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.DB - 数据库
    cs.DC - 分布式、并行与集群计算
    cs.DL - 数字图书馆
    cs.HC - 人机接口
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.MA - 多代理系统
    cs.MM - 多媒体
    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.SD - 声音处理
    cs.SI - 社交网络与信息网络
    eess.AS - 语音处理
    eess.IV - 图像与视频处理
    eess.SY - 系统和控制
    math.AC - 交换代数
    math.OC - 优化与控制
    math.ST - 统计理论
    physics.data-an - 数据分析、 统计和概率
    physics.flu-dyn - 流体动力学
    physics.soc-ph - 物理学与社会
    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]A Comparison of Contextual and Non-Contextual Preference Ranking for Set Addition Problems
    • [cs.AI]An ontology for the formalization and visualization of scientific knowledge
    • [cs.AI]Integrating Planning, Execution and Monitoring in the presence of Open World Novelties: Case Study of an Open World Monopoly Solver
    • [cs.AI]Parallel and Multi-Objective Falsification with Scenic and VerifAI
    • [cs.AI]Rail Topology Ontology: A Rail Infrastructure Base Ontology
    • [cs.AI]Safe Learning of Lifted Action Models
    • [cs.AR]WinoCNN: Kernel Sharing Winograd Systolic Array for Efficient Convolutional Neural Network Acceleration on FPGAs
    • [cs.CL]A Robust Deep Ensemble Classifier for Figurative Language Detection
    • [cs.CL]A Survey on Low-Resource Neural Machine Translation
    • [cs.CL]A Systematic Survey of Text Worlds as Embodied Natural Language Environments
    • [cs.CL]Benchmarking for Biomedical Natural Language Processing Tasks with a Domain Specific ALBERT
    • [cs.CL]Improved Language Identification Through Cross-Lingual Self-Supervised Learning
    • [cs.CL]Joint Models for Answer Verification in Question Answering Systems
    • [cs.CL]Learning Syntactic Dense Embedding with Correlation Graph for Automatic Readability Assessment
    • [cs.CL]Levi Graph AMR Parser using Heterogeneous Attention
    • [cs.CL]UniRE: A Unified Label Space for Entity Relation Extraction
    • [cs.CL]Using Machine Translation to Localize Task Oriented NLG Output
    • [cs.CR]SherLOCKED: A Detective-themed Serious Game for Cyber Security Education
    • [cs.CV]A Multi-modal and Multi-task Learning Method for Action Unit and Expression Recognition
    • [cs.CV]A Multi-task Mean Teacher for Semi-supervised Facial Affective Behavior Analysis
    • [cs.CV]Action Unit Detection with Joint Adaptive Attention and Graph Relation
    • [cs.CV]Activated Gradients for Deep Neural Networks
    • [cs.CV]Beyond Farthest Point Sampling in Point-Wise Analysis
    • [cs.CV]Cross-modal Attention for MRI and Ultrasound Volume Registration
    • [cs.CV]Deep Image Synthesis from Intuitive User Input: A Review and Perspectives
    • [cs.CV]Effectiveness of State-of-the-Art Super Resolution Algorithms in Surveillance Environment
    • [cs.CV]Emotion Recognition with Incomplete Labels Using Modified Multi-task Learning Technique
    • [cs.CV]Event-Based Feature Tracking in Continuous Time with Sliding Window Optimization
    • [cs.CV]Fast Pixel-Matching for Video Object Segmentation
    • [cs.CV]Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors
    • [cs.CV]Graph-based Deep Generative Modelling for Document Layout Generation
    • [cs.CV]Hoechst Is All You Need: LymphocyteClassification with Deep Learning
    • [cs.CV]Interpretable Compositional Convolutional Neural Networks
    • [cs.CV]JPGNet: Joint Predictive Filtering and Generative Network for Image Inpainting
    • [cs.CV]Joint Matrix Decomposition for Deep Convolutional Neural Networks Compression
    • [cs.CV]Learning Cascaded Detection Tasks with Weakly-Supervised Domain Adaptation
    • [cs.CV]Memes in the Wild: Assessing the Generalizability of the Hateful Memes Challenge Dataset
    • [cs.CV]Multi-Modal Association based Grouping for Form Structure Extraction
    • [cs.CV]Multimodal Icon Annotation For Mobile Applications
    • [cs.CV]Multitask Multi-database Emotion Recognition
    • [cs.CV]MutualEyeContact: A conversation analysis tool with focus on eye contact
    • [cs.CV]Mutually-aware Sub-Graphs Differentiable Architecture Search
    • [cs.CV]On the Challenges of Open World Recognitionunder Shifting Visual Domains
    • [cs.CV]Prior-Guided Multi-View 3D Head Reconstruction
    • [cs.CV]RGB Stream Is Enough for Temporal Action Detection
    • [cs.CV]Score refinement for confidence-based 3D multi-object tracking
    • [cs.CV]Semantic Segmentation on Multiple Visual Domains
    • [cs.CV]Semantic and Geometric Unfolding of StyleGAN Latent Space
    • [cs.CV]Seven Basic Expression Recognition Using ResNet-18
    • [cs.CV]StyleCariGAN: Caricature Generation via StyleGAN Feature Map Modulation
    • [cs.CV]Towards Robust General Medical Image Segmentation
    • [cs.CV]Unity Perception: Generate Synthetic Data for Computer Vision
    • [cs.CV]UrbanScene3D: A Large Scale Urban Scene Dataset and Simulator
    • [cs.CV]ViTGAN: Training GANs with Vision Transformers
    • [cs.CV]Wavelet Transform-assisted Adaptive Generative Modeling for Colorization
    • [cs.CV]White-Box Cartoonization Using An Extended GAN Framework
    • [cs.DB]Can Deep Neural Networks Predict Data Correlations from Column Names?
    • [cs.DB]Redescription Model Mining
    • [cs.DC]Experiences with Integrating Custos SecurityServices
    • [cs.DC]FedAdapt: Adaptive Offloading for IoT Devices in Federated Learning
    • [cs.DL]Being Together in Place as a Catalyst for Scientific Advance
    • [cs.DL]Bib2Auth: Deep Learning Approach for Author Disambiguation using Bibliographic Data
    • [cs.HC]Crowd Sensing and Living Lab Outdoor Experimentation Made Easy
    • [cs.IR]CausalRec: Causal Inference for Visual Debiasing in Visually-Aware Recommendation
    • [cs.IR]Graph Neural Pre-training for Enhancing Recommendations using Side Information
    • [cs.IT]Information cohomology of classical vector-valued observables
    • [cs.IT]Massive MIMO Communication with Intelligent Reflecting Surface
    • [cs.IT]Neural-Network-Optimized Degree-Specific Weights for LDPC MinSum Decoding
    • [cs.IT]On pure MDS asymmetric entanglement-assisted quantum error-correcting codes
    • [cs.IT]Optimal three-weight cyclic codes whose duals are also optimal
    • [cs.IT]Sketching and Sequence Alignment: A Rate-Distortion Perspective
    • [cs.LG]ANCER: Anisotropic Certification via Sample-wise Volume Maximization
    • [cs.LG]ARC: Adversarially Robust Control Policies for Autonomous Vehicles
    • [cs.LG]Adversarial Domain Adaptation with Self-Training for EEG-based Sleep Stage Classification
    • [cs.LG]Adversarial Mixture Density Networks: Learning to Drive Safely from Collision Data
    • [cs.LG]Attend2Pack: Bin Packing through Deep Reinforcement Learning with Attention
    • [cs.LG]Autoencoder-driven Spiral Representation Learning for Gravitational Wave Surrogate Modelling
    • [cs.LG]Batch Inverse-Variance Weighting: Deep Heteroscedastic Regression
    • [cs.LG]Convergence analysis for gradient flows in the training of artificial neural networks with ReLU activation
    • [cs.LG]Differentially private training of neural networks with Langevin dynamics forcalibrated predictive uncertainty
    • [cs.LG]Does Form Follow Function? An Empirical Exploration of the Impact of Deep Neural Network Architecture Design on Hardware-Specific Acceleration
    • [cs.LG]Exploring Dropout Discriminator for Domain Adaptation
    • [cs.LG]Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform
    • [cs.LG]Form2Seq : A Framework for Higher-Order Form Structure Extraction
    • [cs.LG]Group-Node Attention for Community Evolution Prediction
    • [cs.LG]How to choose an Explainability Method? Towards a Methodical Implementation of XAI in Practice
    • [cs.LG]IDRLnet: A Physics-Informed Neural Network Library
    • [cs.LG]Learning to Delegate for Large-scale Vehicle Routing
    • [cs.LG]Learning to Detect Adversarial Examples Based on Class Scores
    • [cs.LG]Likelihood ratio-based policy gradient methods for distorted risk measures: A non-asymptotic analysis
    • [cs.LG]Lithography Hotspot Detection via Heterogeneous Federated Learning with Local Adaptation
    • [cs.LG]MCMC Variational Inference via Uncorrected Hamiltonian Annealing
    • [cs.LG]Measuring and Improving Model-Moderator Collaboration using Uncertainty Estimation
    • [cs.LG]Model compression as constrained optimization, with application to neural nets. Part V: combining compressions
    • [cs.LG]Multi-headed Neural Ensemble Search
    • [cs.LG]Multi-level Stress Assessment from ECG in a Virtual Reality Environment using Multimodal Fusion
    • [cs.LG]Multiaccurate Proxies for Downstream Fairness
    • [cs.LG]Offline reinforcement learning with uncertainty for treatment strategies in sepsis
    • [cs.LG]On the Variance of the Fisher Information for Deep Learning
    • [cs.LG]Online Adaptation to Label Distribution Shift
    • [cs.LG]Optimal Gradient-based Algorithms for Non-concave Bandit Optimization
    • [cs.LG]Personalized Federated Learning over non-IID Data for Indoor Localization
    • [cs.LG]REX: Revisiting Budgeted Training with an Improved Schedule
    • [cs.LG]Robust Counterfactual Explanations on Graph Neural Networks
    • [cs.LG]Safe Exploration by Solving Early Terminated MDP
    • [cs.LG]Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation
    • [cs.LG]Specialists Outperform Generalists in Ensemble Classification
    • [cs.LG]Structured Model Pruning of Convolutional Networks on Tensor Processing Units
    • [cs.LG]Understanding surrogate explanations: the interplay between complexity, fidelity and coverage
    • [cs.LG]Understanding the Distributions of Aggregation Layers in Deep Neural Networks
    • [cs.LG]Universal Multilayer Network Exploration by Random Walk with Restart
    • [cs.MA]Intelligent Link Adaptation for Grant-Free Access Cellular Networks: A Distributed Deep Reinforcement Learning Approach
    • [cs.MM]Hacking VMAF and VMAF NEG: metrics vulnerability to different preprocessing
    • [cs.NE]Even Faster SNN Simulation with Lazy+Event-driven Plasticity and Shared Atomics
    • [cs.NI]A First Look at Class Incremental Learning in Deep Learning Mobile Traffic Classification
    • [cs.RO]Aligning an optical interferometer with beam divergence control and continuous action space
    • [cs.RO]BayesSimIG: Scalable Parameter Inference for Adaptive Domain Randomization with IsaacGym
    • [cs.RO]Behavior Self-Organization Supports Task Inference for Continual Robot Learning
    • [cs.RO]Control Lyapunov Functions for Compliant Hybrid Zero Dynamic Walking
    • [cs.RO]Distributed formation control for manipulator end-effectors
    • [cs.RO]Dynamic Modeling of Bucket-Soil Interactions Using Koopman-DFL Lifting Linearization for Model Predictive Contouring Control of Autonomous Excavators
    • [cs.RO]Excavation Learning for Rigid Objects in Clutter
    • [cs.RO]Learning Interaction-aware Guidance Policies for Motion Planning in Dense Traffic Scenarios
    • [cs.RO]Learning structured approximations of operations research problems
    • [cs.RO]Planning of efficient trajectories in robotized assembly of aerostructures exploiting kinematic redundancy
    • [cs.RO]Probabilistic Trajectory Prediction with Structural Constraints
    • [cs.RO]Semantic Feature Matching for Robust Mapping in Agriculture
    • [cs.SD]EasyCom: An Augmented Reality Dataset to Support Algorithms for Easy Communication in Noisy Environments
    • [cs.SD]Improved Breath Phase and Continuous Adventitious Sound Detection in Lung and Tracheal Sound Using Mixed Set Training and Domain Adaptation
    • [cs.SD]Multi-path Convolutional Neural Networks Efficiently Improve Feature Extraction in Continuous Adventitious Lung Sound Detection
    • [cs.SI]Causal Inference for Influence Propagation — Identifiability of the Independent Cascade Model
    • [cs.SI]Using Network Analysis on Twitter Data to Identify Threats on Indonesian Digital Activism
    • [eess.AS]Training a Deep Neural Network via Policy Gradients for Blind Source Separation in Polyphonic Music Recordings
    • [eess.IV]3D RegNet: Deep Learning Model for COVID-19 Diagnosis on Chest CT Image
    • [eess.IV]A Deep Discontinuity-Preserving Image Registration Network
    • [eess.IV]CASPIANET++: A Multidimensional Channel-Spatial Asymmetric Attention Network with Noisy Student Curriculum Learning Paradigm for Brain Tumor Segmentation
    • [eess.IV]Comparison of 2D vs. 3D U-Net Organ Segmentation in abdominal 3D CT images
    • [eess.IV]Deep Learning models for benign and malign Ocular Tumor Growth Estimation
    • [eess.IV]Hepatocellular Carcinoma Segmentation fromDigital Subtraction Angiography Videos usingLearnable Temporal Difference
    • [eess.IV]LIFE: A Generalizable Autodidactic Pipeline for 3D OCT-A Vessel Segmentation
    • [eess.IV]Modality specific U-Net variants for biomedical image segmentation: A survey
    • [eess.IV]Retinal OCT Denoising with Pseudo-Multimodal Fusion Network
    • [eess.SY]Bayesian Error-in-Variables Models for the Identification of Power Networks
    • [math.AC]Staged tree models with toric structure
    • [math.OC]Block Alternating Bregman Majorization Minimization with Extrapolation
    • [math.OC]Deep Learning for Mean Field Games and Mean Field Control with Applications to Finance
    • [math.OC]Structured Hammerstein-Wiener Model Learning for Model Predictive Control
    • [math.ST]Diagonal Nonlinear Transformations Preserve Structure in Covariance and Precision Matrices
    • [math.ST]Higher Order Imprecise Probabilities and Statistical Testing
    • [math.ST]Statistical Estimation and Nonlinear Filtering in Environmental Pollution
    • [math.ST]Two Sample Test for Extrinsic Antimeans on Planar Kendall Shape Spaces with an Application to Medical Imaging
    • [physics.data-an]Entropy, Information, and the Updating of Probabilities
    • [physics.flu-dyn]Deep Learning for Reduced Order Modelling and Efficient Temporal Evolution of Fluid Simulations
    • [physics.soc-ph]Quantifying the rise and fall of scientific fields
    • [stat.AP]Coastal water quality prediction based on machine learning with feature interpretation and spatio-temporal analysis
    • [stat.AP]From Many to One: Consensus Inference in a MIP
    • [stat.AP]Prediction of butt rot volume in Norway spruce forest stands using harvester, remotely sensed and environmental data
    • [stat.CO]Fast compression of MCMC output
    • [stat.ME]Hypothetical estimands in clinical trials: a unification of causal inference and missing data methods
    • [stat.ME]Joint Modeling of Longitudinal and Survival Data with Censored Single-index Varying Coefficient Models
    • [stat.ME]Parsimonious Hidden Markov Models for Matrix-Variate Longitudinal Data
    • [stat.ML]Continual Learning in the Teacher-Student Setup: Impact of Task Similarity
    • [stat.ML]Generalization of the Change of Variables Formula with Applications to Residual Flows
    • [stat.ML]The Bayesian Learning Rule

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

    • [cs.AI]A Comparison of Contextual and Non-Contextual Preference Ranking for Set Addition Problems
    Timo Bertram, Johannes Fürnkranz, Martin Müller
    http://arxiv.org/abs/2107.04438v1

    • [cs.AI]An ontology for the formalization and visualization of scientific knowledge
    Vincenzo Daponte, Gilles Falquet
    http://arxiv.org/abs/2107.04347v1

    • [cs.AI]Integrating Planning, Execution and Monitoring in the presence of Open World Novelties: Case Study of an Open World Monopoly Solver
    Sriram Gopalakrishnan, Utkarsh Soni, Tung Thai, Panagiotis Lymperopoulos, Matthias Scheutz, Subbarao Kambhampati
    http://arxiv.org/abs/2107.04303v1

    • [cs.AI]Parallel and Multi-Objective Falsification with Scenic and VerifAI
    Kesav Viswanadha, Edward Kim, Francis Indaheng, Daniel J. Fremont, Sanjit A. Seshia
    http://arxiv.org/abs/2107.04164v1

    • [cs.AI]Rail Topology Ontology: A Rail Infrastructure Base Ontology
    Stefan Bischof, Gottfried Schenner
    http://arxiv.org/abs/2107.04378v1

    • [cs.AI]Safe Learning of Lifted Action Models
    Brendan Juba, Hai S. Le, Roni Stern
    http://arxiv.org/abs/2107.04169v1

    • [cs.AR]WinoCNN: Kernel Sharing Winograd Systolic Array for Efficient Convolutional Neural Network Acceleration on FPGAs
    Xinheng Liu, Yao Chen, Cong Hao, Ashutosh Dhar, Deming Chen
    http://arxiv.org/abs/2107.04244v1

    • [cs.CL]A Robust Deep Ensemble Classifier for Figurative Language Detection
    Rolandos Alexandros Potamias, Georgios Siolas, Andreas - Georgios Stafylopatis
    http://arxiv.org/abs/2107.04372v1

    • [cs.CL]A Survey on Low-Resource Neural Machine Translation
    Rui Wang, Xu Tan, Renqian Luo, Tao Qin, Tie-Yan Liu
    http://arxiv.org/abs/2107.04239v1

    • [cs.CL]A Systematic Survey of Text Worlds as Embodied Natural Language Environments
    Peter A Jansen
    http://arxiv.org/abs/2107.04132v1

    • [cs.CL]Benchmarking for Biomedical Natural Language Processing Tasks with a Domain Specific ALBERT
    Usman Naseem, Adam G. Dunn, Matloob Khushi, Jinman Kim
    http://arxiv.org/abs/2107.04374v1

    • [cs.CL]Improved Language Identification Through Cross-Lingual Self-Supervised Learning
    Andros Tjandra, Diptanu Gon Choudhury, Frank Zhang, Kritika Singh, Alexei Baevski, Assaf Sela, Yatharth Saraf, Michael Auli
    http://arxiv.org/abs/2107.04082v1

    • [cs.CL]Joint Models for Answer Verification in Question Answering Systems
    Zeyu Zhang, Thuy Vu, Alessandro Moschitti
    http://arxiv.org/abs/2107.04217v1

    • [cs.CL]Learning Syntactic Dense Embedding with Correlation Graph for Automatic Readability Assessment
    Xinying Qiu, Yuan Chen, Hanwu Chen, Jian-Yun Nie, Yuming Shen, Dawei Lu
    http://arxiv.org/abs/2107.04268v1

    • [cs.CL]Levi Graph AMR Parser using Heterogeneous Attention
    Han He, Jinho D. Choi
    http://arxiv.org/abs/2107.04152v1

    • [cs.CL]UniRE: A Unified Label Space for Entity Relation Extraction
    Yijun Wang, Changzhi Sun, Yuanbin Wu, Hao Zhou, Lei Li, Junchi Yan
    http://arxiv.org/abs/2107.04292v1

    • [cs.CL]Using Machine Translation to Localize Task Oriented NLG Output
    Scott Roy, Cliff Brunk, Kyu-Young Kim, Justin Zhao, Markus Freitag, Mihir Kale, Gagan Bansal, Sidharth Mudgal, Chris Varano
    http://arxiv.org/abs/2107.04512v1

    • [cs.CR]SherLOCKED: A Detective-themed Serious Game for Cyber Security Education
    Alice Jaffray, Conor Finn, Jason R. C. Nurse
    http://arxiv.org/abs/2107.04506v1

    • [cs.CV]A Multi-modal and Multi-task Learning Method for Action Unit and Expression Recognition
    Yue Jin, Tianqing Zheng, Chao Gao, Guoqiang Xu
    http://arxiv.org/abs/2107.04187v1

    • [cs.CV]A Multi-task Mean Teacher for Semi-supervised Facial Affective Behavior Analysis
    Lingfeng Wang, Shisen Wang
    http://arxiv.org/abs/2107.04225v1

    • [cs.CV]Action Unit Detection with Joint Adaptive Attention and Graph Relation
    Chenggong Zhang, Juan Song, Qingyang Zhang, Weilong Dong, Ruomeng Ding, Zhilei Liu
    http://arxiv.org/abs/2107.04389v1

    • [cs.CV]Activated Gradients for Deep Neural Networks
    Mei Liu, Liangming Chen, Xiaohao Du, Long Jin, Mingsheng Shang
    http://arxiv.org/abs/2107.04228v1

    • [cs.CV]Beyond Farthest Point Sampling in Point-Wise Analysis
    Yiqun Lin, Lichang Chen, Haibin Huang, Chongyang Ma, Xiaoguang Han, Shuguang Cui
    http://arxiv.org/abs/2107.04291v1

    • [cs.CV]Cross-modal Attention for MRI and Ultrasound Volume Registration
    Xinrui Song, Hengtao Guo, Xuanang Xu, Hanqing Chao, Sheng Xu, Baris Turkbey, Bradford J. Wood, Ge Wang, Pingkun Yan
    http://arxiv.org/abs/2107.04548v1

    • [cs.CV]Deep Image Synthesis from Intuitive User Input: A Review and Perspectives
    Yuan Xue, Yuan-Chen Guo, Han Zhang, Tao Xu, Song-Hai Zhang, Xiaolei Huang
    http://arxiv.org/abs/2107.04240v1

    • [cs.CV]Effectiveness of State-of-the-Art Super Resolution Algorithms in Surveillance Environment
    Muhammad Ali Farooq, Ammar Ali Khan, Ansar Ahmad, Rana Hammad Raza
    http://arxiv.org/abs/2107.04133v1

    • [cs.CV]Emotion Recognition with Incomplete Labels Using Modified Multi-task Learning Technique
    Phan Tran Dac Thinh, Hoang Manh Hung, Hyung-Jeong Yang, Soo-Hyung Kim, Guee-Sang Lee
    http://arxiv.org/abs/2107.04192v1

    • [cs.CV]Event-Based Feature Tracking in Continuous Time with Sliding Window Optimization
    Jason Chui, Simon Klenk, Daniel Cremers
    http://arxiv.org/abs/2107.04536v1

    • [cs.CV]Fast Pixel-Matching for Video Object Segmentation
    Siyue Yu, Jimin Xiao, BingFeng Zhang, Eng Gee Lim
    http://arxiv.org/abs/2107.04279v1

    • [cs.CV]Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors
    Tobias Riedlinger, Matthias Rottmann, Marius Schubert, Hanno Gottschalk
    http://arxiv.org/abs/2107.04517v1

    • [cs.CV]Graph-based Deep Generative Modelling for Document Layout Generation
    Sanket Biswas, Pau Riba, Josep Lladós, Umapada Pal
    http://arxiv.org/abs/2107.04357v1

    • [cs.CV]Hoechst Is All You Need: LymphocyteClassification with Deep Learning
    Jessica Cooper, In Hwa Um, Ognjen Arandjelović, David J Harrison
    http://arxiv.org/abs/2107.04388v1

    • [cs.CV]Interpretable Compositional Convolutional Neural Networks
    Wen Shen, Zhihua Wei, Shikun Huang, Binbin Zhang, Jiaqi Fan, Ping Zhao, Quanshi Zhang
    http://arxiv.org/abs/2107.04474v1

    • [cs.CV]JPGNet: Joint Predictive Filtering and Generative Network for Image Inpainting
    Xiaoguang Li, Qing Guo, Felix Juefei-Xu, Hongkai Yu, Yang Liu, Song wang
    http://arxiv.org/abs/2107.04281v1

    • [cs.CV]Joint Matrix Decomposition for Deep Convolutional Neural Networks Compression
    Shaowu Chen, Jihao Zhou, Weize Sun, Lei Huang
    http://arxiv.org/abs/2107.04386v1

    • [cs.CV]Learning Cascaded Detection Tasks with Weakly-Supervised Domain Adaptation
    Niklas Hanselmann, Nick Schneider, Benedikt Ortelt, Andreas Geiger
    http://arxiv.org/abs/2107.04523v1

    • [cs.CV]Memes in the Wild: Assessing the Generalizability of the Hateful Memes Challenge Dataset
    Hannah Rose Kirk, Yennie Jun, Paulius Rauba, Gal Wachtel, Ruining Li, Xingjian Bai, Noah Broestl, Martin Doff-Sotta, Aleksandar Shtedritski, Yuki M. Asano
    http://arxiv.org/abs/2107.04313v1

    • [cs.CV]Multi-Modal Association based Grouping for Form Structure Extraction
    Milan Aggarwal, Mausoom Sarkar, Hiresh Gupta, Balaji Krishnamurthy
    http://arxiv.org/abs/2107.04396v1

    • [cs.CV]Multimodal Icon Annotation For Mobile Applications
    Xiaoxue Zang, Ying Xu, Jindong Chen
    http://arxiv.org/abs/2107.04452v1

    • [cs.CV]Multitask Multi-database Emotion Recognition
    Manh Tu Vu, Marie Beurton-Aimar
    http://arxiv.org/abs/2107.04127v1

    • [cs.CV]MutualEyeContact: A conversation analysis tool with focus on eye contact
    Alexander Schäfer, Tomoko Isomura, Gerd Reis, Katsumi Watanabe, Didier Stricker
    http://arxiv.org/abs/2107.04476v1

    • [cs.CV]Mutually-aware Sub-Graphs Differentiable Architecture Search
    Haoxian Tan, Sheng Guo, Yujie Zhong, Weilin Huang
    http://arxiv.org/abs/2107.04324v1

    • [cs.CV]On the Challenges of Open World Recognitionunder Shifting Visual Domains
    Dario Fontanel, Fabio Cermelli, Massimiliano Mancini, Barbara Caputo
    http://arxiv.org/abs/2107.04461v1

    • [cs.CV]Prior-Guided Multi-View 3D Head Reconstruction
    Xueying Wang, Yudong Guo, Zhongqi Yang, Juyong Zhang
    http://arxiv.org/abs/2107.04277v1

    • [cs.CV]RGB Stream Is Enough for Temporal Action Detection
    Chenhao Wang, Hongxiang Cai, Yuxin Zou, Yichao Xiong
    http://arxiv.org/abs/2107.04362v1

    • [cs.CV]Score refinement for confidence-based 3D multi-object tracking
    Nuri Benbarka, Jona Schröder, Andreas Zell
    http://arxiv.org/abs/2107.04327v1

    • [cs.CV]Semantic Segmentation on Multiple Visual Domains
    Floris Naber
    http://arxiv.org/abs/2107.04326v1

    • [cs.CV]Semantic and Geometric Unfolding of StyleGAN Latent Space
    Mustafa Shukor, Xu Yao, Bharath Bhushan Damodaran, Pierre Hellier
    http://arxiv.org/abs/2107.04481v1

    • [cs.CV]Seven Basic Expression Recognition Using ResNet-18
    Satnam Singh, Doris Schicker
    http://arxiv.org/abs/2107.04569v1

    • [cs.CV]StyleCariGAN: Caricature Generation via StyleGAN Feature Map Modulation
    Wonjong Jang, Gwangjin Ju, Yucheol Jung, Jiaolong Yang, Xin Tong, Seungyong Lee
    http://arxiv.org/abs/2107.04331v1

    • [cs.CV]Towards Robust General Medical Image Segmentation
    Laura Daza, Juan C. Pérez, Pablo Arbeláez
    http://arxiv.org/abs/2107.04263v1

    • [cs.CV]Unity Perception: Generate Synthetic Data for Computer Vision
    Steve Borkman, Adam Crespi, Saurav Dhakad, Sujoy Ganguly, Jonathan Hogins, You-Cyuan Jhang, Mohsen Kamalzadeh, Bowen Li, Steven Leal, Pete Parisi, Cesar Romero, Wesley Smith, Alex Thaman, Samuel Warren, Nupur Yadav
    http://arxiv.org/abs/2107.04259v1

    • [cs.CV]UrbanScene3D: A Large Scale Urban Scene Dataset and Simulator
    Yilin Liu, Fuyou Xue, Hui Huang
    http://arxiv.org/abs/2107.04286v1

    • [cs.CV]ViTGAN: Training GANs with Vision Transformers
    Kwonjoon Lee, Huiwen Chang, Lu Jiang, Han Zhang, Zhuowen Tu, Ce Liu
    http://arxiv.org/abs/2107.04589v1

    • [cs.CV]Wavelet Transform-assisted Adaptive Generative Modeling for Colorization
    Jin Li, Wanyun Li, Zichen Xu, Yuhao Wang, Qiegen Liu
    http://arxiv.org/abs/2107.04261v1

    • [cs.CV]White-Box Cartoonization Using An Extended GAN Framework
    Amey Thakur, Hasan Rizvi, Mega Satish
    http://arxiv.org/abs/2107.04551v1

    • [cs.DB]Can Deep Neural Networks Predict Data Correlations from Column Names?
    Immanuel Trummer
    http://arxiv.org/abs/2107.04553v1

    • [cs.DB]Redescription Model Mining
    Felix I. Stamm, Martin Becker, Markus Strohmaier, Florian Lemmerich
    http://arxiv.org/abs/2107.04462v1

    • [cs.DC]Experiences with Integrating Custos SecurityServices
    Isuru Ranawaka, Samitha Liyanage, Dannon Baker, Alexandru Mahmoud, Juleen Graham, Terry Fleury, Dimuthu Wannipurage, Yu Ma, Enis Afgan, Jim Basney, Suresh Marru, Marlon Pierce
    http://arxiv.org/abs/2107.04172v1

    • [cs.DC]FedAdapt: Adaptive Offloading for IoT Devices in Federated Learning
    Di Wu, Rehmat Ullah, Paul Harvey, Peter Kilpatrick, Ivor Spence, Blesson Varghese
    http://arxiv.org/abs/2107.04271v1

    • [cs.DL]Being Together in Place as a Catalyst for Scientific Advance
    Eamon Duede, Misha Teplistkiy, Karim Lakhani, James Evans
    http://arxiv.org/abs/2107.04165v1

    • [cs.DL]Bib2Auth: Deep Learning Approach for Author Disambiguation using Bibliographic Data
    Zeyd Boukhers, Nagaraj Bahubali, Abinaya Thulsi Chandrasekaran, Adarsh Anand, Soniya Manchenahalli Gnanendra Prasadand, Sriram Aralappa
    http://arxiv.org/abs/2107.04382v1

    • [cs.HC]Crowd Sensing and Living Lab Outdoor Experimentation Made Easy
    Evangelos Pournaras, Atif Nabi Ghulam, Renato Kunz, Regula Hänggli
    http://arxiv.org/abs/2107.04117v1

    • [cs.IR]CausalRec: Causal Inference for Visual Debiasing in Visually-Aware Recommendation
    Ruihong Qiu, Sen Wang, Zhi Chen, Hongzhi Yin, Zi Huang
    http://arxiv.org/abs/2107.02390v2

    • [cs.IR]Graph Neural Pre-training for Enhancing Recommendations using Side Information
    Zaiqiao Meng, Siwei Liu, Craig Macdonald, Iadh Ounis
    http://arxiv.org/abs/2107.03936v2

    • [cs.IT]Information cohomology of classical vector-valued observables
    Juan Pablo Vigneaux
    http://arxiv.org/abs/2107.04377v1

    • [cs.IT]Massive MIMO Communication with Intelligent Reflecting Surface
    Zhaorui Wang, Liang Liu, Shuowen Zhang, Shuguang Cui
    http://arxiv.org/abs/2107.04255v1

    • [cs.IT]Neural-Network-Optimized Degree-Specific Weights for LDPC MinSum Decoding
    Linfang Wang, Sean Chen, Jonathan Nguyen, Divsalar Dariush, Richard Wesel
    http://arxiv.org/abs/2107.04221v1

    • [cs.IT]On pure MDS asymmetric entanglement-assisted quantum error-correcting codes
    Ziteng Huang, Weijun Fang, Fang-Wei Fu
    http://arxiv.org/abs/2107.04166v1

    • [cs.IT]Optimal three-weight cyclic codes whose duals are also optimal
    Gerardo Vega, Félix Hernández
    http://arxiv.org/abs/2107.04579v1

    • [cs.IT]Sketching and Sequence Alignment: A Rate-Distortion Perspective
    Ilan Shomorony, Govinda M. Kamath
    http://arxiv.org/abs/2107.04202v1

    • [cs.LG]ANCER: Anisotropic Certification via Sample-wise Volume Maximization
    Francisco Eiras, Motasem Alfarra, M. Pawan Kumar, Philip H. S. Torr, Puneet K. Dokania, Bernard Ghanem, Adel Bibi
    http://arxiv.org/abs/2107.04570v1

    • [cs.LG]ARC: Adversarially Robust Control Policies for Autonomous Vehicles
    Sampo Kuutti, Saber Fallah, Richard Bowden
    http://arxiv.org/abs/2107.04487v1

    • [cs.LG]Adversarial Domain Adaptation with Self-Training for EEG-based Sleep Stage Classification
    Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li, Cuntai Guan
    http://arxiv.org/abs/2107.04470v1

    • [cs.LG]Adversarial Mixture Density Networks: Learning to Drive Safely from Collision Data
    Sampo Kuutti, Saber Fallah, Richard Bowden
    http://arxiv.org/abs/2107.04485v1

    • [cs.LG]Attend2Pack: Bin Packing through Deep Reinforcement Learning with Attention
    Jingwei Zhang, Bin Zi, Xiaoyu Ge
    http://arxiv.org/abs/2107.04333v1

    • [cs.LG]Autoencoder-driven Spiral Representation Learning for Gravitational Wave Surrogate Modelling
    Paraskevi Nousi, Styliani-Christina Fragkouli, Nikolaos Passalis, Panagiotis Iosif, Theocharis Apostolatos, George Pappas, Nikolaos Stergioulas, Anastasios Tefas
    http://arxiv.org/abs/2107.04312v1

    • [cs.LG]Batch Inverse-Variance Weighting: Deep Heteroscedastic Regression
    Vincent Mai, Waleed Khamies, Liam Paull
    http://arxiv.org/abs/2107.04497v1

    • [cs.LG]Convergence analysis for gradient flows in the training of artificial neural networks with ReLU activation
    Arnulf Jentzen, Adrian Riekert
    http://arxiv.org/abs/2107.04479v1

    • [cs.LG]Differentially private training of neural networks with Langevin dynamics forcalibrated predictive uncertainty
    Moritz Knolle, Alexander Ziller, Dmitrii Usynin, Rickmer Braren, Marcus R. Makowski, Daniel Rueckert, Georgios Kaissis
    http://arxiv.org/abs/2107.04296v1

    • [cs.LG]Does Form Follow Function? An Empirical Exploration of the Impact of Deep Neural Network Architecture Design on Hardware-Specific Acceleration
    Saad Abbasi, Mohammad Javad Shafiee, Ellick Chan, Alexander Wong
    http://arxiv.org/abs/2107.04144v1

    • [cs.LG]Exploring Dropout Discriminator for Domain Adaptation
    Vinod K Kurmi, Venkatesh K Subramanian, Vinay P. Namboodiri
    http://arxiv.org/abs/2107.04231v1

    • [cs.LG]Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform
    Bo Liu, Chaowei Tan, Jiazhou Wang, Tao Zeng, Huasong Shan, Houpu Yao, Huang Heng, Peng Dai, Liefeng Bo, Yanqing Chen
    http://arxiv.org/abs/2107.04129v1

    • [cs.LG]Form2Seq : A Framework for Higher-Order Form Structure Extraction
    Milan Aggarwal, Hiresh Gupta, Mausoom Sarkar, Balaji Krishnamurthy
    http://arxiv.org/abs/2107.04419v1

    • [cs.LG]Group-Node Attention for Community Evolution Prediction
    Matt Revelle, Carlotta Domeniconi, Ben Gelman
    http://arxiv.org/abs/2107.04522v1

    • [cs.LG]How to choose an Explainability Method? Towards a Methodical Implementation of XAI in Practice
    Tom Vermeire, Thibault Laugel, Xavier Renard, David Martens, Marcin Detyniecki
    http://arxiv.org/abs/2107.04427v1

    • [cs.LG]IDRLnet: A Physics-Informed Neural Network Library
    Wei Peng, Jun Zhang, Weien Zhou, Xiaoyu Zhao, Wen Yao, Xiaoqian Chen
    http://arxiv.org/abs/2107.04320v1

    • [cs.LG]Learning to Delegate for Large-scale Vehicle Routing
    Sirui Li, Zhongxia Yan, Cathy Wu
    http://arxiv.org/abs/2107.04139v1

    • [cs.LG]Learning to Detect Adversarial Examples Based on Class Scores
    Tobias Uelwer, Felix Michels, Oliver De Candido
    http://arxiv.org/abs/2107.04435v1

    • [cs.LG]Likelihood ratio-based policy gradient methods for distorted risk measures: A non-asymptotic analysis
    Nithia Vijayan, Prashanth L. A
    http://arxiv.org/abs/2107.04422v1

    • [cs.LG]Lithography Hotspot Detection via Heterogeneous Federated Learning with Local Adaptation
    Xuezhong Lin, Jingyu Pan, Jinming Xu, Yiran Chen, Cheng Zhuo
    http://arxiv.org/abs/2107.04367v1

    • [cs.LG]MCMC Variational Inference via Uncorrected Hamiltonian Annealing
    Tomas Geffner, Justin Domke
    http://arxiv.org/abs/2107.04150v1

    • [cs.LG]Measuring and Improving Model-Moderator Collaboration using Uncertainty Estimation
    Ian D. Kivlichan, Zi Lin, Jeremiah Liu, Lucy Vasserman
    http://arxiv.org/abs/2107.04212v1

    • [cs.LG]Model compression as constrained optimization, with application to neural nets. Part V: combining compressions
    Miguel Á. Carreira-Perpiñán, Yerlan Idelbayev
    http://arxiv.org/abs/2107.04380v1

    • [cs.LG]Multi-headed Neural Ensemble Search
    Ashwin Raaghav Narayanan, Arber Zela, Tonmoy Saikia, Thomas Brox, Frank Hutter
    http://arxiv.org/abs/2107.04369v1

    • [cs.LG]Multi-level Stress Assessment from ECG in a Virtual Reality Environment using Multimodal Fusion
    Zeeshan Ahmad, Suha Rabbani, Muhammad Rehman Zafar, Syem Ishaque, Sridhar Krishnan, Naimul Khan
    http://arxiv.org/abs/2107.04566v1

    • [cs.LG]Multiaccurate Proxies for Downstream Fairness
    Emily Diana, Wesley Gill, Michael Kearns, Krishnaram Kenthapadi, Aaron Roth, Saeed Sharifi-Malvajerdi
    http://arxiv.org/abs/2107.04423v1

    • [cs.LG]Offline reinforcement learning with uncertainty for treatment strategies in sepsis
    Ran Liu, Joseph L. Greenstein, James C. Fackler, Jules Bergmann, Melania M. Bembea, Raimond L. Winslow
    http://arxiv.org/abs/2107.04491v1

    • [cs.LG]On the Variance of the Fisher Information for Deep Learning
    Alexander Soen, Ke Sun
    http://arxiv.org/abs/2107.04205v1

    • [cs.LG]Online Adaptation to Label Distribution Shift
    Ruihan Wu, Chuan Guo, Yi Su, Kilian Q. Weinberger
    http://arxiv.org/abs/2107.04520v1

    • [cs.LG]Optimal Gradient-based Algorithms for Non-concave Bandit Optimization
    Baihe Huang, Kaixuan Huang, Sham M. Kakade, Jason D. Lee, Qi Lei, Runzhe Wang, Jiaqi Yang
    http://arxiv.org/abs/2107.04518v1

    • [cs.LG]Personalized Federated Learning over non-IID Data for Indoor Localization
    Peng Wu, Tales Imbiriba, Junha Park, Sunwoo Kim, Pau Closas
    http://arxiv.org/abs/2107.04189v1

    • [cs.LG]REX: Revisiting Budgeted Training with an Improved Schedule
    John Chen, Cameron Wolfe, Anastasios Kyrillidis
    http://arxiv.org/abs/2107.04197v1

    • [cs.LG]Robust Counterfactual Explanations on Graph Neural Networks
    Mohit Bajaj, Lingyang Chu, Zi Yu Xue, Jian Pei, Lanjun Wang, Peter Cho-Ho Lam, Yong Zhang
    http://arxiv.org/abs/2107.04086v1

    • [cs.LG]Safe Exploration by Solving Early Terminated MDP
    Hao Sun, Ziping Xu, Meng Fang, Zhenghao Peng, Jiadong Guo, Bo Dai, Bolei Zhou
    http://arxiv.org/abs/2107.04200v1

    • [cs.LG]Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation
    Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Kritika Prakash, Andrew Trask, Rickmer Braren, Marcus Makowski, Daniel Rueckert, Georgios Kaissis
    http://arxiv.org/abs/2107.04265v1

    • [cs.LG]Specialists Outperform Generalists in Ensemble Classification
    Sascha Meyen, Frieder Göppert, Helen Alber, Ulrike von Luxburg, Volker H. Franz
    http://arxiv.org/abs/2107.04381v1

    • [cs.LG]Structured Model Pruning of Convolutional Networks on Tensor Processing Units
    Kongtao Chen, Ken Franko, Ruoxin Sang
    http://arxiv.org/abs/2107.04191v1

    • [cs.LG]Understanding surrogate explanations: the interplay between complexity, fidelity and coverage
    Rafael Poyiadzi, Xavier Renard, Thibault Laugel, Raul Santos-Rodriguez, Marcin Detyniecki
    http://arxiv.org/abs/2107.04309v1

    • [cs.LG]Understanding the Distributions of Aggregation Layers in Deep Neural Networks
    Eng-Jon Ong, Sameed Husain, Miroslaw Bober
    http://arxiv.org/abs/2107.04458v1

    • [cs.LG]Universal Multilayer Network Exploration by Random Walk with Restart
    Anthony Baptista, Aitor Gonzalez, Anaïs Baudot
    http://arxiv.org/abs/2107.04565v1

    • [cs.MA]Intelligent Link Adaptation for Grant-Free Access Cellular Networks: A Distributed Deep Reinforcement Learning Approach
    Joao V. C. Evangelista, Zeeshan Sattar, Georges Kaddoum, Bassant Selim, Aydin Sarraf
    http://arxiv.org/abs/2107.04145v1

    • [cs.MM]Hacking VMAF and VMAF NEG: metrics vulnerability to different preprocessing
    Maksim Siniukov, Anastasia Antsiferova, Dmitriy Kulikov, Dmitriy Vatolin
    http://arxiv.org/abs/2107.04510v1

    • [cs.NE]Even Faster SNN Simulation with Lazy+Event-driven Plasticity and Shared Atomics
    Dennis Bautembach, Iason Oikonomidis, Antonis Argyros
    http://arxiv.org/abs/2107.04092v1

    • [cs.NI]A First Look at Class Incremental Learning in Deep Learning Mobile Traffic Classification
    Giampaolo Bovenzi, Lixuan Yang, Alessandro Finamore, Giuseppe Aceto, Domenico Ciuonzo, Antonio Pescapè, Dario Rossi
    http://arxiv.org/abs/2107.04464v1

    • [cs.RO]Aligning an optical interferometer with beam divergence control and continuous action space
    Stepan Makarenko, Dmitry Sorokin, Alexander Ulanov, A. I. Lvovsky
    http://arxiv.org/abs/2107.04457v1

    • [cs.RO]BayesSimIG: Scalable Parameter Inference for Adaptive Domain Randomization with IsaacGym
    Rika Antonova, Fabio Ramos, Rafael Possas, Dieter Fox
    http://arxiv.org/abs/2107.04527v1

    • [cs.RO]Behavior Self-Organization Supports Task Inference for Continual Robot Learning
    Muhammad Burhan Hafez, Stefan Wermter
    http://arxiv.org/abs/2107.04533v1

    • [cs.RO]Control Lyapunov Functions for Compliant Hybrid Zero Dynamic Walking
    Jenna Reher, Aaron D. Ames
    http://arxiv.org/abs/2107.04241v1

    • [cs.RO]Distributed formation control for manipulator end-effectors
    Haiwen Wu, Bayu Jayawardhana, Hector Garcia de Marina, Dabo Xu
    http://arxiv.org/abs/2107.04141v1

    • [cs.RO]Dynamic Modeling of Bucket-Soil Interactions Using Koopman-DFL Lifting Linearization for Model Predictive Contouring Control of Autonomous Excavators
    Filippos E. Sotiropoulos, H. Harry Asada
    http://arxiv.org/abs/2107.04314v1

    • [cs.RO]Excavation Learning for Rigid Objects in Clutter
    Qingkai Lu, Liangjun Zhang
    http://arxiv.org/abs/2107.04171v1

    • [cs.RO]Learning Interaction-aware Guidance Policies for Motion Planning in Dense Traffic Scenarios
    Bruno Brito, Achin Agarwal, Javier Alonso-Mora
    http://arxiv.org/abs/2107.04538v1

    • [cs.RO]Learning structured approximations of operations research problems
    Axel Parmentier
    http://arxiv.org/abs/2107.04323v1

    • [cs.RO]Planning of efficient trajectories in robotized assembly of aerostructures exploiting kinematic redundancy
    Federica Storiale, Enrico Ferrentino, Pasquale Chiacchio
    http://arxiv.org/abs/2107.04341v1

    • [cs.RO]Probabilistic Trajectory Prediction with Structural Constraints
    Weiming Zhi, Lionel Ott, Fabio Ramos
    http://arxiv.org/abs/2107.04193v1

    • [cs.RO]Semantic Feature Matching for Robust Mapping in Agriculture
    Mohamad Qadri, George Kantor
    http://arxiv.org/abs/2107.04178v1

    • [cs.SD]EasyCom: An Augmented Reality Dataset to Support Algorithms for Easy Communication in Noisy Environments
    Jacob Donley, Vladimir Tourbabin, Jung-Suk Lee, Mark Broyles, Hao Jiang, Jie Shen, Maja Pantic, Vamsi Krishna Ithapu, Ravish Mehra
    http://arxiv.org/abs/2107.04174v1

    • [cs.SD]Improved Breath Phase and Continuous Adventitious Sound Detection in Lung and Tracheal Sound Using Mixed Set Training and Domain Adaptation
    Fu-Shun Hsu, Shang-Ran Huang, Chang-Fu Su, Chien-Wen Huang, Yuan-Ren Cheng, Chun-Chieh Chen, Chun-Yu Wu, Chung-Wei Chen, Yen-Chun Lai, Tang-Wei Cheng, Nian-Jhen Lin, Wan-Ling Tsai, Ching-Shiang Lu, Chuan Chen, Feipei Lai
    http://arxiv.org/abs/2107.04229v1

    • [cs.SD]Multi-path Convolutional Neural Networks Efficiently Improve Feature Extraction in Continuous Adventitious Lung Sound Detection
    Fu-Shun Hsu, Shang-Ran Huang, Chien-Wen Huang, Chun-Chieh Chen, Yuan-Ren Cheng, Feipei Lai
    http://arxiv.org/abs/2107.04226v1

    • [cs.SI]Causal Inference for Influence Propagation — Identifiability of the Independent Cascade Model
    Shi Feng, Wei Chen
    http://arxiv.org/abs/2107.04224v1

    • [cs.SI]Using Network Analysis on Twitter Data to Identify Threats on Indonesian Digital Activism
    Adya Danaditya
    http://arxiv.org/abs/2107.04294v1

    • [eess.AS]Training a Deep Neural Network via Policy Gradients for Blind Source Separation in Polyphonic Music Recordings
    Sören Schulze, Johannes Leuschner, Emily J. King
    http://arxiv.org/abs/2107.04235v1

    • [eess.IV]3D RegNet: Deep Learning Model for COVID-19 Diagnosis on Chest CT Image
    Haibo Qi, Yuhan Wang, Xinyu Liu
    http://arxiv.org/abs/2107.04055v1

    • [eess.IV]A Deep Discontinuity-Preserving Image Registration Network
    Xiang Chen, Nishant Ravikumar, Yan Xia, Alejandro F Frangi
    http://arxiv.org/abs/2107.04440v1

    • [eess.IV]CASPIANET++: A Multidimensional Channel-Spatial Asymmetric Attention Network with Noisy Student Curriculum Learning Paradigm for Brain Tumor Segmentation
    Andrea Liew, Chun Cheng Lee, Boon Leong Lan, Maxine Tan
    http://arxiv.org/abs/2107.04099v1

    • [eess.IV]Comparison of 2D vs. 3D U-Net Organ Segmentation in abdominal 3D CT images
    Nico Zettler, Andre Mastmeyer
    http://arxiv.org/abs/2107.04062v1

    • [eess.IV]Deep Learning models for benign and malign Ocular Tumor Growth Estimation
    Mayank Goswami
    http://arxiv.org/abs/2107.04220v1

    • [eess.IV]Hepatocellular Carcinoma Segmentation fromDigital Subtraction Angiography Videos usingLearnable Temporal Difference
    Wenting Jiang, Yicheng Jiang, Lu Zhang, Changmiao Wang, Xiaoguang Han, Shuixing Zhang, Xiang Wan, Shuguang Cui
    http://arxiv.org/abs/2107.04306v1

    • [eess.IV]LIFE: A Generalizable Autodidactic Pipeline for 3D OCT-A Vessel Segmentation
    Dewei Hu, Can Cui, Hao Li, Kathleen E. Larson, Yuankai K. Tao, Ipek Oguz
    http://arxiv.org/abs/2107.04282v1

    • [eess.IV]Modality specific U-Net variants for biomedical image segmentation: A survey
    Narinder Singh Punn, Sonali Agarwal
    http://arxiv.org/abs/2107.04537v1

    • [eess.IV]Retinal OCT Denoising with Pseudo-Multimodal Fusion Network
    Dewei Hu, Joseph D. Malone, Yigit Atay, Yuankai K. Tao, Ipek Oguz
    http://arxiv.org/abs/2107.04288v1

    • [eess.SY]Bayesian Error-in-Variables Models for the Identification of Power Networks
    Jean-Sébastien Brouillon, Emanuele Fabbiani, Pulkit Nahata, Florian Dörfler, Giancarlo Ferrari-Trecate
    http://arxiv.org/abs/2107.04480v1

    • [math.AC]Staged tree models with toric structure
    Christiane Görgen, Aida Maraj, Lisa Nicklasson
    http://arxiv.org/abs/2107.04516v1

    • [math.OC]Block Alternating Bregman Majorization Minimization with Extrapolation
    Le Thi Khanh Hien, Duy Nhat Phan, Nicolas Gillis, Masoud Ahookhosh, Panagiotis Patrinos
    http://arxiv.org/abs/2107.04395v1

    • [math.OC]Deep Learning for Mean Field Games and Mean Field Control with Applications to Finance
    René Carmona, Mathieu Laurière
    http://arxiv.org/abs/2107.04568v1

    • [math.OC]Structured Hammerstein-Wiener Model Learning for Model Predictive Control
    Ryuta Moriyasu, Taro Ikeda, Sho Kawaguchi, Kenji Kashima
    http://arxiv.org/abs/2107.04247v1

    • [math.ST]Diagonal Nonlinear Transformations Preserve Structure in Covariance and Precision Matrices
    Rebecca E Morrison, Ricardo Baptista, Estelle L Basor
    http://arxiv.org/abs/2107.04136v1

    • [math.ST]Higher Order Imprecise Probabilities and Statistical Testing
    Justus Hibshman, Tim Weninger
    http://arxiv.org/abs/2107.04542v1

    • [math.ST]Statistical Estimation and Nonlinear Filtering in Environmental Pollution
    Qizhu Liang, Jie Xiong, Xingqiu Zhao
    http://arxiv.org/abs/2107.04592v1

    • [math.ST]Two Sample Test for Extrinsic Antimeans on Planar Kendall Shape Spaces with an Application to Medical Imaging
    Aaid Algahtani, Vic Patrangenaru
    http://arxiv.org/abs/2107.04230v1

    • [physics.data-an]Entropy, Information, and the Updating of Probabilities
    Ariel Caticha
    http://arxiv.org/abs/2107.04529v1

    • [physics.flu-dyn]Deep Learning for Reduced Order Modelling and Efficient Temporal Evolution of Fluid Simulations
    Pranshu Pant, Ruchit Doshi, Pranav Bahl, Amir Barati Farimani
    http://arxiv.org/abs/2107.04556v1

    • [physics.soc-ph]Quantifying the rise and fall of scientific fields
    Chakresh Singh, Emma Barme, Robert Ward, Liubov Tupikina, Marc Santolini
    http://arxiv.org/abs/2107.03749v2

    • [stat.AP]Coastal water quality prediction based on machine learning with feature interpretation and spatio-temporal analysis
    Luka Grbčić, Siniša Družeta, Goran Mauša, Tomislav Lipić, Darija Vukić Lušić, Marta Alvir, Ivana Lučin, Ante Sikirica, Davor Davidović, Vanja Travaš, Daniela Kalafatović, Kristina Pikelj, Hana Fajković, Toni Holjević, Lado Kranjčević
    http://arxiv.org/abs/2107.03230v2

    • [stat.AP]From Many to One: Consensus Inference in a MIP
    Noel Cressie, Michael Bertolacci, Andrew Zammit-Mangion
    http://arxiv.org/abs/2107.04208v1

    • [stat.AP]Prediction of butt rot volume in Norway spruce forest stands using harvester, remotely sensed and environmental data
    Janne Räty, Johannes Breidenbach, Marius Hauglin, Rasmus Astrup
    http://arxiv.org/abs/2107.04316v1

    • [stat.CO]Fast compression of MCMC output
    Nicolas Chopin, Gabriel Ducrocq
    http://arxiv.org/abs/2107.04552v1

    • [stat.ME]Hypothetical estimands in clinical trials: a unification of causal inference and missing data methods
    Camila Olarte Parra, Rhian M. Daniel, Jonathan W. Bartlett
    http://arxiv.org/abs/2107.04392v1

    • [stat.ME]Joint Modeling of Longitudinal and Survival Data with Censored Single-index Varying Coefficient Models
    Jizi Shangguan
    http://arxiv.org/abs/2107.04496v1

    • [stat.ME]Parsimonious Hidden Markov Models for Matrix-Variate Longitudinal Data
    Tomarchio Salvatore D., Punzo Antonio, Maruotti Antonello
    http://arxiv.org/abs/2107.04330v1

    • [stat.ML]Continual Learning in the Teacher-Student Setup: Impact of Task Similarity
    Sebastian Lee, Sebastian Goldt, Andrew Saxe
    http://arxiv.org/abs/2107.04384v1

    • [stat.ML]Generalization of the Change of Variables Formula with Applications to Residual Flows
    Niklas Koenen, Marvin N. Wright, Peter Maaß, Jens Behrmann
    http://arxiv.org/abs/2107.04346v1

    • [stat.ML]The Bayesian Learning Rule
    Mohammad Emtiyaz Khan, Håvard Rue
    http://arxiv.org/abs/2107.04562v1