cs.AI - 人工智能

    cs.AR - 硬件体系结构 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DL - 数字图书馆 cs.DS - 数据结构与算法 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.MA - 多代理系统 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.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.SY - 系统和控制 math.OC - 优化与控制 math.PR - 概率 q-bio.QM - 定量方法 q-fin.GN - 通用财务 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

    • [cs.AI]”It’s Unwieldy and It Takes a Lot of Time.” Challenges and Opportunities for Creating Agents in Commercial Games
    • [cs.AI]A Benchmark for Multi-UAV Task Assignment of an Extended Team Orienteering Problem
    • [cs.AI]Cross-modal Knowledge Reasoning for Knowledge-based Visual Question Answering
    • [cs.AI]Landscape of Machine Implemented Ethics
    • [cs.AI]Machine Reasoning Explainability
    • [cs.AI]More is not Always Better: The Negative Impact of A-box Materialization on RDF2vec Knowledge Graph Embeddings
    • [cs.AI]PYCSP3: Modeling Combinatorial Constrained Problems in Python
    • [cs.AI]Solving the single-track train scheduling problem via Deep Reinforcement Learning
    • [cs.AI]Visual Causality Analysis of Event Sequence Data
    • [cs.AI]XCSP3-core: A Format for Representing Constraint Satisfaction/Optimization Problems
    • [cs.AR]Direct CMOS Implementation of Neuromorphic Temporal Neural Networks for Sensory Processing
    • [cs.CL]Extracting Semantic Concepts and Relations from Scientific Publications by Using Deep Learning
    • [cs.CL]PNEL: Pointer Network based End-To-End Entity Linking over Knowledge Graphs
    • [cs.CL]SuperPAL: Supervised Proposition ALignment for Multi-Document Summarization and Derivative Sub-Tasks
    • [cs.CL]Temporal Mental Health Dynamics on Social Media
    • [cs.CR]Efficient Evasion Attacks to Graph Neural Networks via Influence Function
    • [cs.CR]POSEIDON:Privacy-Preserving Federated Neural Network Learning
    • [cs.CR]Reinforcement Learning-based Black-Box Evasion Attacks to Link Prediction in Dynamic Graphs
    • [cs.CR]Sampling Attacks: Amplification of Membership Inference Attacks by Repeated Queries
    • [cs.CV]3D-DEEP: 3-Dimensional Deep-learning based on elevation patterns forroad scene interpretation
    • [cs.CV]A Framework For Contrastive Self-Supervised Learning And Designing A New Approach
    • [cs.CV]A High-Level Description and Performance Evaluation of Pupil Invisible
    • [cs.CV]A Primer on Motion Capture with Deep Learning: Principles, Pitfalls and Perspectives
    • [cs.CV]A Review of Single-Source Deep Unsupervised Visual Domain Adaptation
    • [cs.CV]A Short Review on Data Modelling for Vector Fields
    • [cs.CV]Active Deep Densely Connected Convolutional Network for Hyperspectral Image Classification
    • [cs.CV]Automatic Radish Wilt Detection Using Image Processing Based Techniques and Machine Learning Algorithm
    • [cs.CV]Deep Ice Layer Tracking and Thickness Estimation using Fully Convolutional Networks
    • [cs.CV]Distinctive 3D local deep descriptors
    • [cs.CV]DropLeaf: a precision farming smartphone application for measuring pesticide spraying methods
    • [cs.CV]GIF: Generative Interpretable Faces
    • [cs.CV]Generalized Zero-Shot Learning via VAE-Conditioned Generative Flow
    • [cs.CV]Heatmap Regression via Randomized Rounding
    • [cs.CV]Inducing Predictive Uncertainty Estimation for Face Recognition
    • [cs.CV]LaDDer: Latent Data Distribution Modelling with a Generative Prior
    • [cs.CV]LiftFormer: 3D Human Pose Estimation using attention models
    • [cs.CV]LodoNet: A Deep Neural Network with 2D Keypoint Matchingfor 3D LiDAR Odometry Estimation
    • [cs.CV]MORPH-DSLAM: Model Order Reduction for PHysics-based Deformable SLAM
    • [cs.CV]Multi-channel Transformers for Multi-articulatory Sign Language Translation
    • [cs.CV]Multimodal Aggregation Approach for Memory Vision-Voice Indoor Navigation with Meta-Learning
    • [cs.CV]Object Detection-Based Variable Quantization Processing
    • [cs.CV]Online Multi-Object Tracking and Segmentation with GMPHD Filter and Simple Affinity Fusion
    • [cs.CV]PIDNet: An Efficient Network for Dynamic Pedestrian Intrusion Detection
    • [cs.CV]Personalization in Human Activity Recognition
    • [cs.CV]RangeRCNN: Towards Fast and Accurate 3D Object Detection with Range Image Representation
    • [cs.CV]Semantics-aware Adaptive Knowledge Distillation for Sensor-to-Vision Action Recognition
    • [cs.CV]Temporal Continuity Based Unsupervised Learning for Person Re-Identification
    • [cs.CV]To augment or not to augment? Data augmentation in user identification based on motion sensors
    • [cs.CV]Uncovering Hidden Challenges in Query-Based Video Moment Retrieval
    • [cs.CV]Utilizing Satellite Imagery Datasets and Machine Learning Data Models to Evaluate Infrastructure Change in Undeveloped Regions
    • [cs.CY]An Experience of Introducing Primary School Children to Programming using Ozobots
    • [cs.CY]Bubble Storytelling with Automated Animation: A Brexit Hashtag Activism Case Study
    • [cs.CY]Continuous Artificial Prediction Markets as a Syndromic Surveillance Technique
    • [cs.CY]Entropy of Co-Enrolment Networks Reveal Disparities in High School STEM Participation
    • [cs.CY]Explainability Case Studies
    • [cs.CY]High-Resolution Poverty Maps in Sub-Saharan Africa
    • [cs.CY]LoRaWAN Temperature Sensors for Local Government Asset Management
    • [cs.CY]Return to Bali
    • [cs.CY]Suspect AI: Vibraimage, Emotion Recognition Technology, and Algorithmic Opacity
    • [cs.DB]Tensor Relational Algebra for Machine Learning System Design
    • [cs.DC]Design and Simulation of a Hybrid Architecture for Edge Computing in 5G and Beyond
    • [cs.DC]Federated Edge Learning : Design Issues and Challenges
    • [cs.DC]GOSH: Embedding Big Graphs on Small Hardware
    • [cs.DC]LoCUS: A multi-robot loss-tolerant algorithm for surveying volcanic plumes
    • [cs.DC]Railgun: streaming windows for mission critical systems
    • [cs.DC]WorkflowHub: Community Framework for Enabling Scientific Workflow Research and Development — Technical Report
    • [cs.DL]Mapping Researchers with PeopleMap
    • [cs.DS]Localized Topological Simplification of Scalar Data
    • [cs.HC]MultiSegVA: Using Visual Analytics to Segment Biologging Time Series on Multiple Scales
    • [cs.HC]PlotThread: Creating Expressive Storyline Visualizations using Reinforcement Learning
    • [cs.HC]Toward Multimodal Modeling of Emotional Expressiveness
    • [cs.IR]From Clicks to Conversions: Recommendation for long-term reward
    • [cs.IT]A Concentration of Measure Approach to Correlated Graph Matching
    • [cs.IT]Centralized vs Decentralized Targeted Brute-Force Attacks: Guessing with Side-Information
    • [cs.IT]Ergodic Secrecy Capacity of RIS-Assisted Communication Systems in the Presence of Discrete Phase Shifts and Multiple Eavesdroppers
    • [cs.IT]Fast Grant Learning-Based Approach for Machine Type Communications with NOMA
    • [cs.IT]Large Intelligent Surface Aided Physical Layer Security Transmission
    • [cs.IT]Pecoding and Scheduling for AoI Minimization in MIMO Broadcast Channels
    • [cs.IT]Precise Expression for the Algorithmic Information Distance
    • [cs.IT]Robust and Secure Communications in Intelligent Reflecting Surface Assisted NOMA networks
    • [cs.IT]Secrecy Outage Analysis of Two-Hop Decode-and-Forward Mixed RF/UWOC Systems
    • [cs.LG]A Mathematical Introduction to Generative Adversarial Nets (GAN)
    • [cs.LG]A Survey of Deep Active Learning
    • [cs.LG]Advancing from Predictive Maintenance to Intelligent Maintenance with AI and IIoT
    • [cs.LG]Adversarial Shapley Value Experience Replay for Task-Free Continual Learning
    • [cs.LG]An in-depth comparison of methods handling mixed-attribute data for general fuzzy min-max neural network
    • [cs.LG]Boosting House Price Predictions using Geo-Spatial Network Embedding
    • [cs.LG]Boosting share routing for multi-task learning
    • [cs.LG]Developing Constrained Neural Units Over Time
    • [cs.LG]Distance Encoding — Design Provably More Powerful GNNs for Structural Representation Learning
    • [cs.LG]Graph Embedding with Data Uncertainty
    • [cs.LG]Improved Weighted Random Forest for Classification Problems
    • [cs.LG]Learning Nash Equilibria in Zero-Sum Stochastic Games via Entropy-Regularized Policy Approximation
    • [cs.LG]Learning explanations that are hard to vary
    • [cs.LG]Performance-Agnostic Fusion of Probabilistic Classifier Outputs
    • [cs.LG]Rank-one partitioning: formalization, illustrative examples, and a new cluster enhancing strategy
    • [cs.LG]Scaling Up Deep Neural Network Optimization for Edge Inference
    • [cs.LG]Training Deep Neural Networks with Constrained Learning Parameters
    • [cs.LG]Unsupervised Domain Adaptation with Progressive Adaptation of Subspaces
    • [cs.MA]Finding Core Members of Cooperative Games using Agent-Based Modeling
    • [cs.MA]Needs-driven Heterogeneous Multi-Robot Cooperation in Rescue Missions
    • [cs.NE]A Deep 2-Dimensional Dynamical Spiking Neuronal Network for Temporal Encoding trained with STDP
    • [cs.NE]Adaptation in a System Metamodel for Evolutionary Computation
    • [cs.NE]The Computational Capacity of Memristor Reservoirs
    • [cs.NI]On the Benefits of Multi-hop Communication for Indoor 60 GHz Wireless Networks
    • [cs.NI]Under Water Waste Cleaning by Mobile Edge Computing and Intelligent Image Processing Based Robotic Fish
    • [cs.RO]A Samplable Multimodal Observation Model for Global Localization and Kidnapping
    • [cs.RO]Accurate Prediction and Estimation of 3D-Repetitive-Trajectories using Kalman Filter, Machine Learning and Curve-Fitting Method
    • [cs.RO]Autonomous Formula Racecar: Overall System Design and Experimental Validation
    • [cs.RO]Flightmare: A Flexible Quadrotor Simulator
    • [cs.RO]Gaussian Process Gradient Maps for Loop-Closure Detection in Unstructured Planetary Environments
    • [cs.RO]Intelligent Hotel ROS-based Service Robot
    • [cs.SE]Theodolite: Scalability Benchmarking of Distributed Stream Processing Engines
    • [cs.SI]Dynamics of node influence in network growth models
    • [cs.SI]Internal migration and mobile communication patterns among pairs with strong ties
    • [cs.SI]Random Surfing Revisited: Generalizing PageRank’s Teleportation Model
    • [cs.SI]Structural balance of alliance and rivalry networks in international relations
    • [cs.SI]Top-k Socio-Spatial Co-engaged Location Selection for Social Users
    • [cs.SI]Twitter Corpus of the #BlackLivesMatter Movement And Counter Protests: 2013 to 2020
    • [cs.SI]Twitter Interaction to Analyze Covid-19 Impact in Ghana, Africa from March to July
    • [cs.SI]Using Graphlet Spectrograms for Temporal Pattern Analysis of Virus-Research Collaboration Networks
    • [cs.SI]Using Social Networks to Improve Group Transition Prediction in Professional Sports
    • [econ.EM]Time-Varying Parameters as Ridge Regressions
    • [eess.AS]Neural Architecture Search For Keyword Spotting
    • [eess.AS]Parallel Rescoring with Transformer for Streaming On-Device Speech Recognition
    • [eess.IV]Data and Image Prior Integration for Image Reconstruction Using Consensus Equilibrium
    • [eess.IV]End-to-End Hyperspectral-Depth Imaging with Learned Diffractive Optics
    • [eess.IV]Image Reconstruction of Static and Dynamic Scenes through Anisoplanatic Turbulence
    • [eess.IV]Image Super-Resolution using Explicit Perceptual Loss
    • [eess.IV]On The Usage Of Average Hausdorff Distance For Segmentation Performance Assessment: Hidden Bias When Used For Ranking
    • [eess.IV]PiNet: Deep Structure Learning using Feature Extraction in Trained Projection Space
    • [eess.IV]Quality-aware semi-supervised learning for CMR segmentation
    • [eess.IV]Recognition Oriented Iris Image Quality Assessment in the Feature Space
    • [eess.IV]Semantic Segmentation of Neuronal Bodies in Fluorescence Microscopy Using a 2D+3D CNN Training Strategy with Sparsely Annotated Data
    • [eess.SY]Market Model for Demand Response under Block Rate Pricing
    • [eess.SY]Optimal Bayesian Quickest Detection for Hidden Markov Models and Structured Generalisations
    • [eess.SY]Transaction Pricing for Maximizing Throughput in a Sharded Blockchain Ledger
    • [math.OC]Linear-Quadratic Zero-Sum Mean-Field Type Games: Optimality Conditions and Policy Optimization
    • [math.PR]Edge statistics of large dimensional deformed rectangular matrices
    • [math.PR]Large-dimensional Central Limit Theorem with Fourth-moment Error Bounds on Convex Sets and Balls
    • [math.PR]Statistical analysis of the non-ergodic fractional Ornstein-Uhlenbeck process with periodic mean
    • [q-bio.QM]Unsupervised and Supervised Structure Learning for Protein Contact Prediction
    • [q-fin.GN]Contingent Convertible Bonds in Financial Networks
    • [quant-ph]Universal Approximation Property of Quantum Feature Map
    • [stat.AP]A Comparative Study of Parametric Regression Models to Detect Breakpoint in Traffic Fundamental Diagram
    • [stat.AP]Application of the Cox Regression Model for Analysis of Railway Safety Performance
    • [stat.AP]Variable selection in social-environmental data: Sparse regression and tree ensemble machine learning approaches
    • [stat.CO]Adaptive Path Sampling in Metastable Posterior Distributions
    • [stat.CO]diproperm: An R Package for the DiProPerm Test
    • [stat.ME]Accounting for correlated horizontal pleiotropy in two-sample Mendelian randomization using correlated instrumental variants
    • [stat.ME]Characterizing the Probability Law on Time Until Core Damage With PRA
    • [stat.ME]Design and Analysis of Switchback Experiments
    • [stat.ME]Informative Goodness-of-Fit for Multivariate Distributions
    • [stat.ME]Invited Discussion of “A Unified Framework for De-Duplication and Population Size Estimation”
    • [stat.ML]Curb Your Normality: On the Quality Requirements of Demand Prediction for Dynamic Public Transport
    • [stat.ML]InClass Nets: Independent Classifier Networks for Nonparametric Estimation of Conditional Independence Mixture Models and Unsupervised Classification
    • [stat.ML]Random Forest (RF) Kernel for Regression, Classification and Survival
    • [stat.ML]Semi-Supervised Empirical Risk Minimization: When can unlabeled data improve prediction
    • [stat.ML]Stochastic Graph Recurrent Neural Network
    • [stat.ML]Uncertainty quantification for Markov Random Fields
    • [stat.ML]Variational Mixture of Normalizing Flows

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    • [cs.AI]“It’s Unwieldy and It Takes a Lot of Time.” Challenges and Opportunities for Creating Agents in Commercial Games
    Mikhail Jacob, Sam Devlin, Katja Hofmann
    http://arxiv.org/abs/2009.00541v1

    • [cs.AI]A Benchmark for Multi-UAV Task Assignment of an Extended Team Orienteering Problem
    Kun Xiao, Junqi Lu, Ying Nie, Lan Ma, Xiangke Wang, Guohui Wang
    http://arxiv.org/abs/2009.00363v1

    • [cs.AI]Cross-modal Knowledge Reasoning for Knowledge-based Visual Question Answering
    Jing Yu, Zihao Zhu, Yujing Wang, Weifeng Zhang, Yue Hu, Jianlong Tan
    http://arxiv.org/abs/2009.00145v1

    • [cs.AI]Landscape of Machine Implemented Ethics
    Vivek Nallur
    http://arxiv.org/abs/2009.00335v1

    • [cs.AI]Machine Reasoning Explainability
    Kristijonas Cyras, Ramamurthy Badrinath, Swarup Kumar Mohalik, Anusha Mujumdar, Alexandros Nikou, Alessandro Previti, Vaishnavi Sundararajan, Aneta Vulgarakis Feljan
    http://arxiv.org/abs/2009.00418v1

    • [cs.AI]More is not Always Better: The Negative Impact of A-box Materialization on RDF2vec Knowledge Graph Embeddings
    Andreea Iana, Heiko Paulheim
    http://arxiv.org/abs/2009.00318v1

    • [cs.AI]PYCSP3: Modeling Combinatorial Constrained Problems in Python
    Christophe Lecoutre, Nicolas Szczepanski
    http://arxiv.org/abs/2009.00326v1

    • [cs.AI]Solving the single-track train scheduling problem via Deep Reinforcement Learning
    Valerio Agasucci, Giorgio Grani, Leonardo Lamorgese
    http://arxiv.org/abs/2009.00433v1

    • [cs.AI]Visual Causality Analysis of Event Sequence Data
    Zhuochen Jin, Shunan Guo, Nan Chen, Daniel Weiskopf, David Gotz, Nan Cao
    http://arxiv.org/abs/2009.00219v1

    • [cs.AI]XCSP3-core: A Format for Representing Constraint Satisfaction/Optimization Problems
    Frédéric Boussemart, Christophe Lecoutre, Gilles Audemard, Cédric Piette
    http://arxiv.org/abs/2009.00514v1

    • [cs.AR]Direct CMOS Implementation of Neuromorphic Temporal Neural Networks for Sensory Processing
    Harideep Nair, John Paul Shen, James E. Smith
    http://arxiv.org/abs/2009.00457v1

    • [cs.CL]Extracting Semantic Concepts and Relations from Scientific Publications by Using Deep Learning
    Fatima N. AL-Aswadi, Huah Yong Chan, Keng Hoon Gan
    http://arxiv.org/abs/2009.00331v1

    • [cs.CL]PNEL: Pointer Network based End-To-End Entity Linking over Knowledge Graphs
    Debayan Banerjee, Debanjan Chaudhuri, Mohnish Dubey, Jens Lehmann
    http://arxiv.org/abs/2009.00106v1

    • [cs.CL]SuperPAL: Supervised Proposition ALignment for Multi-Document Summarization and Derivative Sub-Tasks
    Ori Ernst, Ori Shapira, Ramakanth Pasunuru, Michael Lepioshkin, Jacob Goldberger, Mohit Bansal, Ido Dagan
    http://arxiv.org/abs/2009.00590v1

    • [cs.CL]Temporal Mental Health Dynamics on Social Media
    Tom Tabak, Matthew Purver
    http://arxiv.org/abs/2008.13121v2

    • [cs.CR]Efficient Evasion Attacks to Graph Neural Networks via Influence Function
    Binghui Wang, Tianxiang Zhou, Minhua Lin, Pan Zhou, Ang Li, Meng Pang, Cai Fu, Hai Li, Yiran Chen
    http://arxiv.org/abs/2009.00203v1

    • [cs.CR]POSEIDON:Privacy-Preserving Federated Neural Network Learning
    Sinem Sav, Apostolos Pyrgelis, Juan R. Troncoso-Pastoriza, David Froelicher, Jean-Philippe Bossuat, Joao Sa Sousa, Jean-Pierre Hubaux
    http://arxiv.org/abs/2009.00349v1

    • [cs.CR]Reinforcement Learning-based Black-Box Evasion Attacks to Link Prediction in Dynamic Graphs
    Houxiang Fan, Binghui Wang, Pan Zhou, Ang Li, Meng Pang, Zichuan Xu, Cai Fu, Hai Li, Yiran Chen
    http://arxiv.org/abs/2009.00163v1

    • [cs.CR]Sampling Attacks: Amplification of Membership Inference Attacks by Repeated Queries
    Shadi Rahimian, Tribhuvanesh Orekondy, Mario Fritz
    http://arxiv.org/abs/2009.00395v1

    • [cs.CV]3D-DEEP: 3-Dimensional Deep-learning based on elevation patterns forroad scene interpretation
    A. Hernández, S. Woo, H. Corrales, I. Parra, E. Kim, D. F. Llorca, M. A. Sotelo
    http://arxiv.org/abs/2009.00330v1

    • [cs.CV]A Framework For Contrastive Self-Supervised Learning And Designing A New Approach
    William Falcon, Kyunghyun Cho
    http://arxiv.org/abs/2009.00104v1

    • [cs.CV]A High-Level Description and Performance Evaluation of Pupil Invisible
    Marc Tonsen, Chris Kay Baumann, Kai Dierkes
    http://arxiv.org/abs/2009.00508v1

    • [cs.CV]A Primer on Motion Capture with Deep Learning: Principles, Pitfalls and Perspectives
    Alexander Mathis, Steffen Schneider, Jessy Lauer, Mackenzie W. Mathis
    http://arxiv.org/abs/2009.00564v1

    • [cs.CV]A Review of Single-Source Deep Unsupervised Visual Domain Adaptation
    Sicheng Zhao, Xiangyu Yue, Shanghang Zhang, Bo Li, Han Zhao, Bichen Wu, Ravi Krishna, Joseph E. Gonzalez, Alberto L. Sangiovanni-Vincentelli, Sanjit A. Seshia, Kurt Keutzer
    http://arxiv.org/abs/2009.00155v1

    • [cs.CV]A Short Review on Data Modelling for Vector Fields
    Jun Li, Wanrong Hong, Yusheng Xiang
    http://arxiv.org/abs/2009.00577v1

    • [cs.CV]Active Deep Densely Connected Convolutional Network for Hyperspectral Image Classification
    Bing Liu, Anzhu Yu, Pengqiang Zhang, Lei Ding, Wenyue Guo, Kuiliang Gao, Xibing Zuo
    http://arxiv.org/abs/2009.00320v1

    • [cs.CV]Automatic Radish Wilt Detection Using Image Processing Based Techniques and Machine Learning Algorithm
    Asif Ashraf Patankar, Hyeonjoon Moon
    http://arxiv.org/abs/2009.00173v1

    • [cs.CV]Deep Ice Layer Tracking and Thickness Estimation using Fully Convolutional Networks
    Maryam Rahnemoonfar, Debvrat Varshney, Masoud Yari, John Paden
    http://arxiv.org/abs/2009.00191v1

    • [cs.CV]Distinctive 3D local deep descriptors
    Fabio Poiesi, Davide Boscaini
    http://arxiv.org/abs/2009.00258v1

    • [cs.CV]DropLeaf: a precision farming smartphone application for measuring pesticide spraying methods
    Bruno Brandoli, Gabriel Spadon, Travis Esau, Patrick Hennessy, Andre C. P. L. Carvalho, Jose F. Rodrigues-Jr, Sihem Amer-Yahia
    http://arxiv.org/abs/2009.00453v1

    • [cs.CV]GIF: Generative Interpretable Faces
    Partha Ghosh, Pravir Singh Gupta, Roy Uziel, Anurag Ranjan, Michael Black, Timo Bolkart
    http://arxiv.org/abs/2009.00149v1

    • [cs.CV]Generalized Zero-Shot Learning via VAE-Conditioned Generative Flow
    Yu-Chao Gu, Le Zhang, Yun Liu, Shao-Ping Lu, Ming-Ming Cheng
    http://arxiv.org/abs/2009.00303v1

    • [cs.CV]Heatmap Regression via Randomized Rounding
    Baosheng Yu, Dacheng Tao
    http://arxiv.org/abs/2009.00225v1

    • [cs.CV]Inducing Predictive Uncertainty Estimation for Face Recognition
    Weidi Xie, Jeffrey Byrne, Andrew Zisserman
    http://arxiv.org/abs/2009.00603v1

    • [cs.CV]LaDDer: Latent Data Distribution Modelling with a Generative Prior
    Shuyu Lin, Ronald Clark
    http://arxiv.org/abs/2009.00088v1

    • [cs.CV]LiftFormer: 3D Human Pose Estimation using attention models
    Adrian Llopart
    http://arxiv.org/abs/2009.00348v1

    • [cs.CV]LodoNet: A Deep Neural Network with 2D Keypoint Matchingfor 3D LiDAR Odometry Estimation
    Ce Zheng, Yecheng Lyu, Ming Li, Ziming Zhang
    http://arxiv.org/abs/2009.00164v1

    • [cs.CV]MORPH-DSLAM: Model Order Reduction for PHysics-based Deformable SLAM
    Alberto Badias, Iciar Alfaro, David Gonzalez, Francisco Chinesta, Elias Cueto
    http://arxiv.org/abs/2009.00576v1

    • [cs.CV]Multi-channel Transformers for Multi-articulatory Sign Language Translation
    Necati Cihan Camgoz, Oscar Koller, Simon Hadfield, Richard Bowden
    http://arxiv.org/abs/2009.00299v1

    • [cs.CV]Multimodal Aggregation Approach for Memory Vision-Voice Indoor Navigation with Meta-Learning
    Liqi Yan, Dongfang Liu, Yaoxian Song, Changbin Yu
    http://arxiv.org/abs/2009.00402v1

    • [cs.CV]Object Detection-Based Variable Quantization Processing
    Likun Liu, Hua Qi
    http://arxiv.org/abs/2009.00189v1

    • [cs.CV]Online Multi-Object Tracking and Segmentation with GMPHD Filter and Simple Affinity Fusion
    Young-min Song, Moongu Jeon
    http://arxiv.org/abs/2009.00100v1

    • [cs.CV]PIDNet: An Efficient Network for Dynamic Pedestrian Intrusion Detection
    Jingchen Sun, Jiming Chen, Tao Chen, Jiayuan Fan, Shibo He
    http://arxiv.org/abs/2009.00312v1

    • [cs.CV]Personalization in Human Activity Recognition
    Anna Ferrari, Daniela Micucci, Marco Mobilio, Paolo Napoletano
    http://arxiv.org/abs/2009.00268v1

    • [cs.CV]RangeRCNN: Towards Fast and Accurate 3D Object Detection with Range Image Representation
    Zhidong Liang, Ming Zhang, Zehan Zhang, Xian Zhao, Shiliang Pu
    http://arxiv.org/abs/2009.00206v1

    • [cs.CV]Semantics-aware Adaptive Knowledge Distillation for Sensor-to-Vision Action Recognition
    Yang Liu, Guanbin Li, Liang Lin
    http://arxiv.org/abs/2009.00210v1

    • [cs.CV]Temporal Continuity Based Unsupervised Learning for Person Re-Identification
    Usman Ali, Bayram Bayramli, Hongtao Lu
    http://arxiv.org/abs/2009.00242v1

    • [cs.CV]To augment or not to augment? Data augmentation in user identification based on motion sensors
    Cezara Benegui, Radu Tudor Ionescu
    http://arxiv.org/abs/2009.00300v1

    • [cs.CV]Uncovering Hidden Challenges in Query-Based Video Moment Retrieval
    Mayu Otani, Yuta Nakashima, Esa Rahtu, Janne Heikkilä
    http://arxiv.org/abs/2009.00325v1

    • [cs.CV]Utilizing Satellite Imagery Datasets and Machine Learning Data Models to Evaluate Infrastructure Change in Undeveloped Regions
    Kyle McCullough, Andrew Feng, Meida Chen, Ryan McAlinden
    http://arxiv.org/abs/2009.00185v1

    • [cs.CY]An Experience of Introducing Primary School Children to Programming using Ozobots
    Nina Körber, Lisa Bailey, Gordon Fraser, Barbara Sabitzer, Marina Rottenhofer
    http://arxiv.org/abs/2008.13566v1

    • [cs.CY]Bubble Storytelling with Automated Animation: A Brexit Hashtag Activism Case Study
    Noptanit Chotisarn, Junhua Lu, Libinzi Ma, Jingli Xu, Linhao Meng, Bingru Lin, Ying Xu, Xiaonan Luo, Wei Chen
    http://arxiv.org/abs/2009.00549v1

    • [cs.CY]Continuous Artificial Prediction Markets as a Syndromic Surveillance Technique
    Fatemeh Jahedpari
    http://arxiv.org/abs/2009.00394v1

    • [cs.CY]Entropy of Co-Enrolment Networks Reveal Disparities in High School STEM Participation
    Steven Martin Turnbull, Dion R. J. O’Neale
    http://arxiv.org/abs/2008.13575v1

    • [cs.CY]Explainability Case Studies
    Ben Zevenbergen, Allison Woodruff, Patrick Gage Kelley
    http://arxiv.org/abs/2009.00246v1

    • [cs.CY]High-Resolution Poverty Maps in Sub-Saharan Africa
    Kamwoo Lee, Jeanine Braithwaite
    http://arxiv.org/abs/2009.00544v1

    • [cs.CY]LoRaWAN Temperature Sensors for Local Government Asset Management
    Jack Downes
    http://arxiv.org/abs/2009.00172v1

    • [cs.CY]Return to Bali
    Marc Böhlen, Wawan Sujarwo
    http://arxiv.org/abs/2009.00597v1

    • [cs.CY]Suspect AI: Vibraimage, Emotion Recognition Technology, and Algorithmic Opacity
    James Wright
    http://arxiv.org/abs/2009.00502v1

    • [cs.DB]Tensor Relational Algebra for Machine Learning System Design
    Binhang Yuan, Dimitrije Jankov, Jia Zou, Yuxin Tang, Daniel Bourgeois, Chris Jermaine
    http://arxiv.org/abs/2009.00524v1

    • [cs.DC]Design and Simulation of a Hybrid Architecture for Edge Computing in 5G and Beyond
    Hamed Rahimi, Yvan Picaud, Salvatore Costanzo, Giyyarpuram Madhusudan, Olivier Boissier, kamal Deep Singh
    http://arxiv.org/abs/2009.00041v1

    • [cs.DC]Federated Edge Learning : Design Issues and Challenges
    Afaf Taïk, Soumaya Cherkaoui
    http://arxiv.org/abs/2009.00081v1

    • [cs.DC]GOSH: Embedding Big Graphs on Small Hardware
    Taha Atahan Akyildiz, Amro Alabsi Aljundi, Kamer Kaya
    http://arxiv.org/abs/2008.12336v2

    • [cs.DC]LoCUS: A multi-robot loss-tolerant algorithm for surveying volcanic plumes
    John Erickson, Abhinav Aggarwal, G. Matthew Fricke, Melanie E. Moses
    http://arxiv.org/abs/2009.00156v1

    • [cs.DC]Railgun: streaming windows for mission critical systems
    João Oliveirinha, Ana Sofia Gomes, Pedro Cardoso, Pedro Bizarro
    http://arxiv.org/abs/2009.00361v1

    • [cs.DC]WorkflowHub: Community Framework for Enabling Scientific Workflow Research and Development — Technical Report
    Rafael Ferreira da Silva, Loïc Pottier, Tainã Coleman, Ewa Deelman, Henri Casanova
    http://arxiv.org/abs/2009.00250v1

    • [cs.DL]Mapping Researchers with PeopleMap
    Jon Saad-Falcon, Omar Shaikh, Zijie J. Wang, Austin P. Wright, Sasha Richardson, Duen Horng Chau
    http://arxiv.org/abs/2009.00091v1

    • [cs.DS]Localized Topological Simplification of Scalar Data
    Jonas Lukasczyk, Christoph Garth, Ross Maciejewski, Julien Tierny
    http://arxiv.org/abs/2009.00083v1

    • [cs.HC]MultiSegVA: Using Visual Analytics to Segment Biologging Time Series on Multiple Scales
    Philipp Meschenmoser, Juri F. Buchmüller, Daniel Seebacher, Martin Wikelski, Daniel A. Keim
    http://arxiv.org/abs/2009.00548v1

    • [cs.HC]PlotThread: Creating Expressive Storyline Visualizations using Reinforcement Learning
    Tan Tang, Renzhong Li, Xinke Wu, Shuhan Liu, Johannes Knittel, Steffen Koch, Thomas Ertl, Lingyun Yu, Peiran Ren, Yingcai Wu
    http://arxiv.org/abs/2009.00249v1

    • [cs.HC]Toward Multimodal Modeling of Emotional Expressiveness
    Victoria Lin, Jeffrey M. Girard, Michael A. Sayette, Louis-Philippe Morency
    http://arxiv.org/abs/2009.00001v1

    • [cs.IR]From Clicks to Conversions: Recommendation for long-term reward
    Philomène Chagniot, Flavian Vasile, David Rohde
    http://arxiv.org/abs/2009.00497v1

    • [cs.IT]A Concentration of Measure Approach to Correlated Graph Matching
    Farhad Shirani, Siddharth Garg, Elza Erkip
    http://arxiv.org/abs/2009.00467v1

    • [cs.IT]Centralized vs Decentralized Targeted Brute-Force Attacks: Guessing with Side-Information
    Salman Salamatian, Wasim Huleihel, Ahmad Beirami, Asaf Cohen, Muriel Médard
    http://arxiv.org/abs/2008.12823v1

    • [cs.IT]Ergodic Secrecy Capacity of RIS-Assisted Communication Systems in the Presence of Discrete Phase Shifts and Multiple Eavesdroppers
    Peng Xu, Gaojie Chen, Gaofeng Pan, Marco Di Renzo
    http://arxiv.org/abs/2009.00517v1

    • [cs.IT]Fast Grant Learning-Based Approach for Machine Type Communications with NOMA
    Manal El Tanab, Walaa Hamouda
    http://arxiv.org/abs/2009.00105v1

    • [cs.IT]Large Intelligent Surface Aided Physical Layer Security Transmission
    Biqian Feng, Yongpeng Wu, Mengfan Zheng, Xiang-Gen Xia, Yongjian Wang, Chengshan Xiao
    http://arxiv.org/abs/2009.00473v1

    • [cs.IT]Pecoding and Scheduling for AoI Minimization in MIMO Broadcast Channels
    Songtao Feng, Jing Yang
    http://arxiv.org/abs/2009.00171v1

    • [cs.IT]Precise Expression for the Algorithmic Information Distance
    Bruno Bauwens
    http://arxiv.org/abs/2009.00469v1

    • [cs.IT]Robust and Secure Communications in Intelligent Reflecting Surface Assisted NOMA networks
    Zheng Zhang, Lu Lv, Qingqing Wu, Hao Deng, Jian Chen
    http://arxiv.org/abs/2009.00267v1

    • [cs.IT]Secrecy Outage Analysis of Two-Hop Decode-and-Forward Mixed RF/UWOC Systems
    Yi Lou, Ruofan Sun, Julian Cheng, Donghu Nie, Gang Qiao
    http://arxiv.org/abs/2009.00328v1

    • [cs.LG]A Mathematical Introduction to Generative Adversarial Nets (GAN)
    Yang Wang
    http://arxiv.org/abs/2009.00169v1

    • [cs.LG]A Survey of Deep Active Learning
    Pengzhen Ren, Yun Xiao, Xiaojun Chang, Po-Yao Huang, Zhihui Li, Xiaojiang Chen, Xin Wang
    http://arxiv.org/abs/2009.00236v1

    • [cs.LG]Advancing from Predictive Maintenance to Intelligent Maintenance with AI and IIoT
    Haining Zheng, Antonio R. Paiva, Chris S. Gurciullo
    http://arxiv.org/abs/2009.00351v1

    • [cs.LG]Adversarial Shapley Value Experience Replay for Task-Free Continual Learning
    Zheda Mai, Dongsub Shim, Jihwan Jeong, Scott Sanner, Hyunwoo Kim, Jongseong Jang
    http://arxiv.org/abs/2009.00093v1

    • [cs.LG]An in-depth comparison of methods handling mixed-attribute data for general fuzzy min-max neural network
    Thanh Tung Khuat, Bogdan Gabrys
    http://arxiv.org/abs/2009.00237v1

    • [cs.LG]Boosting House Price Predictions using Geo-Spatial Network Embedding
    Sarkar Snigdha Sarathi Das, Mohammed Eunus Ali, Yuan-Fang Li, Yong-Bin Kang, Timos Sellis
    http://arxiv.org/abs/2009.00254v1

    • [cs.LG]Boosting share routing for multi-task learning
    Xiaokai Chen, Xiaoguang Gu, Libo Fu
    http://arxiv.org/abs/2009.00387v1

    • [cs.LG]Developing Constrained Neural Units Over Time
    Alessandro Betti, Marco Gori, Simone Marullo, Stefano Melacci
    http://arxiv.org/abs/2009.00296v1

    • [cs.LG]Distance Encoding — Design Provably More Powerful GNNs for Structural Representation Learning
    Pan Li, Yanbang Wang, Hongwei Wang, Jure Leskovec
    http://arxiv.org/abs/2009.00142v1

    • [cs.LG]Graph Embedding with Data Uncertainty
    Firas Laakom, Jenni Raitoharju, Nikolaos Passalis, Alexandros Iosifidis, Moncef Gabbouj
    http://arxiv.org/abs/2009.00505v1

    • [cs.LG]Improved Weighted Random Forest for Classification Problems
    Mohsen Shahhosseini, Guiping Hu
    http://arxiv.org/abs/2009.00534v1

    • [cs.LG]Learning Nash Equilibria in Zero-Sum Stochastic Games via Entropy-Regularized Policy Approximation
    Qifan Zhang, Yue Guan, Panagiotis Tsiotras
    http://arxiv.org/abs/2009.00162v1

    • [cs.LG]Learning explanations that are hard to vary
    Giambattista Parascandolo, Alexander Neitz, Antonio Orvieto, Luigi Gresele, Bernhard Schölkopf
    http://arxiv.org/abs/2009.00329v1

    • [cs.LG]Performance-Agnostic Fusion of Probabilistic Classifier Outputs
    Jordan F. Masakuna, Simukai W. Utete, Steve Kroon
    http://arxiv.org/abs/2009.00565v1

    • [cs.LG]Rank-one partitioning: formalization, illustrative examples, and a new cluster enhancing strategy
    Charlotte Laclau, Franck Iutzeler, Ievgen Redko
    http://arxiv.org/abs/2009.00365v1

    • [cs.LG]Scaling Up Deep Neural Network Optimization for Edge Inference
    Bingqian Lu, Jianyi Yang, Shaolei Ren
    http://arxiv.org/abs/2009.00278v1

    • [cs.LG]Training Deep Neural Networks with Constrained Learning Parameters
    Prasanna Date, Christopher D. Carothers, John E. Mitchell, James A. Hendler, Malik Magdon-Ismail
    http://arxiv.org/abs/2009.00540v1

    • [cs.LG]Unsupervised Domain Adaptation with Progressive Adaptation of Subspaces
    Weikai Li, Songcan Chen
    http://arxiv.org/abs/2009.00520v1

    • [cs.MA]Finding Core Members of Cooperative Games using Agent-Based Modeling
    Daniele Vernon-Bido, Andrew J. Collins
    http://arxiv.org/abs/2009.00519v1

    • [cs.MA]Needs-driven Heterogeneous Multi-Robot Cooperation in Rescue Missions
    Qin Yang, Ramviyas Parasuraman
    http://arxiv.org/abs/2009.00288v1

    • [cs.NE]A Deep 2-Dimensional Dynamical Spiking Neuronal Network for Temporal Encoding trained with STDP
    Matthew Evanusa, Cornelia Fermuller, Yiannis Aloimonos
    http://arxiv.org/abs/2009.00581v1

    • [cs.NE]Adaptation in a System Metamodel for Evolutionary Computation
    Patrik Christen, Olivier Del Fabbro
    http://arxiv.org/abs/2009.00110v1

    • [cs.NE]The Computational Capacity of Memristor Reservoirs
    Forrest C. Sheldon, Artemy Kolchinsky, Francesco Caravelli
    http://arxiv.org/abs/2009.00112v1

    • [cs.NI]On the Benefits of Multi-hop Communication for Indoor 60 GHz Wireless Networks
    Chanaka Samarathunga, Mohamed Abouelseoud, Kazuyuki Sakoda, Morteza Hashemi
    http://arxiv.org/abs/2009.00205v1

    • [cs.NI]Under Water Waste Cleaning by Mobile Edge Computing and Intelligent Image Processing Based Robotic Fish
    Subhadeep Sahoo, Xiao Han Dong, Zi Qian Liu, Joydeep Sahoo
    http://arxiv.org/abs/2009.00072v1

    • [cs.RO]A Samplable Multimodal Observation Model for Global Localization and Kidnapping
    Runjian Chen, Yue Wang, Huan Yin, Yanmei Jiao, Gamini Dissanayake, Rong Xiong
    http://arxiv.org/abs/2009.00211v1

    • [cs.RO]Accurate Prediction and Estimation of 3D-Repetitive-Trajectories using Kalman Filter, Machine Learning and Curve-Fitting Method
    Aakriti Agrawal, Aashay Bhise, Rohitkumar Arasanipalai, Lima Agnel Tony, Shuvrangshu Jana, Debasish Ghose
    http://arxiv.org/abs/2009.00067v1

    • [cs.RO]Autonomous Formula Racecar: Overall System Design and Experimental Validation
    Hanqing Tian, Jun Ni, Zirui Li, Jibin Hu
    http://arxiv.org/abs/2009.00385v1

    • [cs.RO]Flightmare: A Flexible Quadrotor Simulator
    Yunlong Song, Selim Naji, Elia Kaufmann, Antonio Loquercio, Davide Scaramuzza
    http://arxiv.org/abs/2009.00563v1

    • [cs.RO]Gaussian Process Gradient Maps for Loop-Closure Detection in Unstructured Planetary Environments
    Cedric Le Gentil, Mallikarjuna Vayugundla, Riccardo Giubilato, Wolfgang Stürzl, Teresa Vidal-Calleja, Rudolph Triebel
    http://arxiv.org/abs/2009.00221v1

    • [cs.RO]Intelligent Hotel ROS-based Service Robot
    Yanyu Zhang, Xiu Wang, Xuan Wu, Wenjing Zhang, Meiqian Jiang, Mahmood Al-Khassaweneh
    http://arxiv.org/abs/2009.00594v1

    • [cs.SE]Theodolite: Scalability Benchmarking of Distributed Stream Processing Engines
    Sören Henning, Wilhelm Hasselbring
    http://arxiv.org/abs/2009.00304v1

    • [cs.SI]Dynamics of node influence in network growth models
    Shravika Mittal, Tanmoy Chakraborty, Siddharth Pal
    http://arxiv.org/abs/2009.00235v1

    • [cs.SI]Internal migration and mobile communication patterns among pairs with strong ties
    Mikaela Irene D. Fudolig, Daniel Monsivais, Kunal Bhattacharya, Hang-Hyun Jo, Kimmo Kaski
    http://arxiv.org/abs/2009.00252v1

    • [cs.SI]Random Surfing Revisited: Generalizing PageRank’s Teleportation Model
    Athanasios N. Nikolakopoulos
    http://arxiv.org/abs/2008.12916v2

    • [cs.SI]Structural balance of alliance and rivalry networks in international relations
    Koji Oishi, Kentaro Sakuwa
    http://arxiv.org/abs/2009.00369v1

    • [cs.SI]Top-k Socio-Spatial Co-engaged Location Selection for Social Users
    Nur Al Hasan Haldar, Jianxin Li, Mohammed Eunus Ali, Taotao Cai, Timos Sellis, Mark Reynolds
    http://arxiv.org/abs/2009.00373v1

    • [cs.SI]Twitter Corpus of the #BlackLivesMatter Movement And Counter Protests: 2013 to 2020
    Salvatore Giorgi, Sharath Chandra Guntuku, Muhammad Rahman, McKenzie Himelein-Wachowiak, Amy Kwarteng, Brenda Curtis
    http://arxiv.org/abs/2009.00596v1

    • [cs.SI]Twitter Interaction to Analyze Covid-19 Impact in Ghana, Africa from March to July
    Josimar Chire Saire, Kobby Panford-Quainoo
    http://arxiv.org/abs/2008.12277v2

    • [cs.SI]Using Graphlet Spectrograms for Temporal Pattern Analysis of Virus-Research Collaboration Networks
    Dimitris Floros, Tiancheng Liu, Nikos Pitsianis, Xiaobai Sun
    http://arxiv.org/abs/2009.00477v1

    • [cs.SI]Using Social Networks to Improve Group Transition Prediction in Professional Sports
    Emily J. Evans, Rebecca Jones, Joseph Leung, Benjamin Z. Webb
    http://arxiv.org/abs/2009.00550v1

    • [econ.EM]Time-Varying Parameters as Ridge Regressions
    Philippe Goulet Coulombe
    http://arxiv.org/abs/2009.00401v1

    • [eess.AS]Neural Architecture Search For Keyword Spotting
    Tong Mo, Yakun Yu, Mohammad Salameh, Di Niu, Shangling Jui
    http://arxiv.org/abs/2009.00165v1

    • [eess.AS]Parallel Rescoring with Transformer for Streaming On-Device Speech Recognition
    Wei Li, James Qin, Chung-Cheng Chiu, Ruoming Pang, Yanzhang He
    http://arxiv.org/abs/2008.13093v2

    • [eess.IV]Data and Image Prior Integration for Image Reconstruction Using Consensus Equilibrium
    Muhammad Usman Ghani, W. Clem Karl
    http://arxiv.org/abs/2009.00092v1

    • [eess.IV]End-to-End Hyperspectral-Depth Imaging with Learned Diffractive Optics
    Seung-Hwan Baek, Hayato Ikoma, Daniel S. Jeon, Yuqi Li, Wolfgang Heidrich, Gordon Wetzstein, Min H. Kim
    http://arxiv.org/abs/2009.00463v1

    • [eess.IV]Image Reconstruction of Static and Dynamic Scenes through Anisoplanatic Turbulence
    Zhiyuan Mao, Nicholas Chimitt, Stanley Chan
    http://arxiv.org/abs/2009.00071v1

    • [eess.IV]Image Super-Resolution using Explicit Perceptual Loss
    Tomoki Yoshida, Kazutoshi Akita, Muhammad Haris, Norimichi Ukita
    http://arxiv.org/abs/2009.00382v1

    • [eess.IV]On The Usage Of Average Hausdorff Distance For Segmentation Performance Assessment: Hidden Bias When Used For Ranking
    Orhun Utku Aydin, Abdel Aziz Taha, Adam Hilbert, Ahmed A. Khalil, Ivana Galinovic, Jochen B. Fiebach, Dietmar Frey, Vince Istvan Madai
    http://arxiv.org/abs/2009.00215v1

    • [eess.IV]PiNet: Deep Structure Learning using Feature Extraction in Trained Projection Space
    Christoph Angermann, Markus Haltmeier
    http://arxiv.org/abs/2009.00378v1

    • [eess.IV]Quality-aware semi-supervised learning for CMR segmentation
    Bram Ruijsink, Esther Puyol-Anton, Ye Li, Wenja Bai, Eric Kerfoot, Reza Razavi, Andrew P. King
    http://arxiv.org/abs/2009.00584v1

    • [eess.IV]Recognition Oriented Iris Image Quality Assessment in the Feature Space
    Leyuan Wang, Kunbo Zhang, Min Ren, Yunlong Wang, Zhenan Sun
    http://arxiv.org/abs/2009.00294v1

    • [eess.IV]Semantic Segmentation of Neuronal Bodies in Fluorescence Microscopy Using a 2D+3D CNN Training Strategy with Sparsely Annotated Data
    Filippo Maria Castelli, Matteo Roffilli, Giacomo Mazzamuto, Irene Costantini, Ludovico Silvestri, Francesco Saverio Pavone
    http://arxiv.org/abs/2009.00029v1

    • [eess.SY]Market Model for Demand Response under Block Rate Pricing
    Haris Mansoor, Naveed Arshad
    http://arxiv.org/abs/2009.00439v1

    • [eess.SY]Optimal Bayesian Quickest Detection for Hidden Markov Models and Structured Generalisations
    Jasmin James, Jason J. Ford, Jenna Riseley, Timothy L. Molloy
    http://arxiv.org/abs/2009.00150v1

    • [eess.SY]Transaction Pricing for Maximizing Throughput in a Sharded Blockchain Ledger
    James R. Riehl, Jonathan Ward
    http://arxiv.org/abs/2009.00319v1

    • [math.OC]Linear-Quadratic Zero-Sum Mean-Field Type Games: Optimality Conditions and Policy Optimization
    René Carmona, Kenza Hamidouche, Mathieu Laurière, Zongjun Tan
    http://arxiv.org/abs/2009.00578v1

    • [math.PR]Edge statistics of large dimensional deformed rectangular matrices
    Xiucai Ding, Fan Yang
    http://arxiv.org/abs/2009.00389v1

    • [math.PR]Large-dimensional Central Limit Theorem with Fourth-moment Error Bounds on Convex Sets and Balls
    Xiao Fang, Yuta Koike
    http://arxiv.org/abs/2009.00339v1

    • [math.PR]Statistical analysis of the non-ergodic fractional Ornstein-Uhlenbeck process with periodic mean
    Rachid Belfadli, Khalifa Es-Sebaiy, Fatima-Ezzahra Farah
    http://arxiv.org/abs/2009.00052v1

    • [q-bio.QM]Unsupervised and Supervised Structure Learning for Protein Contact Prediction
    Siqi Sun
    http://arxiv.org/abs/2009.00133v1

    • [q-fin.GN]Contingent Convertible Bonds in Financial Networks
    Giovanni Calice, Carlo Sala, Daniele Tantari
    http://arxiv.org/abs/2009.00062v1

    • [quant-ph]Universal Approximation Property of Quantum Feature Map
    Takahiro Goto, Quoc Hoan Tran, Kohei Nakajima
    http://arxiv.org/abs/2009.00298v1

    • [stat.AP]A Comparative Study of Parametric Regression Models to Detect Breakpoint in Traffic Fundamental Diagram
    Emmanuel Kidando, Angela E. Kitali, Boniphace Kutela, Thobias Sando
    http://arxiv.org/abs/2009.00536v1

    • [stat.AP]Application of the Cox Regression Model for Analysis of Railway Safety Performance
    Hendrik Schäbe, Jens Braband
    http://arxiv.org/abs/2009.00558v1

    • [stat.AP]Variable selection in social-environmental data: Sparse regression and tree ensemble machine learning approaches
    Elizabeth Handorf, Yinuo Yin, Michael Slifker, Shannon Lynch
    http://arxiv.org/abs/2009.00065v1

    • [stat.CO]Adaptive Path Sampling in Metastable Posterior Distributions
    Yuling Yao, Collin Cademartori, Aki Vehtari, Andrew Gelman
    http://arxiv.org/abs/2009.00471v1

    • [stat.CO]diproperm: An R Package for the DiProPerm Test
    Andrew G. Allmon, J. S. Marron, Michael G. Hudgens
    http://arxiv.org/abs/2009.00003v1

    • [stat.ME]Accounting for correlated horizontal pleiotropy in two-sample Mendelian randomization using correlated instrumental variants
    Qing Cheng, Baoluo Sun, Yingcun Xia, Jin Liu
    http://arxiv.org/abs/2009.00399v1

    • [stat.ME]Characterizing the Probability Law on Time Until Core Damage With PRA
    Martin Wortman, Ernest Kee, Paul Nelson
    http://arxiv.org/abs/2009.00208v1

    • [stat.ME]Design and Analysis of Switchback Experiments
    Iavor Bojinov, David Simchi-Levi, Jinglong Zhao
    http://arxiv.org/abs/2009.00148v1

    • [stat.ME]Informative Goodness-of-Fit for Multivariate Distributions
    Sara Algeri
    http://arxiv.org/abs/2009.00503v1

    • [stat.ME]Invited Discussion of “A Unified Framework for De-Duplication and Population Size Estimation”
    Jared S. Murray
    http://arxiv.org/abs/2009.00217v1

    • [stat.ML]Curb Your Normality: On the Quality Requirements of Demand Prediction for Dynamic Public Transport
    Inon Peled, Kelvin Lee, Yu Jiang, Justin Dauwels, Francisco C. Pereira
    http://arxiv.org/abs/2008.13443v2

    • [stat.ML]InClass Nets: Independent Classifier Networks for Nonparametric Estimation of Conditional Independence Mixture Models and Unsupervised Classification
    Konstantin T. Matchev, Prasanth Shyamsundar
    http://arxiv.org/abs/2009.00131v1

    • [stat.ML]Random Forest (RF) Kernel for Regression, Classification and Survival
    Dai Feng, Richard Baumgartner
    http://arxiv.org/abs/2009.00089v1

    • [stat.ML]Semi-Supervised Empirical Risk Minimization: When can unlabeled data improve prediction
    Oren Yuval, Saharon Rosset
    http://arxiv.org/abs/2009.00606v1

    • [stat.ML]Stochastic Graph Recurrent Neural Network
    Tijin Yan, Hongwei Zhang, Zirui Li, Yuanqing Xia
    http://arxiv.org/abs/2009.00538v1

    • [stat.ML]Uncertainty quantification for Markov Random Fields
    Panagiota Birmpa, Markos A. Katsoulakis
    http://arxiv.org/abs/2009.00038v1

    • [stat.ML]Variational Mixture of Normalizing Flows
    Guilherme G. P. Freitas Pires, Mário A. T. Figueiredo
    http://arxiv.org/abs/2009.00585v1