astro-ph.GA - 星系天体物理学
    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.CY - 计算与社会
    cs.DB - 数据库
    cs.DC - 分布式、并行与集群计算
    cs.HC - 人机接口
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.LO - 计算逻辑
    cs.MA - 多代理系统
    cs.PL - 编程语言
    cs.RO - 机器人学
    cs.SI - 社交网络与信息网络
    eess.IV - 图像与视频处理
    eess.SP - 信号处理
    eess.SY - 系统和控制
    hep-th - 高能物理理论
    math.CO - 组合数学
    math.DS - 动力系统
    math.OC - 优化与控制
    math.ST - 统计理论
    physics.flu-dyn - 流体动力学
    stat.AP - 应用统计
    stat.ME - 统计方法论
    stat.ML - (统计)机器学习

    • [astro-ph.GA]AGNet: Weighing Black Holes with Deep Learning
    • [cs.AI]Coalesced Multi-Output Tsetlin Machines with Clause Sharing
    • [cs.AI]Learning C to x86 Translation: An Experiment in Neural Compilation
    • [cs.AI]On Limited Non-Prioritised Belief Revision Operators with Dynamic Scope
    • [cs.AI]The Ecosystem Path to General AI
    • [cs.AI]Thirty years of Epistemic Specifications
    • [cs.CL]A Game Interface to Study Semantic Grounding in Text-Based Models
    • [cs.CL]A Light-weight contextual spelling correction model for customizing transducer-based speech recognition systems
    • [cs.CL]A Weak Supervised Dataset of Fine-Grained Emotions in Portuguese
    • [cs.CL]An NLP approach to quantify dynamic salience of predefined topics in a text corpus
    • [cs.CL]Annotation Guidelines for the Turku Paraphrase Corpus
    • [cs.CL]Combining speakers of multiple languages to improve quality of neural voices
    • [cs.CL]Generative Relation Linking for Question Answering over Knowledge Bases
    • [cs.CL]Graph Capsule Aggregation for Unaligned Multimodal Sequences
    • [cs.CL]IsoScore: Measuring the Uniformity of Vector Space Utilization
    • [cs.CL]MigrationsKB: A Knowledge Base of Public Attitudes towards Migrations and their Driving Factors
    • [cs.CL]Not All Linearizations Are Equally Data-Hungry in Sequence Labeling Parsing
    • [cs.CL]SPMoE: Generate Multiple Pattern-Aware Outputs with Sparse Pattern Mixture of Expert
    • [cs.CV]A Dense S
    6bcf
    iamese U-Net trained with Edge Enhanced 3D IOU Loss for Image Co-segmentation
    • [cs.CV]A Flexible Three-Dimensional Hetero-phase Computed Tomography Hepatocellular Carcinoma (HCC) Detection Algorithm for Generalizable and Practical HCC Screening
    • [cs.CV]A Hybrid Sparse-Dense Monocular SLAM System for Autonomous Driving
    • [cs.CV]An Evaluation of RGB and LiDAR Fusion for Semantic Segmentation
    • [cs.CV]Appearance Based Deep Domain Adaptation for the Classification of Aerial Images
    • [cs.CV]BN-NAS: Neural Architecture Search with Batch Normalization
    • [cs.CV]CaT: Weakly Supervised Object Detection with Category Transfer
    • [cs.CV]CaraNet: Context Axial Reverse Attention Network for Segmentation of Small Medical Objects
    • [cs.CV]CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation
    • [cs.CV]Clustering augmented Self-Supervised Learning: Anapplication to Land Cover Mapping
    • [cs.CV]Contextual Convolutional Neural Networks
    • [cs.CV]Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation
    • [cs.CV]DRB-GAN: A Dynamic ResBlock Generative Adversarial Network for Artistic Style Transfer
    • [cs.CV]DRÆM — A discriminatively trained reconstruction embedding for surface anomaly detection
    • [cs.CV]Diffeomorphic Particle Image Velocimetry
    • [cs.CV]End-to-End Dense Video Captioning with Parallel Decoding
    • [cs.CV]Exploring Classification Equilibrium in Long-Tailed Object Detection
    • [cs.CV]FaPN: Feature-aligned Pyramid Network for Dense Image Prediction
    • [cs.CV]Federated Multi-Target Domain Adaptation
    • [cs.CV]Fully Convolutional Networks for Panoptic Segmentation with Point-based Supervision
    • [cs.CV]G-DetKD: Towards General Distillation Framework for Object Detectors via Contrastive and Semantic-guided Feature Imitation
    • [cs.CV]Group-aware Contrastive Regression for Action Quality Assessment
    • [cs.CV]Guided Colorization Using Mono-Color Image Pairs
    • [cs.CV]Indoor Semantic Scene Understanding using Multi-modality Fusion
    • [cs.CV]Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks
    • [cs.CV]Investigating transformers in the decomposition of polygonal shapes as point collections
    • [cs.CV]LIF-Seg: LiDAR and Camera Image Fusion for 3D LiDAR Semantic Segmentation
    • [cs.CV]Learning Canonical View Representation for 3D Shape Recognition with Arbitrary Views
    • [cs.CV]Learning Dynamic Interpolation for Extremely Sparse Light Fields with Wide Baselines
    • [cs.CV]Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation
    • [cs.CV]Learning by Aligning: Visible-Infrared Person Re-identification using Cross-Modal Correspondences
    • [cs.CV]Light Field Image Super-Resolution with Transformers
    • [cs.CV]Look Who’s Talking: Active Speaker Detection in the Wild
    • [cs.CV]MSR-GCN: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction
    • [cs.CV]MV-TON: Memory-based Video Virtual Try-on network
    • [cs.CV]MVCNet: Multiview Contrastive Network for Unsupervised Representation Learning for 3D CT Lesions
    • [cs.CV]Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation
    • [cs.CV]Network Generalization Prediction for Safety Critical Tasks in Novel Operating Domains
    • [cs.CV]Neural Photofit: Gaze-based Mental Image Reconstruction
    • [cs.CV]Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation
    • [cs.CV]PR-RRN: Pairwise-Regularized Residual-Recursive Networks for Non-rigid Structure-from-Motion
    • [cs.CV]PnP-3D: A Plug-and-Play for 3D Point Clouds
    • [cs.CV]RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object Detection
    • [cs.CV]SOTR: Segmenting Objects with Transformers
    • [cs.CV]Scene Designer: a Unified Model for Scene Search and Synthesis from Sketch
    • [cs.CV]Self-Supervised 3D Human Pose Estimation with Multiple-View Geometry
    • [cs.CV]Self-Supervised Pretraining and Controlled Augmentation Improve Rare Wildlife Recognition in UAV Images
    • [cs.CV]Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation
    • [cs.CV]Semantic-embedded Unsupervised Spectral Reconstruction from Single RGB Images in the Wild
    • [cs.CV]TOOD: Task-aligned One-stage Object Detection
    • [cs.CV]TUM-VIE: The TUM Stereo Visual-Inertial Event Dataset
    • [cs.CV]Transferring Knowledge with Attention Distillation for Multi-Domain Image-to-Image Translation
    • [cs.CV]Unsupervised Geodesic-preserved Generative Adversarial Networks for Unconstrained 3D Pose Transfer
    • [cs.CV]VisBuddy — A Smart Wearable Assistant for the Visually Challenged
    • [cs.CV]Visual Enhanced 3D Point Cloud Reconstruction from A Single Image
    • [cs.CV]Who’s Waldo? Linking People Across Text and Images
    • [cs.CY]Global Tweet Mentions of COVID-19
    • [cs.CY]Monitor++?: Multiple versus Single Laboratory Monitors in Early Programming Education
    • [cs.DB]Reusable Templates and Guides For Documenting Datasets and Models for Natural Language Processing and Generation: A Case Study of the HuggingFace and GEM Data and Model Cards
    • [cs.DC]A Game-Theoretic Approach to Self-Stabilization with Selfish Agents
    • [cs.DC]An Efficient Parallel Algorithm for finding Bridges in a Dense Graph
    • [cs.HC]Social influence leads to the formation of diverse local trends
    • [cs.IR]ACM-CR: A Manually Annotated Test Collection for Citation Recommendation
    • [cs.IR]How Powerful is Graph Convolution for Recommendation?
    • [cs.IR]When Product Search Meets Collaborative Filtering: A Hierarchical Heterogeneous Graph Neural Network Approach
    • [cs.IT]Approximate MDS Property of Linear Codes
    • [cs.IT]Channel Estimation for Extremely Large-Scale MIMO: Far-Field or Near-Field?
    • [cs.IT]Correlation of Golay-Rudin-Shapiro Sequences
    • [cs.IT]Distributed Expectation Propagation Detection for Cell-Free Massive MIMO
    • [cs.IT]First-Order Theory of Probabilistic Independence and Single-Letter Characterizations of Capacity Regions
    • [cs.IT]Kähler information manifolds of signal processing filters in weighted Hardy spaces
    • [cs.IT]Rateless Codes for Low-Latency Distributed Inference in Mobile Edge Computing
    • [cs.IT]Self-dual 今日学术视野(2021.8.19) - 图1-quasi-abelian Codes
    • [cs.IT]The Emergence of Wireless MAC Protocols with Multi-Agent Reinforcement Learning
    • [cs.IT]Two-Timescale Design for Reconfigurable Intelligent Surface-Aided Massive MIMO Systems with Imperfect CSI
    • [cs.IT]Wireless Federated Langevin Monte Carlo: Repurposing Channel Noise for Bayesian Sampling and Privacy
    • [cs.LG]Aggregation Delayed Federated Learning
    • [cs.LG]BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing
    • [cs.LG]Diagnosis of Acute Myeloid Leukaemia Using Machine Learning
    • [cs.LG]Direct domain adaptation through reciprocal linear transformations
    • [cs.LG]FARF: A Fair and Adaptive Random Forests Classifier
    • [cs.LG]Fine-tuning is Fine in Federated Learning
    • [cs.LG]From the Greene—Wu Convolution to Gradient Estimation over Riemannian Manifolds
    • [cs.LG]Identifying Biased Subgroups in Ranking and Classification
    • [cs.LG]ImitAL: Learning Active Learning Strategies from Synthetic Data
    • [cs.LG]Incorporating Uncertainty in Learning to Defer Algorithms for Safe Computer-Aided Diagnosis
    • [cs.LG]Incremental cluster validity index-guided online learning for performance and robustness to presentation order
    • [cs.LG]Investigating a Baseline Of Self Supervised Learning Towards Reducing Labeling Costs For Image Classification
    • [cs.LG]KCNet: An Insect-Inspired Single-Hidden-Layer Neural Network with Randomized Binary Weights for Prediction and Classification Tasks
    • [cs.LG]Learning to Cluster via Same-Cluster Queries
    • [cs.LG]MOI-Mixer: Improving MLP-Mixer with Multi Order Interactions in Sequential Recommendation
    • [cs.LG]Memory-Efficient Factorization Machines via Binarizing both Data and Model Coefficients
    • [cs.LG]Modeling Protein Using Large-scale Pretrain Language Model
    • [cs.LG]Neural Predictive Monitoring under Partial Observability
    • [cs.LG]Panoramic Learning with A Standardized Machine Learning Formalism
    • [cs.LG]Revisiting State Augmentation methods for Reinforcement Learning with Stochastic Delays
    • [cs.LG]Scaling Laws for Deep Learning
    • [cs.LG]Stability and Generalization for Randomized Coordinate Descent
    • [cs.LG]Synthesizing Pareto-Optimal Interpretations for Black-Box Models
    • [cs.LG]Understanding the factors driving the opioid epidemic using machine learning
    • [cs.LG]Weakly Supervised Classification Using Group-Level Labels
    • [cs.LG]When Should You Defend Your Classifier — A Game-theoretical Analysis of Countermeasures against Adversarial Examples
    • [cs.LO]Hybrid dynamical type theories for navigation
    • [cs.LO]Reconfigurable Broadcast Networks and Asynchronous Shared-Memory Systems are Equivalent
    • [cs.MA]Encirclement Guaranteed Cooperative Pursuit with Robust Model Predictive Control
    • [cs.PL]On Incorrectness Logic and Kleene Algebra With Top and Tests
    • [cs.RO]Monolithic vs. hybrid controller for multi-objective Sim-to-Real learning
    • [cs.RO]Passivity-based control for haptic teleoperation of a legged manipulator in presence of time-delays
    • [cs.RO]Proximity Perception in Human-Centered Robotics: A Survey on Sensing Systems and Applications
    • [cs.SI]SPAN: Subgraph Prediction Attention Network for Dynamic Graphs
    • [cs.SI]Validating daily social media macroscopes of emotions
    • [eess.IV]A New Backbone for Hyperspectral Image Reconstruction
    • [eess.IV]Deep MRI Reconstruction with Radial Subsampling
    • [eess.IV]spectrai: A deep learning framework for spectral data
    • [eess.SP]Classification of Common Waveforms Including a Watchdog for Unknown Signals
    • [eess.SP]Rate-Splitting Multiple Access for Downlink MIMO: A Generalized Power Iteration Approach
    • [eess.SY]Optimal Placement of Public Electric Vehicle Charging Stations Using Deep Reinforcement Learning
    • [hep-th]Heterotic String Model Building with Monad Bundles and Reinforcement Learning
    • [math.CO]Arbitrary-length analogs to de Bruijn sequences
    • [math.DS]Poincaré-Hopf theorem for hybrid systems
    • [math.OC]Stochastic optimization under time drift: iterate averaging, step decay, and high probability guarantees
    • [math.ST]Limiting distributions of graph-based test statistics
    • [math.ST]Non-Asymptotic Bounds for the 今日学术视野(2021.8.19) - 图2 Estimator in Linear Regression with Uniform Noise
    • [physics.flu-dyn]SURFNet: Super-resolution of Turbulent Flows with Transfer Learning using Small Datasets
    • [stat.AP]Spatio-temporal Parking Behaviour Forecasting and Analysis Before and During COVID-19
    • [stat.AP]Technical report: Impact of evaluation metrics and sampling on the comparison of machine learning methods for biodiversity indicators prediction
    • [stat.ME]Augmenting control arms with Real-World Data for cancer trials: Hybrid control arm methods and considerations
    • [stat.ME]Causal Inference with Noncompliance and Unknown Interference
    • [stat.ME]Density Sharpening: Principles and Applications to Discrete Data Analysis
    • [stat.ME]Detecting changes in covariance via random matrix theory
    • [stat.ME]Modelling Time-Varying First and Second-Order Structure of Time Series via Wavelets and Differencing
    • [stat.ME]Testing Multiple Linear Regression Systems with Metamorphic Testing
    • [stat.ML]InfoGram and Admissible Machine Learning
    • [stat.ML]Semi-parametric Bayesian Additive Regression Trees

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

    • [astro-ph.GA]AGNet: Weighing Black Holes with Deep Learning
    Joshua Yao-Yu Lin, Sneh Pandya, Devanshi Pratap, Xin Liu, Matias Carrasco Kind, Volodymyr Kindratenko
    http://arxiv.org/abs/2108.07749v1

    • [cs.AI]Coalesced Multi-Output Tsetlin Machines with Clause Sharing
    Sondre Glimsdal, Ole-Christoffer Granmo
    http://arxiv.org/abs/2108.07594v1

    • [cs.AI]Learning C to x86 Translation: An Experiment in Neural Compilation
    Jordi Armengol-Estapé, Michael F. P. O’Boyle
    http://arxiv.org/abs/2108.07639v1

    • [cs.AI]On Limited Non-Prioritised Belief Revision Operators with Dynamic Scope
    Kai Sauerwald, Gabriele Kern-Isberner, Christoph Beierle
    http://arxiv.org/abs/2108.07769v1

    • [cs.AI]The Ecosystem Path to General AI
    Claes Strannegård, Niklas Engsner, Pietro Ferrari, Hans Glimmerfors, Marcus Hilding Södergren, Tobias Karlsson, Birger Kleve, Victor Skoglund
    http://arxiv.org/abs/2108.07578v1

    • [cs.AI]Thirty years of Epistemic Specifications
    Jorge Fandinno, Wolfgang Faber, Michael Gelfond
    http://arxiv.org/abs/2108.07669v1

    • [cs.CL]A Game Interface to Study Semantic Grounding in Text-Based Models
    Timothee Mickus, Mathieu Constant, Denis Paperno
    http://arxiv.org/abs/2108.07708v1

    • [cs.CL]A Light-weight contextual spelling correction model for customizing transducer-based speech recognition systems
    Xiaoqiang Wang, Yanqing Liu, Sheng Zhao, Jinyu Li
    http://arxiv.org/abs/2108.07493v1

    • [cs.CL]A Weak Supervised Dataset of Fine-Grained Emotions in Portuguese
    Diogo Cortiz, Jefferson O. Silva, Newton Calegari, Ana Luísa Freitas, Ana Angélica Soares, Carolina Botelho, Gabriel Gaudencio Rêgo, Waldir Sampaio, Paulo Sergio Boggio
    http://arxiv.org/abs/2108.07638v1

    • [cs.CL]An NLP approach to quantify dynamic salience of predefined topics in a text corpus
    A. Bock, A. Palladino, S. Smith-Heisters, I. Boardman, E. Pellegrini, E. J. Bienenstock, A. Valenti
    http://arxiv.org/abs/2108.07345v1

    • [cs.CL]Annotation Guidelines for the Turku Paraphrase Corpus
    Jenna Kanerva, Filip Ginter, Li-Hsin Chang, Iiro Rastas, Valtteri Skantsi, Jemina Kilpeläinen, Hanna-Mari Kupari, Aurora Piirto, Jenna Saarni, Maija Sevón, Otto Tarkka
    http://arxiv.org/abs/2108.07499v1

    • [cs.CL]Combining speakers of multiple languages to improve quality of neural voices
    Javier Latorre, Charlotte Bailleul, Tuuli Morrill, Alistair Conkie, Yannis Stylianou
    http://arxiv.org/abs/2108.07737v1

    • [cs.CL]Generative Relation Linking for Question Answering over Knowledge Bases
    Gaetano Rossiello, Nandana Mihindukulasooriya, Ibrahim Abdelaziz, Mihaela Bornea, Alfio Gliozzo, Tahira Naseem, Pavan Kapanipathi
    http://arxiv.org/abs/2108.07337v1

    • [cs.CL]Graph Capsule Aggregation for Unaligned Multimodal Sequences
    Jianfeng Wu, Sijie Mai, Haifeng Hu
    http://arxiv.org/abs/2108.07543v1

    • [cs.CL]IsoScore: Measuring the Uniformity of Vector Space Utilization
    William Rudman, Nate Gillman, Taylor Rayne, Carsten Eickhoff
    http://arxiv.org/abs/2108.07344v1

    • [cs.CL]MigrationsKB: A Knowledge Base of Public Attitudes towards Migrations and their Driving Factors
    Yiyi Chen, Harald Sack, Mehwish Alam
    http://arxiv.org/abs/2108.07593v1

    • [cs.CL]Not All Linearizations Are Equally Data-Hungry in Sequence Labeling Parsing
    Alberto Muñoz-Ortiz, Michalina Strzyz, David Vilares
    http://arxiv.org/abs/2108.07556v1

    • [cs.CL]SPMoE: Generate Multiple Pattern-Aware Outputs with Sparse Pattern Mixture of Expert
    Shaobo Cui, Xintong Bao, Xuming Lin, Zhongzhou Zhao, Ji Zhang, Wei Zhou, Haiqing Chen
    http://arxiv.org/abs/2108.07535v1

    • [cs.CV]A Dense S
    6bcf
    iamese U-Net trained with Edge Enhanced 3D IOU Loss for Image Co-segmentation
    Xi Liu, Xiabi Liu, Huiyu Li, Xiaopeng Gong
    http://arxiv.org/abs/2108.07491v1

    • [cs.CV]A Flexible Three-Dimensional Hetero-phase Computed Tomography Hepatocellular Carcinoma (HCC) Detection Algorithm for Generalizable and Practical HCC Screening
    Chi-Tung Cheng, Jinzheng Cai, Wei Teng, Youjing Zheng, YuTing Huang, Yu-Chao Wang, Chien-Wei Peng, Youbao Tang, Wei-Chen Lee, Ta-Sen Yeh, Jing Xiao, Le Lu, Chien-Hung Liao, Adam P. Harrison
    http://arxiv.org/abs/2108.07492v1

    • [cs.CV]A Hybrid Sparse-Dense Monocular SLAM System for Autonomous Driving
    Louis Gallagher, Varun Ravi Kumar, Senthil Yogamani, John B. McDonald
    http://arxiv.org/abs/2108.07736v1

    • [cs.CV]An Evaluation of RGB and LiDAR Fusion for Semantic Segmentation
    Amr S. Mohamed, Ali Abdelkader, Mohamed Anany, Omar El-Behady, Muhammad Faisal, Asser Hangal, Hesham M. Eraqi, Mohamed N. Moustafa
    http://arxiv.org/abs/2108.07661v1

    • [cs.CV]Appearance Based Deep Domain Adaptation for the Classification of Aerial Images
    Dennis Wittich, Franz Rottensteiner
    http://arxiv.org/abs/2108.07779v1

    • [cs.CV]BN-NAS: Neural Architecture Search with Batch Normalization
    Boyu Chen, Peixia Li, Baopu Li, Chen Lin, Chuming Li, Ming Sun, Junjie Yan, Wanli Ouyang
    http://arxiv.org/abs/2108.07375v1

    • [cs.CV]CaT: Weakly Supervised Object Detection with Category Transfer
    Tianyue Cao, Lianyu Du, Xiaoyun Zhang, Siheng Chen, Ya Zhang, Yan-Feng Wang
    http://arxiv.org/abs/2108.07487v1

    • [cs.CV]CaraNet: Context Axial Reverse Attention Network for Segmentation of Small Medical Objects
    Ange Lou, Shuyue Guan, Murray Loew
    http://arxiv.org/abs/2108.07368v1

    • [cs.CV]CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation
    Xinru Zhang, Chenghao Liu, Ni Ou, Xiangzhu Zeng, Xiaoliang Xiong, Yizhou Yu, Zhiwen Liu, Chuyang Ye
    http://arxiv.org/abs/2108.06883v2

    • [cs.CV]Clustering augmented Self-Supervised Learning: Anapplication to Land Cover Mapping
    Rahul Ghosh, Xiaowei Jia, Chenxi Lin, Zhenong Jin, Vipin Kumar
    http://arxiv.org/abs/2108.07323v1

    • [cs.CV]Contextual Convolutional Neural Networks
    Ionut Cosmin Duta, Mariana Iuliana Georgescu, Radu Tudor Ionescu
    http://arxiv.org/abs/2108.07387v1

    • [cs.CV]Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation
    Weide Liu, Xiangfei Kong, Tzu-Yi Hung, Guosheng Lin
    http://arxiv.org/abs/2108.07413v1

    • [cs.CV]DRB-GAN: A Dynamic ResBlock Generative Adversarial Network for Artistic Style Transfer
    Wenju Xu, Chengjiang Long, Ruisheng Wang, Guanghui Wang
    http://arxiv.org/abs/2108.07379v1

    • [cs.CV]DRÆM — A discriminatively trained reconstruction embedding for surface anomaly detection
    Vitjan Zavrtanik, Matej Kristan, Danijel Skočaj
    http://arxiv.org/abs/2108.07610v1

    • [cs.CV]Diffeomorphic Particle Image Velocimetry
    Yong Lee, Shuang Mei
    http://arxiv.org/abs/2108.07438v1

    • [cs.CV]End-to-End Dense Video Captioning with Parallel Decoding
    Teng Wang, Ruimao Zhang, Zhichao Lu, Feng Zheng, Ran Cheng, Ping Luo
    http://arxiv.org/abs/2108.07781v1

    • [cs.CV]Exploring Classification Equilibrium in Long-Tailed Object Detection
    Chengjian Feng, Yujie Zhong, Weilin Huang
    http://arxiv.org/abs/2108.07507v1

    • [cs.CV]FaPN: Feature-aligned Pyramid Network for Dense Image Prediction
    Shihua Huang, Zhichao Lu, Ran Cheng, Cheng He
    http://arxiv.org/abs/2108.07058v2

    • [cs.CV]Federated Multi-Target Domain Adaptation
    Chun-Han Yao, Boqing Gong, Yin Cui, Hang Qi, Yukun Zhu, Ming-Hsuan Yang
    http://arxiv.org/abs/2108.07792v1

    • [cs.CV]Fully Convolutional Networks for Panoptic Segmentation with Point-based Supervision
    Yanwei Li, Hengshuang Zhao, Xiaojuan Qi, Yukang Chen, Lu Qi, Liwei Wang, Zeming Li, Jian Sun, Jiaya Jia
    http://arxiv.org/abs/2108.07682v1

    • [cs.CV]G-DetKD: Towards General Distillation Framework for Object Detectors via Contrastive and Semantic-guided Feature Imitation
    Lewei Yao, Renjie Pi, Hang Xu, Wei Zhang, Zhenguo Li, Tong Zhang
    http://arxiv.org/abs/2108.07482v1

    • [cs.CV]Group-aware Contrastive Regression for Action Quality Assessment
    Xumin Yu, Yongming Rao, Wenliang Zhao, Jiwen Lu, Jie Zhou
    http://arxiv.org/abs/2108.07797v1

    • [cs.CV]Guided Colorization Using Mono-Color Image Pairs
    Ze-Hua Sheng, Hui-Liang Shen, Bo-Wen Yao, Huaqi Zhang
    http://arxiv.org/abs/2108.07471v1

    • [cs.CV]Indoor Semantic Scene Understanding using Multi-modality Fusion
    Muraleekrishna Gopinathan, Giang Truong, Jumana Abu-Khalaf
    http://arxiv.org/abs/2108.07616v1

    • [cs.CV]Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks
    Zhihao Liang, Zhihao Li, Songcen Xu, Mingkui Tan, Kui Jia
    http://arxiv.org/abs/2108.07478v1

    • [cs.CV]Investigating transformers in the decomposition of polygonal shapes as point collections
    Andrea Alfieri, Yancong Lin, Jan C. van Gemert
    http://arxiv.org/abs/2108.07533v1

    • [cs.CV]LIF-Seg: LiDAR and Camera Image Fusion for 3D LiDAR Semantic Segmentation
    Lin
    b77
    Zhao, Hui Zhou, Xinge Zhu, Xiao Song, Hongsheng Li, Wenbing Tao
    http://arxiv.org/abs/2108.07511v1

    • [cs.CV]Learning Canonical View Representation for 3D Shape Recognition with Arbitrary Views
    Xin Wei, Yifei Gong, Fudong Wang, Xing Sun, Jian Sun
    http://arxiv.org/abs/2108.07084v2

    • [cs.CV]Learning Dynamic Interpolation for Extremely Sparse Light Fields with Wide Baselines
    Mantang Guo, Jing Jin, Hui Liu, Junhui Hou
    http://arxiv.org/abs/2108.07408v1

    • [cs.CV]Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation
    Ailing Zeng, Xiao Sun, Lei Yang, Nanxuan Zhao, Minhao Liu, Qiang Xu
    http://arxiv.org/abs/2108.07181v2

    • [cs.CV]Learning by Aligning: Visible-Infrared Person Re-identification using Cross-Modal Correspondences
    Hyunjong Park, Sanghoon Lee, Junghyup Lee, Bumsub Ham
    http://arxiv.org/abs/2108.07422v1

    • [cs.CV]Light Field Image Super-Resolution with Transformers
    Zhengyu Liang, Yingqian Wang, Longguang Wang, Jungang Yang, Shilin Zhou
    http://arxiv.org/abs/2108.07597v1

    • [cs.CV]Look Who’s Talking: Active Speaker Detection in the Wild
    You Jin Kim, Hee-Soo Heo, Soyeon Choe, Soo-Whan Chung, Yoohwan Kwon, Bong-Jin Lee, Youngki Kwon, Joon Son Chung
    http://arxiv.org/abs/2108.07640v1

    • [cs.CV]MSR-GCN: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction
    Lingwei Dang, Yongwei Nie, Chengjiang Long, Qing Zhang, Guiqing Li
    http://arxiv.org/abs/2108.07152v2

    • [cs.CV]MV-TON: Memory-based Video Virtual Try-on network
    Xiaojing Zhong, Zhonghua Wu, Taizhe Tan, Guosheng Lin, Qingyao Wu
    http://arxiv.org/abs/2108.07502v1

    • [cs.CV]MVCNet: Multiview Contrastive Network for Unsupervised Representation Learning for 3D CT Lesions
    Penghua Zhai, Huaiwei Cong, Gangming Zhao, Chaowei Fang, Jinpeng Li
    http://arxiv.org/abs/2108.07662v1

    • [cs.CV]Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation
    Antoine Saporta, Tuan-Hung Vu, Matthieu Cord, Patrick Pérez
    http://arxiv.org/abs/
    rg/abs/2108.06962v1
    rg/abs/2108.06962v1)

    • [cs.CV]Network Generalization Prediction for Safety Critical Tasks in Novel Operating Domains
    Molly O’Brien, Mike Medoff, Julia Bukowski, Greg Hager
    http://arxiv.org/abs/2108.07399v1

    • [cs.CV]Neural Photofit: Gaze-based Mental Image Reconstruction
    Florian Strohm, Ekta Sood, Sven Mayer, Philipp Müller, Mihai Bâce, Andreas Bulling
    http://arxiv.org/abs/2108.07524v1

    • [cs.CV]Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation
    Yuxiang Wei, Yupeng Shi, Xiao Liu, Zhilong Ji, Yuan Gao, Zhongqin Wu, Wangmeng Zuo
    http://arxiv.org/abs/2108.07668v1

    • [cs.CV]PR-RRN: Pairwise-Regularized Residual-Recursive Networks for Non-rigid Structure-from-Motion
    Haitian Zeng, Yuchao Dai, Xin Yu, Xiaohan Wang, Yi Yang
    http://arxiv.org/abs/2108.07506v1

    • [cs.CV]PnP-3D: A Plug-and-Play for 3D Point Clouds
    Shi Qiu, Saeed Anwar, Nick Barnes
    http://arxiv.org/abs/2108.07378v1

    • [cs.CV]RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object Detection
    Yongming Rao, Benlin Liu, Yi Wei, Jiwen Lu, Cho-Jui Hsieh, Jie Zhou
    http://arxiv.org/abs/2108.07794v1

    • [cs.CV]SOTR: Segmenting Objects with Transformers
    Ruohao Guo, Dantong Niu, Liao Qu, Zhenbo Li
    http://arxiv.org/abs/2108.06747v2

    • [cs.CV]Scene Designer: a Unified Model for Scene Search and Synthesis from Sketch
    Leo Sampaio Ferraz Ribeiro, Tu Bui, John Collomosse, Moacir Ponti
    http://arxiv.org/abs/2108.07353v1

    • [cs.CV]Self-Supervised 3D Human Pose Estimation with Multiple-View Geometry
    Arij Bouazizi, Julian Wiederer, Ulrich Kressel, Vasileios Belagiannis
    http://arxiv.org/abs/2108.07777v1

    • [cs.CV]Self-Supervised Pretraining and Controlled Augmentation Improve Rare Wildlife Recognition in UAV Images
    Xiaochen Zheng, Benjamin Kellenberger, Rui Gong, Irena Hajnsek, Devis Tuia
    http://arxiv.org/abs/2108.07582v1

    • [cs.CV]Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation
    Lina Liu, Xibin Song, Mengmeng Wang, Yong Liu, Liangjun Zhang
    http://arxiv.org/abs/2108.07628v1

    • [cs.CV]Semantic-embedded Unsupervised Spectral Reconstruction from Single RGB Images in the Wild
    Zhiyu Zhu, Hui Liu, Junhui Hou, Huanqiang Zeng, Qingfu Zhang
    http://arxiv.org/abs/2108.06659v2

    • [cs.CV]TOOD: Task-aligned One-stage Object Detection
    Chengjian Feng, Yujie Zhong, Yu Gao, Matthew R. Scott, Weilin Huang
    http://arxiv.org/abs/2108.07755v1

    • [cs.CV]TUM-VIE: The TUM Stereo Visual-Inertial Event Dataset
    Simon Klenk, Jason Chui, Nikolaus Demmel, Daniel Cremers
    http://arxiv.org/abs/2108.07329v1

    • [cs.CV]Transferring Knowledge with Attention Distillation for Multi-Domain Image-to-Image Translation
    Runze Li, Tomaso Fontanini, Luca Donati, Andrea Prati, Bir Bhanu
    http://arxiv.org/abs/2108.07466v1

    • [cs.CV]Unsupervised Geodesic-preserved Generative Adversarial Networks for Unconstrained 3D Pose Transfer
    Haoyu Chen, Hao Tang, Henglin Shi, Wei Peng, Nicu Sebe, Guoying Zhao
    http://arxiv.org/abs/2108.07520v1

    • [cs.CV]VisBuddy — A Smart Wearable Assistant for the Visually Challenged
    Ishwarya Sivakumar, Nishaali Meenakshisundaram, Ishwarya Ramesh, Shiloah Elizabeth D, Sunil Retmin Raj C
    http://arxiv.org/abs/2108.07761v1

    • [cs.CV]Visual Enhanced 3D Point Cloud Reconstruction from A Single Image
    Guiju Ping, Mahdi Abolfazli Esfahani, Han Wang
    http://arxiv.org/abs/2108.07685v1

    • [cs.CV]Who’s Waldo? Linking People Across Text and Images
    Claire Yuqing Cui, Apoorv Khandelwal, Yoav Artzi, Noah Snavely, Hadar Averbuch-Elor
    http://arxiv.org/abs/2108.07253v2

    • [cs.CY]Global Tweet Mentions of COVID-19
    Guangqing Chi, Junjun Yin, M. Luke Smith, Yosef Bodovski
    http://arxiv.org/abs/2108.06385v2

    • [cs.CY]Monitor++?: Multiple versus Single Laboratory Monitors in Early Programming Education
    Matthew Stephan
    http://arxiv.org/abs/2108.07729v1

    • [cs.DB]Reusable Templates and Guides For Documenting Datasets and Models for Natural Language Processing and Generation: A Case Study of the HuggingFace and GEM Data and Model Cards
    Angelina McMillan-Major, Salomey Osei, Juan Diego Rodriguez, Pawan Sasanka Ammanamanchi, Sebastian Gehrmann, Yacine Jernite
    http://arxiv.org/abs/2108.07374v1

    • [cs.DC]A Game-Theoretic Approach to Self-Stabilization with Selfish Agents
    Amir Reza Ramtin, Don Towsley
    http://arxiv.org/abs/2108.07362v1

    • [cs.DC]An Efficient Parallel Algorithm for finding Bridges in a Dense Graph
    Ashwani Kumar, Aditya Pratap Singh
    http://arxiv.org/abs/2108.07346v1

    • [cs.HC]Social influence leads to the formation of diverse local trends
    Ziv Epstein, Matthew Groh, Abhimanyu Dubey, Alex “Sandy” Pentland
    http://arxiv.org/abs/2108.07437v1

    • [cs.IR]ACM-CR: A Manually Annotated Test Collection for Citation Recommendation
    Florian Boudin
    http://arxiv.org/abs/2108.07571v1

    • [cs.IR]How Powerful is Graph Convolution for Recommendation?
    Yifei Shen, Yongji Wu, Yao Zhang, Caihua Shan, Jun Zhang, Khaled B. Letaief, Dongsheng Li
    http://arxiv.org/abs/2108.07567v1

    • [cs.IR]When Product Search Meets Collaborative Filtering: A Hierarchical Heterogeneous Graph Neural Network Approach
    Xiangkun Yin, Yangyang Guo, Liqiang Nie, Zhiyong Cheng
    http://arxiv.org/abs/2108.07574v1

    • [cs.IT]Approximate MDS Property of Linear Codes
    Ghurumuruhan Ganesan
    http://arxiv.org/abs/2108.07651v1

    • [cs.IT]Channel Estimation for Extremely Large-Scale MIMO: Far-Field or Near-Field?
    Mingyao Cui, Linglong Dai
    http://arxiv.org/abs/2108.07581v1

    • [cs.IT]Correlation of Golay-Rudin-Shapiro Sequences
    Daniel J. Katz, Courtney M. van der Linden
    http://arxiv.org/abs/2108.07318v1

    • [cs.IT]Distributed Expectation Propagation Detection for Cell-Free Massive MIMO
    Hengtao He, Hanqing Wang, Xianghao Yu, Jun Zhang, S. H. Song, Khaled B. Letaief
    http://arxiv.org/abs/2108.07498v1

    • [cs.IT]First-Order Theory of Probabilistic Independence and Single-Letter Characterizations of Capacity Regions
    Cheuk Ting Li
    http://arxiv.org/abs/2108.07324v1

    • [cs.IT]Kähler information manifolds of signal processing filters in weighted Hardy spaces
    Jaehyung Choi
    http://arxiv.org/abs/2108.07746v1

    • [cs.IT]Rateless Codes for Low-Latency Distributed Inference in Mobile Edge Computing
    Anton Frigård, Siddhartha Kumar, Eirik Rosnes, Alexandre Graell i Amat
    http://arxiv.org/abs/2108.07675v1

    • [cs.IT]Self-dual 今日学术视野(2021.8.19) - 图3-quasi-abelian Codes
    Liren Lin, Yun Fan
    http://arxiv.org/abs/2108.07427v1

    • [cs.IT]The Emergence of Wireless MAC Protocols with Multi-Agent Reinforcement Learning
    Mateus P. Mota, Alvaro Valcarce, Jean-Marie Gorce, Jakob Hoydis
    http://arxiv.org/abs/2108.07144v2

    • [cs.IT]Two-Timescale Design for Reconfigurable Intelligent Surface-Aided Massive MIMO Systems with Imperfect CSI
    Kangda Zhi, Cunhua Pan, Hong Ren, Kezhi Wang, Maged Elkashlan, Marco Di Renzo, Robert Schober, H. Vincent Poor, Jiangzhou Wang, Lajos Han
    http://arxiv.org/abs/2108.07622v1

    • [cs.IT]Wireless Federated Langevin Monte Carlo: Repurposing Channel Noise for Bayesian Sampling and Privacy
    Dongzhu Liu, Osvaldo Simeone
    http://arxiv.org/abs/2108.07644v1

    • [cs.LG]Aggregation Delayed Federated Learning
    Ye Xue, Diego Klabjan, Yuan Luo
    http://arxiv.org/abs/2108.07433v1

    • [cs.LG]BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing
    Aritra Ghosh, Andrew Lan
    http://arxiv.org/abs/2108.07386v1

    • [cs.LG]Diagnosis of Acute Myeloid Leukaemia Using Machine Learning
    A. Angelakis, I. Soulioti
    http://arxiv.org/abs/2108.07396v1

    • [cs.LG]Direct domain adaptation through reciprocal linear transformations
    Tariq Alkhalifah, Oleg Ovcharenko
    http://arxiv.org/abs/2108.07600v1

    • [cs.LG]FARF: A Fair and Adaptive Random Forests Classifier
    Wenbin Zhang, Albert Bifet, Xiangliang Zhang, Jeremy C. Weiss, Wolfgang Nejdl
    http://arxiv.org/abs/2108.07403v1

    • [cs.LG]Fine-tuning is Fine in Federated Learning
    Gary Cheng, Karan Chadha, John Duchi
    http://arxiv.org/abs/2108.07313v1

    • [cs.LG]From the Greene—Wu Convolution to Gradient Estimation over Riemannian Manifolds
    Tianyu Wang, Yifeng Huang, Didong Li
    http://arxiv.org/abs/2108.07406v1

    • [cs.LG]Identifying Biased Subgroups in Ranking and Classification
    Eliana Pastor, Luca de Alfaro, Elena Baralis
    http://arxiv.org/abs/2108.07450v1

    • [cs.LG]ImitAL: Learning Active Learning Strategies from Synthetic Data
    Julius Gonsior, Maik Thiele, Wolfgang Lehner
    http://arxiv.org/abs/2108.07670v1

    • [cs.LG]Incorporating Uncertainty in Learning to Defer Algorithms for Safe Computer-Aided Diagnosis
    Jessie Liu, Blanca Gallego, Sebastiano Barbieri
    http://arxiv.org/abs/2108.07392v1

    • [cs.LG]Incremental cluster validity index-guided online learning for performance and robustness to presentation order
    Leonardo Enzo Brito da Silva, Nagasharath Rayapati, Donald C. Wunsch II
    http://arxiv.org/abs/2108.07743v1

    • [cs.LG]Investigating a Baseline Of Self Supervised Learning Towards Reducing Labeling Costs For Image Classification
    Hilal AlQuabeh, Ameera Bawazeer, Abdulateef Alhashmi
    http://arxiv.org/abs/2108.07464v1

    • [cs.LG]KCNet: An Insect-Inspired Single-Hidden-Layer Neural Network with Randomized Binary Weights for Prediction and Classification Tasks
    Jinyung Hong, Theodore P. Pavlic
    http://arxiv.org/abs/2108.07554v1

    • [cs.LG]Learning to Cluster via Same-Cluster Queries
    Yi Li, Yan Song, Qin Zhang
    http://arxiv.org/abs/2108.07383v1

    • [cs.LG]MOI-Mixer: Improving MLP-Mixer with Multi Order Interactions in Sequential Recommendation
    Hojoon Lee, Dongyoon Hwang, Sunghwan Hong, Changyeon Kim, Seungryong Kim, Jaegul Choo
    http://arxiv.org/abs/2108.07505v1

    • [cs.LG]Memory-Efficient Factorization Machines via Binarizing both Data and Model Coefficients
    Yu Geng, Liang Lan
    http://arxiv.org/abs/2108.07421v1

    • [cs.LG]Modeling Protein Using Large-scale Pretrain Language Model
    Yijia Xiao, Jiezhong Qiu, Ziang Li, Chang-Yu Hsieh, Jie Tang
    http://arxiv.org/abs/2108.07435v1

    • [cs.LG]Neural Predictive Monitoring under Partial Observability
    Francesca Cairoli, Luca Bortolussi, Nicola Paoletti
    http://arxiv.org/abs/2108.07134v2

    • [cs.LG]Panoramic Learning with A Standardized Machine Learning Formalism
    Zhiting Hu, Eric P. Xing
    http://arxiv.org/abs/2108.07783v1

    • [cs.LG]Revisiting State Augmentation methods for Reinforcement Learning with Stochastic Delays
    Somjit Nath, Mayank Baranwal, Harshad Khadilkar
    http://arxiv.org/abs/2108.07555v1

    • [cs.LG]Scaling Laws for Deep Learning
    Jonathan S. Rosenfeld
    http://arxiv.org/abs/2108.07686v1

    • [cs.LG]Stability and Generalization for Randomized Coordinate Descent
    Puyu Wang, Liang Wu, Yunwen Lei
    http://arxiv.org/abs/2108.07414v1

    • [cs.LG]Synthesizing Pareto-Optimal Interpretations for Black-Box Models
    Hazem Torfah, Shetal Shah, Supratik Chakraborty, S. Akshay, Sanjit A. Seshia
    http://arxiv.org/abs/2108.07307v1

    • [cs.LG]Understanding the factors driving the opioid epidemic using machine learning
    Sachin Gavali, Chuming Chen, Julie Cowart, Xi Peng, Shanshan Ding, Cathy Wu, Tammy Anderson
    http://arxiv.org/abs/2108.07301v1

    • [cs.LG]Weakly Supervised Classification Using Group-Level Labels
    Guruprasad Nayak, Rahul Ghosh, Xiaowei Jia, Vipin Kumar
    http://arxiv.org/abs/2108.07330v1

    • [cs.LG]When Should You Defend Your Classifier — A Game-theoretical Analysis of Countermeasures against Adversarial Examples
    Maximilian Samsinger, Florian Merkle, Pascal Schöttle, Tomas Pevny
    http://arxiv.org/abs/2108.07602v1

    • [cs.LO]Hybrid dynamical type theories for navigation
    Paul Gustafson, Jared Culbertson, Daniel E. Koditschek
    http://arxiv.org/abs/2108.07625v1

    • [cs.LO]Reconfigurable Broadcast Networks and Asynchronous Shared-Memory Systems are Equivalent
    A. R. Balasubramanian, Chana Weil-Kennedy
    http://arxiv.org/abs/2108.07510v1

    • [cs.MA]Encirclement Guaranteed Cooperative Pursuit with Robust Model Predictive Control
    Chen Wang, Hua Chen, Jia Pan, Wei Zhang
    http://arxiv.org/abs/2108.07445v1

    • [cs.PL]On Incorrectness Logic and Kleene Algebra With Top and Tests
    Cheng Zhang, Arthur Azevedo de Amorim, Marco Gaboardi
    http://arxiv.org/abs/2108.07707v1

    • [cs.RO]Monolithic vs. hybrid controller for multi-objective Sim-to-Real learning
    Atakan Dag, Alexandre Angleraud, Wenyan Yang, Nataliya Strokina, Roel S. Pieters, Minna Lanz, Joni-Kristian Kamarainen
    http://arxiv.org/abs/2108.07514v1

    • [cs.RO]Passivity-based control for haptic teleoperation of a legged manipulator in presence of time-delays
    Mattia Risiglione, Jean-Pierre Sleiman, Maria Vittoria Minniti, Burak Cizmeci, Douwe Dresscher, Marco Hutter
    http://arxiv.org/abs/2108.07658v1

    • [cs.RO]Proximity Perception in Human-Centered Robotics: A Survey on Sensing Systems and Applications
    Stefan Escaida Navarro, Stephan Mühlbacher-Karrer, Hosam Alagi, Hubert Zangl, Keisuke Koyama, Björn Hein, Christian Duriez, Joshua R. Smith
    http://arxiv.org/abs/2108.07206v2

    • [cs.SI]SPAN: Subgraph Prediction Attention Network for Dynamic Graphs
    Yuan Li, Chuanchang Chen, Yubo Tao, Hai Lin
    http://arxiv.org/abs/2108.07776v1

    • [cs.SI]Validating daily social media macroscopes of emotions
    Max Pellert, Hannah Metzler, Michael Matzenberger, David Garcia
    http://arxiv.org/abs/2108.07646v1

    • [eess.IV]A New Backbone for Hyperspectral Image Reconstruction
    Jiamian Wang, Yulun Zhang, Xin Yuan, Yun Fu, Zhiqiang Tao
    http://arxiv.org/abs/2108.07739v1

    • [eess.IV]Deep MRI Reconstruction with Radial Subsampling
    George Yiasemis, Chaoping Zhang, Clara I. Sánchez, Jan-Jakob Sonke, Jonas Teuwen
    http://arxiv.org/abs/2108.07619v1

    • [eess.IV]spectrai: A deep learning framework for spectral data
    Conor C. Horgan, Mads S. Bergholt
    http://arxiv.org/abs/2108.07595v1

    • [eess.SP]Classification of Common Waveforms Including a Watchdog for Unknown Signals
    C. Tanner Fredieu, Justin Bui, Anthony Martone, Robert J. Marks II, Charles Baylis, R. Michael Buehrer
    http://arxiv.org/abs/2108.07339v1

    • [eess.SP]Rate-Splitting Multiple Access for Downlink MIMO: A Generalized Power Iteration Approach
    Jeonghun Park, Jinseok Choi, Namyoon Lee, Wonjae Shin, H. Vincent Poor
    http://arxiv.org/abs/2108.06844v1

    • [eess.SY]Optimal Placement of Public Electric Vehicle Charging Stations Using Deep Reinforcement Learning
    Aidan Petratos, Allen Ting, Shankar Padmanabhan, Kristina Zhou, Dylan Hageman, Jesse R. Pisel, Michael J. Pyrcz
    http://arxiv.org/abs/2108.07772v1

    • [hep-th]Heterotic String Model Building with Monad Bundles and Reinforcement Learning
    Andrei Constantin, Thomas R. Harvey, Andre Lukas
    http://arxiv.org/abs/2108.07316v1

    • [math.CO]Arbitrary-length analogs to de Bruijn sequences
    Abhinav Nellore, Rachel Ward
    http://arxiv.org/abs/2108.07759v1

    • [math.DS]Poincaré-Hopf theorem for hybrid systems
    Matthew D. Kvalheim
    http://arxiv.org/abs/2108.07434v1

    • [math.OC]Stochastic optimization under time drift: iterate averaging, step decay, and high probability guarantees
    Joshua Cutler, Dmitriy Drusvyatskiy, Zaid Harchaoui
    http://arxiv.org/abs/2108.07356v1

    • [math.ST]Limiting distributions of graph-based test statistics
    Yejiong Zhu, Hao Chen
    http://arxiv.org/abs/2108.07446v1

    • [math.ST]Non-Asymptotic Bounds for the 今日学术视野(2021.8.19) - 图4 Estimator in Linear Regression with Uniform Noise
    Yufei Yi, Matey Neykov
    http://arxiv.org/abs/2108.07630v1

    • [physics.flu-dyn]SURFNet: Super-resolution of Turbulent Flows with Transfer Learning using Small Datasets
    Octavi Obiols-Sales, Abhinav Vishnu, Nicholas Malaya, Aparna Chandramowlishwaran
    http://arxiv.org/abs/2108.07667v1

    • [stat.AP]Spatio-temporal Parking Behaviour Forecasting and Analysis Before and During COVID-19
    Shuhui Gong, Xiaopeng Mo, Rui Cao, Yu Liu, Wei Tu, Ruibin Bai
    http://arxiv.org/abs/2108.07731v1

    • [stat.AP]Technical report: Impact of evaluation metrics and sampling on the comparison of machine learning methods for biodiversity indicators prediction
    Geneviève Robin, Cathia Le Hasif
    http://arxiv.org/abs/2108.07480v1

    • [stat.ME]Augmenting control arms with Real-World Data for cancer trials: Hybrid control arm methods and considerations
    W. Katherine Tan, Brian D. Segal, Melissa D. Curtis, Shrujal S. Baxi, William B. Capra, Elizabeth Garrett-Mayer, Brian P. Hobbs, David S. Hong, Rebecca A. Hubbard, Jiawen Zhu, Somnath Sarkar, Meghna Samant
    http://arxiv.org/abs/2108.07335v1

    • [stat.ME]Causal Inference with Noncompliance and Unknown Interference
    Tadao Hoshino, Takahide Yanagi
    http://arxiv.org/abs/2108.07455v1

    • [stat.ME]Density Sharpening: Principles and Applications to Discrete Data Analysis
    Subhadeep Mukhopadhyay
    http://arxiv.org/abs/2108.07372v1

    • [stat.ME]Detecting changes in covariance via random matrix theory
    Sean Ryan, Rebecca Killick
    http://arxiv.org/abs/2108.07340v1

    • [stat.ME]Modelling Time-Varying First and Second-Order Structure of Time Series via Wavelets and Differencing
    Euan T. McGonigle, Rebecca Killick, Matthew A. Nunes
    http://arxiv.org/abs/2108.07550v1

    • [stat.ME]Testing Multiple Linear Regression Systems with Metamorphic Testing
    Quang-Hung Luu, Man F. Lau, Sebastian P. H. Ng, Tsong Yueh Chen
    http://arxiv.org/abs/2108.07584v1

    • [stat.ML]InfoGram and Admissible Machine Learning
    Subhadeep Mukhopadhyay
    http://arxiv.org/abs/2108.07380v1

    • [stat.ML]Semi-parametric Bayesian Additive Regression Trees
    Estevão B. Prado, Andrew C. Parnell, Nathan McJames, Ann O’Shea, Rafael A. Moral
    http://arxiv.org/abs/2108.07636v1