    Jiaman Li, Ruben Villegas, Duygu Ceylan, Jimei Yang, Zhengfei Kuang, Hao Li, Yajie Zhao
    http://arxiv.org/abs/2106.04004v1

    • [cs.CV]Variational AutoEncoder for Reference based Image Super-Resolution
    Zhi-Song Liu, Wan-Chi Siu, Li-Wen Wang
    http://arxiv.org/abs/2106.04090v1

    • [cs.CV]Weakly Supervised Volumetric Image Segmentation with Deformed Templates
    Udaranga Wickramasinghe, Pascal Fua
    http://arxiv.org/abs/2106.03987v1

    • [cs.CV]White Paper Assistance: A Step Forward Beyond the Shortcut Learning
    Xuan Cheng, Xiaomin Wang, Jiali Deng, Minghui Liu, Ming Liu
    http://arxiv.org/abs/2106.04178v1

    • [cs.DB]A highly scalable repository of waveform and vital signs data from bedside monitoring devices
    Sanjay Malunjkar, Susan Weber, Somalee Datta
    http://arxiv.org/abs/2106.03965v1

    • [cs.DC]Assessing Open Interfaces and Protocols of PLCs for Computation Offloading at Field Level
    Michael Gundall, Hans Dieter Schotten
    http://arxiv.org/abs/2106.04517v1

    • [cs.DC]Asynchronous Distributed Optimization with Redundancy in Cost Functions
    Shuo Liu, Nirupam Gupta, Nitin H. Vaidya
    http://arxiv.org/abs/2106.03998v1

    • [cs.DC]CloudChain: A Cloud Blockchain Using Shared Memory Consensus and RDMA
    Minghui Xu, Shuo Liu, Dongxiao Yu, Xiuzhen Cheng, Shaoyong Guo, Jiguo Yu
    http://arxiv.org/abs/2106.04122v1

    • [cs.DC]GearV: A Two-Gear Hypervisor for Mixed-Criticality IoT Systems
    Kaiwen Long, Chong Xing, Yuebin Qi, Pei Zhang, Changsong Wu, Wenxiao Fang, Jing Tan, Jie Chen, Shiming Zhang, Zuosheng Wang, Zuanmin Liu, Cao Liang, Jiaxiang Xu
    http://arxiv.org/abs/2106.04514v1

    • [cs.DC]Launchpad: A Programming Model for Distributed Machine Learning Research
    Fan Yang, Gabriel Barth-Maron, Piotr Stańczyk, Matthew Hoffman, Siqi Liu, Manuel Kroiss, Aedan Pope, Alban Rrustemi
    http://arxiv.org/abs/2106.04516v1

    • [cs.DC]Near-Optimal Dispersion on Arbitrary Anonymous Graphs
    Ajay D. Kshemkalyani, Gokarna Sharma
    http://arxiv.org/abs/2106.03943v1

    • [cs.DC]PAIO: A Software-Defined Storage Data Plane Framework
    Ricardo Macedo, Yusuke Tanimura, Jason Haga, Vijay Chidambaram, José Pereira, João Paulo
    http://arxiv.org/abs/2106.03617v2

    • [cs.DL]ConSTR: A Contextual Search Term Recommender
    Thomas Krämer, Zeljko Carevic, Dwaipayan Roy, Claus-Peter Klas, Philipp Mayr
    http://arxiv.org/abs/2106.04376v1

    • [cs.DS]Low-Congestion Shortcuts in Constant Diameter Graphs
    Shimon Kogan, Merav Parter
    http://arxiv.org/abs/2106.01894v2

    • [cs.DS]Sketch-Based Streaming Anomaly Detection in Dynamic Graphs
    Siddharth Bhatia, Mohit Wadhwa, Philip S. Yu, Bryan Hooi
    http://arxiv.org/abs/2106.04486v1

    • [cs.GT]Improving Social Welfare While Preserving Autonomy via a Pareto Mediator
    Stephen McAleer, John Lanier, Michael Dennis, Pierre Baldi, Roy Fox
    http://arxiv.org/abs/2106.03927v1

    • [cs.IR]Defining definition: a Text mining Approach to Define Innovative Technological Fields
    Vito Giordano, Filippo Chiarello, Elena Cervelli
    http://arxiv.org/abs/2106.04210v1

    • [cs.IR]Exploring Periodicity and Interactivity in Multi-Interest Framework for Sequential Recommendation
    Gaode Chen, Xinghua Zhang, Yanyan Zhao, Cong Xue, Ji Xiang
    http://arxiv.org/abs/2106.04415v1

    • [cs.IR]HieRec: Hierarchical User Interest Modeling for Personalized News Recommendation
    Tao Qi, Fangzhao Wu, Chuhan Wu, Peiru Yang, Yang Yu, Xing Xie, Yongfeng Huang
    http://arxiv.org/abs/2106.04408v1

    • [cs.IR]MindReader: Recommendation over Knowledge Graph Entities with Explicit User Ratings
    Anders H. Brams, Anders L. Jakobsen, Theis E. Jendal, Matteo Lissandrini, Peter Dolog, Katja Hose
    http://arxiv.org/abs/2106.04209v1

    • [cs.IR]Optimization of Service Addition in Multilevel Index Model for Edge Computing
    Jiayan Gu, Yan Wu, Ashiq Anjum, John Panneerselvam, Yao Lu, Bo Yuan
    http://arxiv.org/abs/2106.04494v1

    • [cs.IR]Review Polarity-wise Recommender
    Han Liu, Yangyang Guo, Jianhua Yin, Zan Gao, Liqiang Nie
    http://arxiv.org/abs/2106.04155v1

    • [cs.IT]A Perspective on Time towards Wireless 6G
    Petar Popovski, Federico Chiariotti, Kaibin Huang, Anders E. Kalør, Marios Kountouris, Nikolaos Pappas, Beatriz Soret
    http://arxiv.org/abs/2106.04314v1

    • [cs.IT]A Sequence Selection Bound for the Capacity of the Nonlinear Fiber Channel
    Stella Civelli, Enrico Forestieri, Alexey Lotsmanov, Dmitry Razdoburdin, Marco Secondini
    http://arxiv.org/abs/2106.04097v1

    • [cs.IT]Contention-based Grant-free Transmission with Extremely Sparse Orthogonal Pilot Scheme
    Zhifeng Yuan, Zhigang Li, Weimin Li, Yihua Ma
    http://arxiv.org/abs/2106.04172v1

    • [cs.IT]Dilated Convolution based CSI Feedback Compression for Massive MIMO Systems
    Shunpu Tang, Junjuan Xia, Lisheng Fan, Xianfu Lei, Wei Xu, Arumugam Nallanathan
    http://arxiv.org/abs/2106.04043v1

    • [cs.IT]Low-complexity Voronoi shaping for the Gaussian channel
    S. Li, A. Mirani, M. Karlsson, E. Agrell
    http://arxiv.org/abs/2106.03262v2

    • [cs.IT]Modeling Uplink Coverage Performance in Hybrid Satellite-Terrestrial Networks
    Bassel Al Homssi, Akram Al-Hourani
    http://arxiv.org/abs/2106.04293v1

    • [cs.IT]On the Linear Capacity of Conditional Disclosure of Secrets
    Zhou Li, Hua Sun
    http://arxiv.org/abs/2106.04483v1

    • [cs.IT]On the Outage Capacity of the Massive MIMO Diversity Channel
    Marco Martalo, Riccardo Raheli
    http://arxiv.org/abs/2106.04203v1

    • [cs.IT]Optimized Rate-Profiling for PAC Codes
    He Sun, Emanuele Viterbo, Rongke Liu
    http://arxiv.org/abs/2106.04074v1

    • [cs.IT]Optimizing a Binary Intelligent Reflecting Surface for OFDM Communications under Mutual Coupling
    Emil Björnson
    http://arxiv.org/abs/2106.04280v1

    • [cs.IT]Outage Performance of Multi-UAV Relaying-based Imperfect Hardware Hybrid Satellite-Terrestrial Networks
    Pankaj K. Sharma, Deepika Gupta
    http://arxiv.org/abs/2106.04223v1

    • [cs.IT]Principal Bit Analysis: Autoencoding with Schur-Concave Loss
    Sourbh Bhadane, Aaron B. Wagner, Jayadev Acharya
    http://arxiv.org/abs/2106.02796v2

    • [cs.IT]Private Multi-Group Aggregation
    Carolina Naim, Rafael G. L. D’Oliveira, Salim El Rouayheb
    http://arxiv.org/abs/2106.04467v1

    • [cs.IT]Proof methods for robust low-rank matrix recovery
    Tim Fuchs, David Gross, Peter Jung, Felix Krahmer, Richard Kueng, Dominik Stöger
    http://arxiv.org/abs/2106.04382v1

    • [cs.LG]A Deep Value-network Based Approach for Multi-Driver Order Dispatching
    Xiaocheng Tang, Zhiwei Qin, Fan Zhang, Zhaodong Wang, Zhe Xu, Yintai Ma, Hongtu Zhu, Jieping Ye
    http://arxiv.org/abs/2106.04493v1

    • [cs.LG]A Survey of Transformers
    Tianyang Lin, Yuxin Wang, Xiangyang Liu, Xipeng Qiu
    http://arxiv.org/abs/2106.04554v1

    • [cs.LG]A critical look at the current train/test split in machine learning
    Jimin Tan, Jianan Yang, Sai Wu, Gang Chen, Jake Zhao
    http://arxiv.org/abs/2106.04525v1

    • [cs.LG]A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs
    Gadi Naveh, Zohar Ringel
    http://arxiv.org/abs/2106.04110v1

    • [cs.LG]Adaptive Machine Unlearning
    Varun Gupta, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Chris Waites
    http://arxiv.org/abs/2106.04378v1

    • [cs.LG]Amortized Generation of Sequential Counterfactual Explanations for Black-box Models
    Sahil Verma, Keegan Hines, John P. Dickerson
    http://arxiv.org/abs/2106.03962v1

    • [cs.LG]Automatic Generation of Machine Learning Synthetic Data Using ROS
    Kyle M. Hart, Ari B. Goodman, Ryan P. O’Shea
    http://arxiv.org/abs/2106.04547v1

    • [cs.LG]Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future
    Harshavardhan Kamarthi, Alexander Rodríguez, B. Aditya Prakash
    http://arxiv.org/abs/2106.04420v1

    • [cs.LG]Breaking the Limits of Message Passing Graph Neural Networks
    Muhammet Balcilar, Pierre Héroux, Benoit Gaüzère, Pascal Vasseur, Sébastien Adam, Paul Honeine
    http://arxiv.org/abs/2106.04319v1

    • [cs.LG]Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks
    Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Furong Huang, Uzi Vishkin, Micah Goldblum, Tom Goldstein
    http://arxiv.org/abs/2106.04537v1

    • [cs.LG]Chow-Liu++: Optimal Prediction-Centric Learning of Tree Ising Models
    Enric Boix-Adsera, Guy Bresler, Frederic Koehler
    http://arxiv.org/abs/2106.03969v1

    • [cs.LG]Closed-Form Analytical Results for Maximum Entropy Reinforcement Learning
    Argenis Arriojas, Stas Tiomkin, Rahul V. Kulkarni
    http://arxiv.org/abs/2106.03931v1

    • [cs.LG]Cooperative Stochastic Multi-agent Multi-armed Bandits Robust to Adversarial Corruptions
    Junyan Liu, Shuai Li, Dapeng Li
    http://arxiv.org/abs/2106.04207v1

    • [cs.LG]Coresets for Classification — Simplified and Strengthened
    Tung Mai, Anup B. Rao, Cameron Musco
    http://arxiv.org/abs/2106.04254v1

    • [cs.LG]Correcting Momentum in Temporal Difference Learning
    Emmanuel Bengio, Joelle Pineau, Doina Precup
    http://arxiv.org/abs/2106.03955v1

    • [cs.LG]Deep Learning Statistical Arbitrage
    Jorge Guijarro-Ordonez, Markus Pelger, Greg Zanotti
    http://arxiv.org/abs/2106.04028v1

    • [cs.LG]Deep Proxy Causal Learning and its Application to Confounded Bandit Policy Evaluation
    Liyuan Xu, Heishiro Kanagawa, Arthur Gretton
    http://arxiv.org/abs/2106.03907v1

    • [cs.LG]Detecting Anomalous Event Sequences with Temporal Point Processes
    Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann
    http://arxiv.org/abs/2106.04465v1

    • [cs.LG]Differentiable Multiple Shooting Layers
    Stefano Massaroli, Michael Poli, Sho Sonoda, Taji Suzuki, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
    http://arxiv.org/abs/2106.03885v1

    • [cs.LG]Dynamic Sparse Training for Deep Reinforcement Learning
    Ghada Sokar, Elena Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy, Peter Stone
    http://arxiv.org/abs/2106.04217v1

    • [cs.LG]Efficient Online Learning for Dynamic k-Clustering
    Dimitris Fotakis, Georgios Piliouras, Stratis Skoulakis
    http://arxiv.org/abs/2106.04336v1

    • [cs.LG]Enhancing Robustness of Neural Networks through Fourier Stabilization
    Netanel Raviv, Aidan Kelley, Michael Guo, Yevgeny Vorobeychik
    http://arxiv.org/abs/2106.04435v1

    • [cs.LG]Evaluating Meta-Feature Selection for the Algorithm Recommendation Problem
    Geand Trindade Pereira, Moises Rocha dos Santos, Andre Carlos Ponce de Leon Ferreira de Carvalho
    http://arxiv.org/abs/2106.03954v1

    • [cs.LG]FEAR: A Simple Lightweight Method to Rank Architectures
    Debadeepta Dey, Shital Shah, Sebastien Bubeck
    http://arxiv.org/abs/2106.04010v1

    • [cs.LG]Fast Federated Learning in the Presence of Arbitrary Device Unavailability
    Xinran Gu, Kaixuan Huang, Jingzhao Zhang, Longbo Huang
    http://arxiv.org/abs/2106.04159v1

    • [cs.LG]Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing
    Mikhail Khodak, Renbo Tu, Tian Li, Liam Li, Maria-Florina Balcan, Virginia Smith, Ameet Talwalkar
    http://arxiv.org/abs/2106.04502v1

    • [cs.LG]Fine-grained Out-of-Distribution Detection with Mixup Outlier Exposure
    Jingyang Zhang, Nathan Inkawhich, Yiran Chen, Hai Li
    http://arxiv.org/abs/2106.03917v1

    • [cs.LG]Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation
    Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio
    http://arxiv.org/abs/2106.04399v1

    • [cs.LG]Generative Flows with Invertible Attentions
    Rhea Sanjay Sukthanker, Zhiwu Huang, Suryansh Kumar, Radu Timofte, Luc Van Gool
    http://arxiv.org/abs/2106.03959v1

    • [cs.LG]Graph-MLP: Node Classification without Message Passing in Graph
    Yang Hu, Haoxuan You, Zhecan Wang, Zhicheng Wang, Erjin Zhou, Yue Gao
    http://arxiv.org/abs/2106.04051v1

    • [cs.LG]Hash Layers For Large Sparse Models
    Stephen Roller, Sainbayar Sukhbaatar, Arthur Szlam, Jason Weston
    http://arxiv.org/abs/2106.04426v1

    • [cs.LG]Householder-Absolute Neural Layers For High Variability and Deep Trainability
    Yueyao Yu, Yin Zhang
    http://arxiv.org/abs/2106.04088v1

    • [cs.LG]Hybrid Method Based on NARX models and Machine Learning for Pattern Recognition
    P. H. O. Silva, A. S. Cerqueira, E. G. Nepomuceno
    http://arxiv.org/abs/2106.04021v1

    • [cs.LG]Incentive Mechanism for Privacy-Preserving Federated Learning
    Shuyuan Zheng, Yang Cao, Masatoshi Yoshikawa
    http://arxiv.org/abs/2106.04384v1

    • [cs.LG]Incorporating NODE with Pre-trained Neural Differential Operator for Learning Dynamics
    Shiqi Gong, Qi Meng, Yue Wang, Lijun Wu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
    http://arxiv.org/abs/2106.04166v1

    • [cs.LG]Interactive Label Cleaning with Example-based Explanations
    Stefano Teso, Andrea Bontempelli, Fausto Giunchiglia, Andrea Passerini
    http://arxiv.org/abs/2106.03922v1

    • [cs.LG]LEADS: Learning Dynamical Systems that Generalize Across Environments
    Yuan Yin, Ibrahim Ayed, Emmanuel de Bézenac, Nicolas Baskiotis, Patrick Gallinari
    http://arxiv.org/abs/2106.04546v1

    • [cs.LG]LaplaceNet: A Hybrid Energy-Neural Model for Deep Semi-Supervised Classification
    Philip Sellars, Angelica I. Aviles-Rivero, Carola-Bibiane Schönlieb
    http://arxiv.org/abs/2106.04527v1

    • [cs.LG]Learning Markov State Abstractions for Deep Reinforcement Learning
    Cameron Allen, Neev Parikh, Omer Gottesman, George Konidaris
    http://arxiv.org/abs/2106.04379v1

    • [cs.LG]Learning from Multiple Noisy Partial Labelers
    Peilin Yu, Tiffany Ding, Stephen H. Bach
    http://arxiv.org/abs/2106.04530v1

    • [cs.LG]Linear Convergence of Entropy-Regularized Natural Policy Gradient with Linear Function Approximation
    Semih Cayci, Niao He, R. Srikant
    http://arxiv.org/abs/2106.04096v1

    • [cs.LG]Manifold Topology Divergence: a Framework for Comparing Data Manifolds
    Serguei Barannikov, Ilya Trofimov, Grigorii Sotnikov, Ekaterina Trimbach, Alexander Korotin, Alexander Filippov, Evgeny Burnaev
    http://arxiv.org/abs/2106.04024v1

    • [cs.LG]Meta Learning for Knowledge Distillation
    Wangchunshu Zhou, Canwen Xu, Julian McAuley
    http://arxiv.org/abs/2106.04570v1

    • [cs.LG]Muddling Label Regularization: Deep Learning for Tabular Datasets
    Karim Lounici, Katia Meziani, Benjamin Riu
    http://arxiv.org/abs/2106.04462v1

    • [cs.LG]Multi-output Gaussian Processes for Uncertainty-aware Recommender Systems
    Yinchong Yang, Florian Buettner
    http://arxiv.org/abs/2106.04221v1

    • [cs.LG]Neural Hybrid Automata: Learning Dynamics with Multiple Modes and Stochastic Transitions
    Michael Poli, Stefano Massaroli, Luca Scimeca, Seong Joon Oh, Sanghyuk Chun, Atsushi Yamashita, Hajime Asama, Jinkyoo Park, Animesh Garg
    http://arxiv.org/abs/2106.04165v1

    • [cs.LG]Nonsmooth Implicit Differentiation for Machine Learning and Optimization
    Jérôme Bolte, Tam Le, Edouard Pauwels, Antonio Silveti-Falls
    http://arxiv.org/abs/2106.04350v1

    • [cs.LG]Offline Policy Comparison under Limited Historical Agent-Environment Interactions
    Anton Dereventsov, Joseph D. Daws Jr., Clayton Webster
    http://arxiv.org/abs/2106.03934v1

    • [cs.LG]Parameter Inference with Bifurcation Diagrams
    Gregory Szep, Neil Dalchau, Attila Csikasz-Nagy
    http://arxiv.org/abs/2106.04243v1

    • [cs.LG]PlayVirtual: Augmenting Cycle-Consistent Virtual Trajectories for Reinforcement Learning
    Tao Yu, Cuiling Lan, Wenjun Zeng, Mingxiao Feng, Zhibo Chen
    http://arxiv.org/abs/2106.04152v1

    • [cs.LG]Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss
    Jeff Z. HaoChen, Colin Wei, Adrien Gaidon, Tengyu Ma
    http://arxiv.org/abs/2106.04156v1

    • [cs.LG]Provably Robust Detection of Out-of-distribution Data (almost) for free
    Alexander Meinke, Julian Bitterwolf, Matthias Hein
    http://arxiv.org/abs/2106.04260v1

    • [cs.LG]RECOWNs: Probabilistic Circuits for Trustworthy Time Series Forecasting
    Nils Thoma, Zhongjie Yu, Fabrizio Ventola, Kristian Kersting
    http://arxiv.org/abs/2106.04148v1

    • [cs.LG]Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization
    Bing-Jing Hsieh, Ping-Chun Hsieh, Xi Liu
    http://arxiv.org/abs/2106.04335v1

    • [cs.LG]Rethinking Graph Transformers with Spectral Attention
    Devin Kreuzer, Dominique Beaini, William L. Hamilton, Vincent Létourneau, Prudencio Tossou
    http://arxiv.org/abs/2106.03893v1

    • [cs.LG]Robust Generalization despite Distribution Shift via Minimum Discriminating Information
    Tobias Sutter, Andreas Krause, Daniel Kuhn
    http://arxiv.org/abs/2106.04443v1

    • [cs.LG]Self-supervised Graph-level Representation Learning with Local and Global Structure
    Minghao Xu, Hang Wang, Bingbing Ni, Hongyu Guo, Jian Tang
    http://arxiv.org/abs/2106.04113v1

    • [cs.LG]Stability and Generalization of Bilevel Programming in Hyperparameter Optimization
    Fan Bao, Guoqiang Wu, Chongxuan Li, Jun Zhu, Bo Zhang
    http://arxiv.org/abs/2106.04188v1

    • [cs.LG]Staircase Attention for Recurrent Processing of Sequences
    Da Ju, Stephen Roller, Sainbayar Sukhbaatar, Jason Weston
    http://arxiv.org/abs/2106.04279v1

    • [cs.LG]Supervised Machine Learning with Plausible Deniability
    Stefan Rass, Sandra König, Jasmin Wachter, Manuel Egger, Manuel Hobisch
    http://arxiv.org/abs/2106.04267v1

    • [cs.LG]The Fast Kernel Transform
    John Paul Ryan, Sebastian Ament, Carla P. Gomes, Anil Damle
    http://arxiv.org/abs/2106.04487v1

    • [cs.LG]The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation
    Alex J. Chan, Ioana Bica, Alihan Huyuk, Daniel Jarrett, Mihaela van der Schaar
    http://arxiv.org/abs/2106.04240v1

    • [cs.LG]The Randomness of Input Data Spaces is an A Priori Predictor for Generalization
    Martin Briesch, Dominik Sobania, Franz Rothlauf
    http://arxiv.org/abs/2106.04181v1

    • [cs.LG]The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition
    Tiancheng Jin, Longbo Huang, Haipeng Luo
    http://arxiv.org/abs/2106.04117v1

    • [cs.LG]There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning
    Nathan Grinsztajn, Johan Ferret, Olivier Pietquin, Philippe Preux, Matthieu Geist
    http://arxiv.org/abs/2106.04480v1

    • [cs.LG]Time-series Imputation of Temporally-occluded Multiagent Trajectories
    Shayegan Omidshafiei, Daniel Hennes, Marta Garnelo, Eugene Tarassov, Zhe Wang, Romuald Elie, Jerome T. Connor, Paul Muller, Ian Graham, William Spearman, Karl Tuyls
    http://arxiv.org/abs/2106.04219v1

    • [cs.LG]Towards Practical Credit Assignment for Deep Reinforcement Learning
    Vyacheslav Alipov, Riley Simmons-Edler, Nikita Putintsev, Pavel Kalinin, Dmitry Vetrov
    http://arxiv.org/abs/2106.04499v1

    • [cs.LG]Towards a Theoretical Framework of Out-of-Distribution Generalization
    Haotian Ye, Chuanlong Xie, Tianle Cai, Ruichen Li, Zhenguo Li, Liwei Wang
    http://arxiv.org/abs/2106.04496v1

    • [cs.LG]Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning
    Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran
    http://arxiv.org/abs/2106.04015v1

    • [cs.LG]Understanding (Generalized) Label Smoothing whenLearning with Noisy Labels
    Jiaheng Wei, Hangyu Liu, Tongliang Liu, Gang Niu, Yang Liu
    http://arxiv.org/abs/2106.04149v1

    • [cs.LG]What Data Augmentation Do We Need for Deep-Learning-Based Finance?
    Liu Ziyin, Kentaro Minami, Kentaro Imajo
    http://arxiv.org/abs/2106.04114v1

    • [cs.LG]What Makes Multimodal Learning Better than Single (Provably)
    Yu Huang, Chenzhuang Du, Zihui Xue, Xuanyao Chen, Hang Zhao, Longbo Huang
    http://arxiv.org/abs/2106.04538v1

    • [cs.LG]What training reveals about neural network complexity
    Andreas Loukas, Marinos Poiitis, Stefanie Jegelka
    http://arxiv.org/abs/2106.04186v1

    • [cs.LG]When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting
    Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
    http://arxiv.org/abs/2106.03904v1

    • [cs.NE]GSGP-CUDA — a CUDA framework for Geometric Semantic Genetic Programming
    Leonardo Trujillo, Jose Manuel Muñoz Contreras, Daniel E Hernandez, Mauro Castelli, Juan J Tapia
    http://arxiv.org/abs/2106.04034v1

    • [cs.NE]JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design
    AkshatKumar Nigam, Robert Pollice, Alan Aspuru-Guzik
    http://arxiv.org/abs/2106.04011v1

    • [cs.RO]A novel partially-decoupled translational parallel manipulator with symbolic kinematics, singularity identification and workspace determination
    Huiping Shen, Yinan Zhao, Ju Li, Guanglei Wu, Damien Chablat
    http://arxiv.org/abs/2106.04337v1

    • [cs.RO]Acoustic Power for Swarms of Microscopic Robots
    Tad Hogg
    http://arxiv.org/abs/2106.03923v1

    • [cs.RO]Efficient Sampling in POMDPs with Lipschitz Bandits for Motion Planning in Continuous Spaces
    Ömer Şahin Taş, Felix Hauser, Martin Lauer
    http://arxiv.org/abs/2106.04206v1

    • [cs.RO]Game-Theoretic Model Predictive Control with Data-Driven Identification of Vehicle Model for Head-to-Head Autonomous Racing
    Chanyoung Jung, Seungwook Lee, Hyunki Seong, Andrea Finazzi, David Hyunchul Shim
    http://arxiv.org/abs/2106.04094v1

    • [cs.RO]H-ModQuad: Modular Multi-Rotors with 4, 5, and 6 Controllable DOF
    Jiawei Xu, Diego S. D’Antonio, David Saldaña
    http://arxiv.org/abs/2106.04048v1

    • [cs.RO]Learning Riemannian Manifolds for Geodesic Motion Skills
    Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Rozo
    http://arxiv.org/abs/2106.04315v1

    • [cs.RO]Learning to Detect Multi-Modal Grasps for Dexterous Grasping in Dense Clutter
    Matt Corsaro, Stefanie Tellex, George Konidaris
    http://arxiv.org/abs/2106.03919v1

    • [cs.RO]Model Predictive Robot-Environment Interaction Control for Mobile Manipulation Tasks
    Maria Vittoria Minniti, Ruben Grandia, Kevin Fäh, Farbod Farshidian, Marco Hutter
    http://arxiv.org/abs/2106.04202v1

    • [cs.RO]Planning Multimodal Exploratory Actions for Online Robot Attribute Learning
    Xiaohan Zhang, Jivko Sinapov, Shiqi Zhang
    http://arxiv.org/abs/2106.03029v2

    • [cs.RO]Property-Aware Robot Object Manipulation: a Generative Approach
    Luca Garello, Linda Lastrico, Francesco Rea, Fulvio Mastrogiovanni, Nicoletta Noceti, Alessandra Sciutti
    http://arxiv.org/abs/2106.04385v1

    • [cs.RO]Residual Feedback Learning for Contact-Rich Manipulation Tasks with Uncertainty
    Alireza Ranjbar, Ngo Anh Vien, Hanna Ziesche, Joschka Boedecker, Gerhard Neumann
    http://arxiv.org/abs/2106.04306v1

    • [cs.RO]Risk Ranked Recall: Collision Safety Metric for Object Detection Systems in Autonomous Vehicles
    Ayoosh Bansal, Jayati Singh, Micaela Verucchi, Marco Caccamo
    http://arxiv.org/abs/2106.04146v1

    • [cs.RO]Safe Deep Q-Network for Autonomous Vehicles at Unsignalized Intersection
    Kasra Mokhtari, Alan R. Wagner
    http://arxiv.org/abs/2106.04561v1

    • [cs.RO]XIRL: Cross-embodiment Inverse Reinforcement Learning
    Kevin Zakka, Andy Zeng, Pete Florence, Jonathan Tompson, Jeannette Bohg, Debidatta Dwibedi
    http://arxiv.org/abs/2106.03911v1

    • [cs.SD]Broadcasted Residual Learning for Efficient Keyword Spotting
    Byeonggeun Kim, Simyung Chang, Jinkyu Lee, Dooyong Sung
    http://arxiv.org/abs/2106.04140v1

    • [cs.SD]Efficient Speech Emotion Recognition Using Multi-Scale CNN and Attention
    Zixuan Peng, Yu Lu, Shengfeng Pan, Yunfeng Liu
    http://arxiv.org/abs/2106.04133v1

    • [cs.SD]NWT: Towards natural audio-to-video generation with representation learning
    Rayhane Mama, Marc S. Tyndel, Hashiam Kadhim, Cole Clifford, Ragavan Thurairatnam
    http://arxiv.org/abs/2106.04283v1

    • [cs.SD]PILOT: Introducing Transformers for Probabilistic Sound Event Localization
    Christopher Schymura, Benedikt Bönninghoff, Tsubasa Ochiai, Marc Delcroix, Keisuke Kinoshita, Tomohiro Nakatani, Shoko Araki, Dorothea Kolossa
    http://arxiv.org/abs/2106.03903v1

    • [cs.SD]Raw Waveform Encoder with Multi-Scale Globally Attentive Locally Recurrent Networks for End-to-End Speech Recognition
    Max W. Y. Lam, Jun Wang, Chao Weng, Dan Su, Dong Yu
    http://arxiv.org/abs/2106.04275v1

    • [cs.SE]How to Bake Quantum into Your Pet Petri Nets and Have Your Net Theory Too
    Heinz W. Schmidt
    http://arxiv.org/abs/2106.03539v1

    • [cs.SI]Designing Toxic Content Classification for a Diversity of Perspectives
    Deepak Kumar, Patrick Gage Kelley, Sunny Consolvo, Joshua Mason, Elie Bursztein, Zakir Durumeric, Kurt Thomas, Michael Bailey
    http://arxiv.org/abs/2106.04511v1

    • [cs.SI]News consumption and social media regulations policy
    Gabriele Etta, Matteo Cinelli, Alessandro Galeazzi, Carlo Michele Valensise, Mauro Conti, Walter Quattrociocchi
    http://arxiv.org/abs/2106.03924v1

    • [cs.SI]Principled Hyperedge Prediction with Structural Spectral Features and Neural Networks
    Changlin Wan, Muhan Zhang, Wei Hao, Sha Cao, Pan Li, Chi Zhang
    http://arxiv.org/abs/2106.04292v1

    • [cs.SI]Surveillance of COVID-19 Pandemic using Social Media: A Reddit Study in North Carolina
    Christopher Whitfield, Yang Liu, Mohad Anwar
    http://arxiv.org/abs/2106.04515v1

    • [econ.EM]Testing Monotonicity of Mean Potential Outcomes in a Continuous Treatment
    Yu-Chin Hsu, Martin Huber, Ying-Ying Lee, Chu-An Liu
    http://arxiv.org/abs/2106.04237v1

    • [eess.AS]Description and Discussion on DCASE 2021 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring under Domain Shifted Conditions
    Yohei Kawaguchi, Keisuke Imoto, Yuma Koizumi, Noboru Harada, Daisuke Niizumi, Kota Dohi, Ryo Tanabe, Harsh Purohit, Takashi Endo
    http://arxiv.org/abs/2106.04492v1

    • [eess.IV]AutoPtosis
    Abdullah Aleem, Manoj Prabhakar Nallabothula, Pete Setabutr, Joelle A. Hallak, Darvin Yi
    http://arxiv.org/abs/2106.03905v1

    • [eess.IV]EnMcGAN: Adversarial Ensemble Learning for 3D Complete Renal Structures Segmentation
    Yuting He, Rongjun Ge, Xiaoming Qi, Guanyu Yang, Yang Chen, Youyong Kong, Huazhong Shu, Jean-Louis Coatrieux, Shuo Li
    http://arxiv.org/abs/2106.04130v1

    • [eess.IV]Generative adversarial network with object detector discriminator for enhanced defect detection on ultrasonic B-scans
    Luka Posilović, Duje Medak, Marko Subasic, Marko Budimir, Sven Loncaric
    http://arxiv.org/abs/2106.04281v1

    • [eess.IV]PolypGen: A multi-center polyp detection and segmentation dataset for generalisability assessment
    Sharib Ali, Debesh Jha, Noha Ghatwary, Stefano Realdon, Renato Cannizzaro, Osama E. Salem, Dominique Lamarque, Christian Daul, Kim V. Anonsen, Michael A. Riegler, Pål Halvorsen, Jens Rittscher, Thomas de Lange, James E. East
    http://arxiv.org/abs/2106.04463v1

    • [hep-ex]SPANet: Generalized Permutationless Set Assignment for Particle Physics using Symmetry Preserving Attention
    Alexander Shmakov, Michael James Fenton, Ta-Wei Ho, Shih-Chieh Hsu, Daniel Whiteson, Pierre Baldi
    http://arxiv.org/abs/2106.03898v1

    • [math.OC]Efficient solution method based on inverse dynamics for optimal control problems of rigid body systems
    Sotaro Katayama, Toshiyuki Ohtsuka
    http://arxiv.org/abs/2106.04176v1

    • [math.OC]Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks
    Dmitry Kovalev, Elnur Gasanov, Peter Richtárik, Alexander Gasnikov
    http://arxiv.org/abs/2106.04469v1

    • [math.OC]Optimized Data Rate Allocation for Dynamic Sensor Fusion over Resource Constrained Communication Networks
    Hyunho Jung, Ali Reza Pedram, Travis Craig Cuvelier, Takashi Tanaka
    http://arxiv.org/abs/2106.04001v1

    • [math.OC]Unbalanced Optimal Transport through Non-negative Penalized Linear Regression
    Laetitia Chapel, Rémi Flamary, Haoran Wu, Cédric Févotte, Gilles Gasso
    http://arxiv.org/abs/2106.04145v1

    • [math.OC]Using a New Nonlinear Gradient Method for Solving Large Scale Convex Optimization Problems with an Application on Arabic Medical Text
    Jaafar Hammoud, Ali Eisab, Natalia Dobrenkoa, Natalia Gusarovaa
    http://arxiv.org/abs/2106.04383v1

    • [math.PR]Markov Chains Generated by Convolutions of Orthogonality Measures
    Satoru Odake, Ryu Sasaki
    http://arxiv.org/abs/2106.04082v1

    • [math.PR]Maximum likelihood estimation for sub-fractional Vasicek model
    B. L. S. Prakasa Rao
    http://arxiv.org/abs/2106.03350v1

    • [math.ST]Bridge Simulation and Metric Estimation on Lie Groups
    Mathias Højgaard Jensen, Sarang Joshi, Stefan Sommer
    http://arxiv.org/abs/2106.03431v1

    • [math.ST]Minimax and adaptive tests for detecting abrupt and possibly transitory changes in a Poisson process
    Magalie Fromont, Fabrice Grela, Ronan Le Guével
    http://arxiv.org/abs/2106.04333v1

    • [math.ST]Process of the slope components of 今日学术视野(2021.6.10) - 图2-regression quantile
    Jana Jurečková
    http://arxiv.org/abs/2106.04373v1

    • [physics.chem-ph]Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations
    Yair Schiff, Vijil Chenthamarakshan, Samuel Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das
    http://arxiv.org/abs/2106.04464v1

    • [physics.data-an]Granger causality in the frequency domain: derivation and applications
    Vinicius Lima, Fernanda Jaiara Dellajustina, Renan O. Shimoura, Mauricio Girardi-Schappo, Nilton L. Kamiji, Rodrigo F. O. Pena, Antonio C. Roque
    http://arxiv.org/abs/2106.03990v1

    • [q-bio.NC]Credit Assignment Through Broadcasting a Global Error Vector
    David G. Clark, L. F. Abbott, SueYeon Chung
    http://arxiv.org/abs/2106.04089v1

    • [q-bio.NC]Object Based Attention Through Internal Gating
    Jordan Lei, Ari S. Benjamin, Konrad P. Kording
    http://arxiv.org/abs/2106.04540v1

    • [quant-ph]Encoding-dependent generalization bounds for parametrized quantum circuits
    Matthias C. Caro, Elies Gil-Fuster, Johannes Jakob Meyer, Jens Eisert, Ryan Sweke
    http://arxiv.org/abs/2106.03880v1

    • [quant-ph]NISQ Algorithm for Semidefinite Programming
    Kishor Bharti, Tobias Haug, Vlatko Vedral, Leong-Chuan Kwek
    http://arxiv.org/abs/2106.03891v1

    • [stat.AP]Scalar on time-by-distribution regression and its application for modelling associations between daily-living physical activity and cognitive functions in Alzheimer’s Disease
    Rahul Ghosal, Vijay R. Varma, Dmitri Volfson, Jacek Urbanek, Jeffrey M. Hausdorff, Amber Watts, Vadim Zipunnikov
    http://arxiv.org/abs/2106.03979v1

    • [stat.AP]Sensitivity analysis for random measurement error using regression calibration and simulation-extrapolation
    Linda Nab, Rolf H. H. Groenwold
    http://arxiv.org/abs/2106.04285v1

    • [stat.ME]A Unified Approach to Robust Inference for Genetic Covariance
    Jianqiao Wang, Sai Li, Hongzhe Li
    http://arxiv.org/abs/2106.04106v1

    • [stat.ME]A likelihood based sensitivity analysis for publication bias on summary ROC in meta-analysis of diagnostic test accuracy
    Yi Zhou, Ao Huang, Satoshi Hattori
    http://arxiv.org/abs/2106.04253v1

    • [stat.ME]Clustering with missing data: which imputation model for which cluster analysis method?
    Vincent Audigier, Ndèye Niang, Matthieu Resche-Rigon
    http://arxiv.org/abs/2106.04424v1

    • [stat.ME]Context-Specific Causal Discovery for Categorical Data Using Staged Trees
    Manuele Leonelli, Gherardo Varando
    http://arxiv.org/abs/2106.04416v1

    • [stat.ME]Do forecasts of bankruptcy cause bankruptcy? A machine learning sensitivity analysis
    Demetrios Papakostas, P. Richard Hahn, Jared Murray, Frank Zhou, Joseph Gerakos
    http://arxiv.org/abs/2106.04503v1

    • [stat.ME]Efficient Estimation For The Joint Model of Survival and Longitudinal Data
    Khandoker Akib Mohammad, Yuichi Hirose, Yuan Yao, Budhi Surya
    http://arxiv.org/abs/2106.04142v1

    • [stat.ME]Inference for Network Regression Models with Community Structure
    Mengjie Pan, Tyler H. McCormick, Bailey K. Fosdick
    http://arxiv.org/abs/2106.04271v1

    • [stat.ME]Methodological considerations for estimating policy effects in the context of co-occurring policies
    Beth Ann Griffin, Megan S. Schuler, Joseph Pane, Stephen W. Patrick, Rosanna Smart, Bradley D. Stein, Geoffrey Grimm, Elizabeth A. Stuart
    http://arxiv.org/abs/2106.04304v1

    • [stat.ME]Searching for consistent associations with a multi-environment knockoff filter
    Shuangning Li, Matteo Sesia, Yaniv Romano, Emmanuel Candès, Chiara Sabatti
    http://arxiv.org/abs/2106.04118v1

    • [stat.ME]Singhing with Confidence: Visualising the Performance of Confidence Structures
    Alexander Wimbush, Nicholas Gray, Scott Ferson
    http://arxiv.org/abs/2106.04433v1

    • [stat.ML]Adaptive transfer learning
    Henry W. J. Reeve, Timothy I. Cannings, Richard J. Samworth
    http://arxiv.org/abs/2106.04455v1

    • [stat.ML]Batch Normalization Orthogonalizes Representations in Deep Random Networks
    Hadi Daneshmand, Amir Joudaki, Francis Bach
    http://arxiv.org/abs/2106.03970v1

    • [stat.ML]Conditional Deep Inverse Rosenblatt Transports
    Tiangang Cui, Sergey Dolgov, Olivier Zahm
    http://arxiv.org/abs/2106.04170v1

    • [stat.ML]Decentralized Learning in Online Queuing Systems
    Flore Sentenac, Etienne Boursier, Vianney Perchet
    http://arxiv.org/abs/2106.04228v1

    • [stat.ML]Intrinsic Dimension Estimation
    Adam Block, Zeyu Jia, Yury Polyanskiy, Alexander Rakhlin
    http://arxiv.org/abs/2106.04018v1

    • [stat.ML]Seismic Inverse Modeling Method based on Generative Adversarial Network
    Pengfei Xie, YanShu Yin, JiaGen Hou, Mei Chen, Lixin Wang
    http://arxiv.org/abs/2106.04197v1

    • [stat.ML]Targeted Active Learning for Bayesian Decision-Making
    Louis Filstroff, Iiris Sundin, Petrus Mikkola, Aleksei Tiulpin, Juuso Kylmäoja, Samuel Kaski
    http://arxiv.org/abs/2106.04193v1

    • [stat.ML]The Future is Log-Gaussian: ResNets and Their Infinite-Depth-and-Width Limit at Initialization
    Mufan Bill Li, Mihai Nica, Daniel M. Roy
    http://arxiv.org/abs/2106.04013v1

    • [stat.ML]Weighted Sparse Subspace Representation: A Unified Framework for Subspace Clustering, Constrained Clustering, and Active Learning
    Hankui Peng, Nicos G. Pavlidis
    http://arxiv.org/abs/2106.04330v1