cond-mat.stat-mech - 统计数学
cs.AI - 人工智能
cs.AR - 硬件体系结构
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.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.NI - 网络和互联网体系结构
cs.RO - 机器人学
cs.SD - 声音处理
cs.SE - 软件工程
cs.SI - 社交网络与信息网络
econ.EM - 计量经济学
eess.IV - 图像与视频处理
eess.SY - 系统和控制
math.NA - 数值分析
math.PR - 概率
math.ST - 统计理论
physics.ao-ph - 大气和海洋物理
physics.soc-ph - 物理学与社会
q-bio.NC - 神经元与认知
q-bio.PE - 人口与发展
quant-ph - 量子物理
stat.AP - 应用统计
stat.ME - 统计方法论
stat.ML - (统计)机器学习
• [cond-mat.stat-mech]Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks
• [cs.AI]Acting upon Imagination: when to trust imagined trajectories in model based reinforcement learning
• [cs.AI]Bayesian Model Averaging for Data Driven Decision Making when Causality is Partially Known
• [cs.AI]Neuro-Symbolic Artificial Intelligence Current Trends
• [cs.AI]Online POMDP Planning via Simplification
• [cs.AI]Probabilistic Loss and its Online Characterization for Simplified Decision Making Under Uncertainty
• [cs.AI]Representation in Dynamical Systems
• [cs.AR]SimNet: Computer Architecture Simulation using Machine Learning
• [cs.CL]!Qué maravilla! Multimodal Sarcasm Detection in Spanish: a Dataset and a Baseline
• [cs.CL]BertGCN: Transductive Text Classification by Combining GCN and BERT
• [cs.CL]Building a Question and Answer System for News Domain
• [cs.CL]Conversational Negation using Worldly Context in Compositional Distributional Semantics
• [cs.CL]Could you give me a hint? Generating inference graphs for defeasible reasoning
• [cs.CL]Discrete representations in neural models of spoken language
• [cs.CL]Encoding Explanatory Knowledge for Zero-shot Science Question Answering
• [cs.CL]Evaluating Gender Bias in Natural Language Inference
• [cs.CL]How Reliable are Model Diagnostics?
• [cs.CL]Improving Lexically Constrained Neural Machine Translation with Source-Conditioned Masked Span Prediction
• [cs.CL]Incorporating Commonsense Knowledge Graph in Pretrained Models for Social Commonsense Tasks
• [cs.CL]Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layouts
• [cs.CL]Mining Legacy Issues in Open Pit Mining sites: Innovation & Support of Renaturalization and Land Utilization
• [cs.CL]NLP for Climate Policy: Creating a Knowledge Platform for Holistic and Effective Climate Action
• [cs.CL]News Headline Grouping as a Challenging NLU Task
• [cs.CL]OCHADAI-KYODAI at SemEval-2021 Task 1: Enhancing ModelGeneralization and Robustness for Lexical Complexity Prediction
• [cs.CL]OutFlip: Generating Out-of-Domain Samples for Unknown Intent Detection with Natural Language Attack
• [cs.CL]Priberam Labs at the NTCIR-15 SHINRA2020-ML: Classification Task
• [cs.CL]Priberam at MESINESP Multi-label Classification of Medical Texts Task
• [cs.CL]Probabilistic modelling of rational communication with conditionals
• [cs.CL]Stacked Acoustic-and-Textual Encoding: Integrating the Pre-trained Models into Speech Translation Encoders
• [cs.CL]The Greedy and Recursive Search for Morphological Productivity
• [cs.CL]The Semantic Brand Score
• [cs.CL]The Summary Loop: Learning to Write Abstractive Summaries Without Examples
• [cs.CL]UIUC_BioNLP at SemEval-2021 Task 11: A Cascade of Neural Models for Structuring Scholarly NLP Contributions
• [cs.CL]Unsupervised Knowledge Graph Alignment by Probabilistic Reasoning and Semantic Embedding
• [cs.CL]What’s The Latest? A Question-driven News Chatbot
• [cs.CV]A Fast Deep Learning Network for Automatic Image Auto-Straightening
• [cs.CV]A Large-Scale Benchmark for Food Image Segmentation
• [cs.CV]A Novel Uncertainty-aware Collaborative Learning Method for Remote Sensing Image Classification Under Multi-Label Noise
• [cs.CV]AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition
• [cs.CV]Breaking Shortcut: Exploring Fully Convolutional Cycle-Consistency for Video Correspondence Learning
• [cs.CV]CT-Net: Complementary Transfering Network for Garment Transfer with Arbitrary Geometric Changes
• [cs.CV]Collaborative Regression of Expressive Bodies using Moderation
• [cs.CV]Deep Spiking Convolutional Neural Network for Single Object Localization Based On Deep Continuous Local Learning
• [cs.CV]Deep and Shallow Covariance Feature Quantization for 3D Facial Expression Recognition
• [cs.CV]Directional GAN: A Novel Conditioning Strategy for Generative Networks
• [cs.CV]FDAN: Flow-guided Deformable Alignment Network for Video Super-Resolution
• [cs.CV]Few-Shot Learning by Integrating Spatial and Frequency Representation
• [cs.CV]FlipReID: Closing the Gap between Training and Inference in Person Re-Identification
• [cs.CV]Image interpretation by iterative bottom-up top-down processing
• [cs.CV]Incremental Few-Shot Instance Segmentation
• [cs.CV]Is Gender “In-the-Wild” Inference Really a Solved Problem?
• [cs.CV]Label Geometry Aware Discriminator for Conditional Generative Networks
• [cs.CV]Learning to Generate Novel Scene Compositions from Single Images and Videos
• [cs.CV]MT: Multi-Perspective Feature Learning Network for Scene Text Detection
• [cs.CV]Object-Based Augmentation Improves Quality of Remote SensingSemantic Segmentation
• [cs.CV]One-shot Compositional Data Generation for Low Resource Handwritten Text Recognition
• [cs.CV]Operation-wise Attention Network for Tampering Localization Fusion
• [cs.CV]PoseContrast: Class-Agnostic Object Viewpoint Estimation in the Wild with Pose-Aware Contrastive Learning
• [cs.CV]ROSEFusion: Random Optimization for Online Dense Reconstruction under Fast Camera Motion
• [cs.CV]SauvolaNet: Learning Adaptive Sauvola Network for Degraded Document Binarization
• [cs.CV]Segmenter: Transformer for Semantic Segmentation
• [cs.CV]Structure Guided Lane Detection
• [cs.CV]TextOCR: Towards large-scale end-to-end reasoning for arbitrary-shaped scene text
• [cs.CV]The DEVIL is in the Details: A Diagnostic Evaluation Benchmark for Video Inpainting
• [cs.CV]Unsupervised Representation Learning from Pathology Images with Multi-directional Contrastive Predictive Coding
• [cs.CV]VL-NMS: Breaking Proposal Bottlenecks in Two-Stage Visual-Language Matching
• [cs.CV]Video Frame Interpolation via Structure-Motion based Iterative Fusion
• [cs.CV]When Does Contrastive Visual Representation Learning Work?
• [cs.CV]WildGait: Learning of Gait Representations from Raw Surveillance Streams
• [cs.CY]An Introduction to Algorithmic Fairness
• [cs.CY]Profiling the Cybercriminal: A Systematic Review of Research
• [cs.DB]Automating Data Science: Prospects and Challenges
• [cs.DC]A survey of size counting in population protocols
• [cs.DC]CoCoNet: Co-Optimizing Computation and Communication for Distributed Machine Learning
• [cs.DC]Distributed In-memory Data Management for Workflow Executions
• [cs.DS]Distributed Graph Coloring Made Easy
• [cs.DS]How to Design Robust Algorithms using Noisy Comparison Oracle
• [cs.DS]Locally Checkable Labelings with Small Messages
• [cs.HC]”Alexa, what do you do for fun?” Characterizing playful requests with virtual assistants
• [cs.HC]Electrotactile feedback for hand interactions:A systematic review, meta-analysis,and future directions
• [cs.HC]From Human-Computer Interaction to Human-AI Interaction: New Challenges and Opportunities for Enabling Human-Centered AI
• [cs.HC]Intelligent interactive technologies for mental health and well-being
• [cs.IR]Co-Factorization Model for Collaborative Filtering with Session-based Data
• [cs.IR]Fairness and Discrimination in Information Access Systems
• [cs.IR]Looking at CTR Prediction Again: Is Attention All You Need?
• [cs.IR]Multi-Field Models in Neural Recipe Ranking — An Early Exploratory Study
• [cs.IR]Thematic recommendations on knowledge graphs using multilayer networks
• [cs.IR]kMatrix: A Space Efficient Streaming Graph Summarization Technique
• [cs.IT]A Statistical Threshold for Adversarial Classification in Laplace Mechanisms
• [cs.IT]Bayesian variational regularization on the ball
• [cs.IT]Capacity Bounds and User Identification Costs in Rayleigh-Fading Many-Access Channel
• [cs.IT]Cyclically Equivariant Neural Decoders for Cyclic Codes
• [cs.IT]Global Optimization for IRS-Assisted Wireless Communications: from Physics and Electromagnetic Perspectives
• [cs.IT]Indoor positioning systems: Smart fusion of a variety of sensor readings
• [cs.IT]Multi-Access Coded Caching with Secure Delivery
• [cs.IT]On Compressed Sensing of Binary Signals for the Unsourced Random Access Channel
• [cs.IT]On Parameter Optimization and Reach Enhancement for the Improved Soft-Aided Staircase Decoder
• [cs.IT]Symmetric Private Information Retrieval with User-Side Common Randomness
• [cs.IT]Trimmed Minimum Error Entropy for Robust Online Regression
• [cs.IT]Unlimited Sampling from Theory to Practice: Fourier-Prony Recovery and Prototype ADC
• [cs.IT]Wireless Covert Communications Aided by Distributed Cooperative Jamming over Slow Fading Channels
• [cs.IT]XOR-Based Codes for Private Information Retrieval with Private Side Information
• [cs.LG]A new framework for experimental design using Bayesian Evidential Learning: the case of wellhead protection area
• [cs.LG]Accuracy-Privacy Trade-off in Deep Ensemble
• [cs.LG]Adversarial Reinforcement Learning in Dynamic Channel Access and Power Control
• [cs.LG]An Efficient Learning Framework For Federated XGBoost Using Secret Sharing And Distributed Optimization
• [cs.LG]An Empirical Experiment on Deep Learning Models for Predicting Traffic Data
• [cs.LG]An efficient projection neural network for -regularized logistic regression
• [cs.LG]Autoencoding Under Normalization Constraints
• [cs.LG]Automatic Classification of Games using Support Vector Machine
• [cs.LG]Comparing interpretability and explainability for feature selection
• [cs.LG]Convergence Analysis of Over-parameterized Deep Linear Networks, and the Principal Components Bias
• [cs.LG]Cross-Modal and Multimodal Data Analysis Based on Functional Mapping of Spectral Descriptors and Manifold Regularization
• [cs.LG]Diffusion Models Beat GANs on Image Synthesis
• [cs.LG]Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces
• [cs.LG]Early prediction of respiratory failure in the intensive care unit
• [cs.LG]Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization
• [cs.LG]Exploring the Similarity of Representations in Model-Agnostic Meta-Learning
• [cs.LG]Hermitian Symmetric Spaces for Graph Embeddings
• [cs.LG]High-Dimensional Experimental Design and Kernel Bandits
• [cs.LG]Homogeneous vector bundles and -equivariant convolutional neural networks
• [cs.LG]Interpretable performance analysis towards offline reinforcement learning: A dataset perspective
• [cs.LG]Learning Graphs from Smooth Signals under Moment Uncertainty
• [cs.LG]Learning Uncertainty with Artificial Neural Networks for Improved Remaining Time Prediction of Business Processes
• [cs.LG]LipBaB: Computing exact Lipschitz constant of ReLU networks
• [cs.LG]Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning
• [cs.LG]Multi-version Tensor Completion for Time-delayed Spatio-temporal Data
• [cs.LG]On risk-based active learning for structural health monitoring
• [cs.LG]On the reproducibility of fully convolutional neural networks for modeling time-space evolving physical systems
• [cs.LG]Return-based Scaling: Yet Another Normalisation Trick for Deep RL
• [cs.LG]Robust Learning of Fixed-Structure Bayesian Networks in Nearly-Linear Time
• [cs.LG]The FeatureCloud AI Store for Federated Learning in Biomedicine and Beyond
• [cs.LG]Winograd Algorithm for AdderNet
• [cs.NI]A Survey on Reinforcement Learning-Aided Caching in Mobile Edge Networks
• [cs.RO]A Resilient and Energy-Aware Task Allocation Framework for Heterogeneous Multi-Robot Systems
• [cs.RO]A Study on Simultaneous Use of a Robotic Walker and a Pneumatic Walking Assist Device Designed for PD Patients
• [cs.RO]Adaptive and Risk-Aware Target Tracking with Heterogeneous Robot Teams
• [cs.RO]Brief Industry Paper: Budget-based real-time Executor for Micro-ROS
• [cs.RO]Learning a Skill-sequence-dependent Policy for Long-horizon Manipulation Tasks
• [cs.RO]Rearrangement on Lattices with Swaps: Optimality Structures and Efficient Algorithms
• [cs.RO]Target-Following Double Deep Q-Networks for UAVs
• [cs.SD]A Statistical Model for Melody Reduction
• [cs.SD]Global Structure-Aware Drum Transcription Based on Self-Attention Mechanisms
• [cs.SE]An Appraisal Transition System for Event-driven Emotions in Agent-based Player Experience Testing
• [cs.SI]An Empirical Study of Compression-friendly Community Detection Methods
• [cs.SI]Forecasting election results by studying brand importance in online news
• [cs.SI]Using social network analysis to prevent money laundering
• [econ.EM]The Local Approach to Causal Inference under Network Interference
• [eess.IV]20-fold Accelerated 7T fMRI Using Referenceless Self-Supervised Deep Learning Reconstruction
• [eess.IV]AVA: Adversarial Vignetting Attack against Visual Recognition
• [eess.IV]Deep Snapshot HDR Reconstruction Based on the Polarization Camera
• [eess.IV]GANs for Medical Image Synthesis: An Empirical Study
• [eess.IV]Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation
• [eess.SY]Discrete-time Contraction-based Control of Nonlinear Systems with Parametric Uncertainties using Neural Networks
• [math.NA]Machine learning moment closure models for the radiative transfer equation I: directly learning a gradient based closure
• [math.PR]Distribution of the Scaled Condition Number of Single-spiked Complex Wishart Matrices
• [math.ST]Estimation of population size based on capture recapture designs and evaluation of the estimation reliability
• [math.ST]Trimmed extreme value estimators for censored heavy-tailed data
• [physics.ao-ph]Real-time Ionospheric Imaging of S4 Scintillation from Limited Data with Parallel Kalman Filters and Smoothness
• [physics.soc-ph]Capturing the diversity of multilingual societies
• [q-bio.NC]CCN GAC Workshop: Issues with learning in biological recurrent neural networks
• [q-bio.PE]EpiCovDA: a mechanistic COVID-19 forecasting model with data assimilation
• [quant-ph]Causal networks and freedom of choice in Bell’s theorem
• [quant-ph]Structural risk minimization for quantum linear classifiers
• [stat.AP]Bayesian Inverse Uncertainty Quantification of a MOOSE-based Melt Pool Model for Additive Manufacturing Using Experimental Data
• [stat.AP]Estimation of mask effectiveness perception for small domains using multiple data sources
• [stat.AP]Joint Fairness Model with Applications to Risk Predictions for Under-represented Populations
• [stat.AP]Path Analysis Of Covid-19 with the Influence of Air Pressure, Air Temperature, and Relative Humidity
• [stat.ME]A Langevinized Ensemble Kalman Filter for Large-Scale Static and Dynamic Learning
• [stat.ME]A better measure of relative prediction accuracy for model selection and model estimation
• [stat.ME]A local MCMC algorithm for variable selection with dimension-free mixing time
• [stat.ME]An Encoding Approach for Stable Change Point Detection
• [stat.ME]Autoregressive Optimal Transport Models
• [stat.ME]Gaussian graphical models with graph constraints for magnetic moment interaction in high entropy alloys
• [stat.ME]Generalized Autoregressive Moving Average Models with GARCH Errors
• [stat.ME]Modeling space-time trends and dependence in extreme precipitations of Burkina Faso by the approach of the Peaks-Over-Threshold
• [stat.ME]Modeling spatial extremes using normal mean-variance mixtures
• [stat.ME]Sample size planning for pilot studies
• [stat.ME]Synthetic Area Weighting for Measuring Public Opinion in Small Areas
• [stat.ML]Kernel Thinning
• [stat.ML]Look-Ahead Screening Rules for the Lasso
• [stat.ML]Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference
• [stat.ML]Surrogate assisted active subspace and active subspace assisted surrogate — A new paradigm for high dimensional structural reliability analysis
·····································
• [cond-mat.stat-mech]Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks
Dian Wu, Riccardo Rossi, Giuseppe Carleo
http://arxiv.org/abs/2105.05650v1
• [cs.AI]Acting upon Imagination: when to trust imagined trajectories in model based reinforcement learning
Adrian Remonda, Eduardo Veas, Granit Luzhnica
http://arxiv.org/abs/2105.05716v1
• [cs.AI]Bayesian Model Averaging for Data Driven Decision Making when Causality is Partially Known
Marios Papamichalis, Abhishek Ray, Ilias Bilionis, Karthik Kannan, Rajiv Krishnamurthy
http://arxiv.org/abs/2105.05395v1
• [cs.AI]Neuro-Symbolic Artificial Intelligence Current Trends
Md Kamruzzaman Sarker, Lu Zhou, Aaron Eberhart, Pascal Hitzler
http://arxiv.org/abs/2105.05330v1
• [cs.AI]Online POMDP Planning via Simplification
Ori Sztyglic, Vadim Indelman
http://arxiv.org/abs/2105.05296v1
• [cs.AI]Probabilistic Loss and its Online Characterization for Simplified Decision Making Under Uncertainty
Andrey Zhitnikov, Vadim Indelman
http://arxiv.org/abs/2105.05789v1
• [cs.AI]Representation in Dynamical Systems
Matthew Hutson
http://arxiv.org/abs/2105.05714v1
• [cs.AR]SimNet: Computer Architecture Simulation using Machine Learning
Lingda Li, Santosh Pandey, Thomas Flynn, Hang Liu, Noel Wheeler, Adolfy Hoisie
http://arxiv.org/abs/2105.05821v1
• [cs.CL]!Qué maravilla! Multimodal Sarcasm Detection in Spanish: a Dataset and a Baseline
Khalid Alnajjar, Mika Hämäläinen
http://arxiv.org/abs/2105.05542v1
• [cs.CL]BertGCN: Transductive Text Classification by Combining GCN and BERT
Yuxiao Lin, Yuxian Meng, Xiaofei Sun, Qinghong Han, Kun Kuang, Jiwei Li, Fei Wu
http://arxiv.org/abs/2105.05727v1
• [cs.CL]Building a Question and Answer System for News Domain
Sandipan Basu, Aravind Gaddala, Pooja Chetan, Garima Tiwari, Narayana Darapaneni, Sadwik Parvathaneni, Anwesh Reddy Paduri
http://arxiv.org/abs/2105.05744v1
• [cs.CL]Conversational Negation using Worldly Context in Compositional Distributional Semantics
Benjamin Rodatz, Razin A. Shaikh, Lia Yeh
http://arxiv.org/abs/2105.05748v1
• [cs.CL]Could you give me a hint? Generating inference graphs for defeasible reasoning
Aman Madaan, Dheeraj Rajagopal, Niket Tandon, Yiming Yang, Eduard Hovy
http://arxiv.org/abs/2105.05418v1
• [cs.CL]Discrete representations in neural models of spoken language
Bertrand Higy, Lieke Gelderloos, Afra Alishahi, Grzegorz Chrupała
http://arxiv.org/abs/2105.05582v1
• [cs.CL]Encoding Explanatory Knowledge for Zero-shot Science Question Answering
Zili Zhou, Marco Valentino, Donal Landers, Andre Freitas
http://arxiv.org/abs/2105.05737v1
• [cs.CL]Evaluating Gender Bias in Natural Language Inference
Shanya Sharma, Manan Dey, Koustuv Sinha
http://arxiv.org/abs/2105.05541v1
• [cs.CL]How Reliable are Model Diagnostics?
Vamsi Aribandi, Yi Tay, Donald Metzler
http://arxiv.org/abs/2105.05641v1
• [cs.CL]Improving Lexically Constrained Neural Machine Translation with Source-Conditioned Masked Span Prediction
Gyubok Lee, Seongjun Yang, Edward Choi
http://arxiv.org/abs/2105.05498v1
• [cs.CL]Incorporating Commonsense Knowledge Graph in Pretrained Models for Social Commonsense Tasks
Ting-Yun Chang, Yang Liu, Karthik Gopalakrishnan, Behnam Hedayatnia, Pei Zhou, Dilek Hakkani-Tur
http://arxiv.org/abs/2105.05457v1
• [cs.CL]Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layouts
Tomasz Stanisławek, Filip Graliński, Anna Wróblewska, Dawid Lipiński, Agnieszka Kaliska, Paulina Rosalska, Bartosz Topolski, Przemysław Biecek
http://arxiv.org/abs/2105.05796v1
• [cs.CL]Mining Legacy Issues in Open Pit Mining sites: Innovation & Support of Renaturalization and Land Utilization
Christopher Schröder, Kim Bürgl, Yves Annanias, Andreas Niekler, Lydia Müller, Daniel Wiegreffe, Christian Bender, Christoph Mengs, Gerik Scheuermann, Gerhard Heyer
http://arxiv.org/abs/2105.05557v1
• [cs.CL]NLP for Climate Policy: Creating a Knowledge Platform for Holistic and Effective Climate Action
Pradip Swarnakar, Ashutosh Modi
http://arxiv.org/abs/2105.05621v1
• [cs.CL]News Headline Grouping as a Challenging NLU Task
Philippe Laban, Lucas Bandarkar, Marti A. Hearst
http://arxiv.org/abs/2105.05391v1
• [cs.CL]OCHADAI-KYODAI at SemEval-2021 Task 1: Enhancing ModelGeneralization and Robustness for Lexical Complexity Prediction
Yuki Taya, Lis Kanashiro Pereira, Fei Cheng, Ichiro Kobayashi
http://arxiv.org/abs/2105.05535v1
• [cs.CL]OutFlip: Generating Out-of-Domain Samples for Unknown Intent Detection with Natural Language Attack
DongHyun Choi, Myeong Cheol Shin, EungGyun Kim, Dong Ryeol Shin
http://arxiv.org/abs/2105.05601v1
• [cs.CL]Priberam Labs at the NTCIR-15 SHINRA2020-ML: Classification Task
Ruben Cardoso, Afonso Mendes, Andre Lamurias
http://arxiv.org/abs/2105.05605v1
• [cs.CL]Priberam at MESINESP Multi-label Classification of Medical Texts Task
Ruben Cardoso, Zita Marinho, Afonso Mendes, Sebastião Miranda
http://arxiv.org/abs/2105.05614v1
• [cs.CL]Probabilistic modelling of rational communication with conditionals
Britta Grusdt, Daniel Lassiter, Michael Franke
http://arxiv.org/abs/2105.05502v1
• [cs.CL]Stacked Acoustic-and-Textual Encoding: Integrating the Pre-trained Models into Speech Translation Encoders
Chen Xu, Bojie Hu, Yanyang Li, Yuhao Zhang, shen huang, Qi Ju, Tong Xiao, Jingbo Zhu
http://arxiv.org/abs/2105.05752v1
• [cs.CL]The Greedy and Recursive Search for Morphological Productivity
Caleb Belth, Sarah Payne, Deniz Beser, Jordan Kodner, Charles Yang
http://arxiv.org/abs/2105.05790v1
• [cs.CL]The Semantic Brand Score
A Fronzetti Colladon
http://arxiv.org/abs/2105.05781v1
• [cs.CL]The Summary Loop: Learning to Write Abstractive Summaries Without Examples
Philippe Laban, Andrew Hsi, John Canny, Marti A. Hearst
http://arxiv.org/abs/2105.05361v1
• [cs.CL]UIUC_BioNLP at SemEval-2021 Task 11: A Cascade of Neural Models for Structuring Scholarly NLP Contributions
Haoyang Liu, M. Janina Sarol, Halil Kilicoglu
http://arxiv.org/abs/2105.05435v1
• [cs.CL]Unsupervised Knowledge Graph Alignment by Probabilistic Reasoning and Semantic Embedding
Zhiyuan Qi, Ziheng Zhang, Jiaoyan Chen, Xi Chen, Yuejia Xiang, Ningyu Zhang, Yefeng Zheng
http://arxiv.org/abs/2105.05596v1
• [cs.CL]What’s The Latest? A Question-driven News Chatbot
Philippe Laban, John Canny, Marti A. Hearst
http://arxiv.org/abs/2105.05392v1
• [cs.CV]A Fast Deep Learning Network for Automatic Image Auto-Straightening
Ionut Mironica, Andrei Zugravu
http://arxiv.org/abs/2105.05787v1
• [cs.CV]A Large-Scale Benchmark for Food Image Segmentation
Xiongwei Wu, Xin Fu, Ying Liu, Ee-Peng Lim, Steven C. H. Hoi, Qianru Sun
http://arxiv.org/abs/2105.05409v1
• [cs.CV]A Novel Uncertainty-aware Collaborative Learning Method for Remote Sensing Image Classification Under Multi-Label Noise
Ahmet Kerem Aksoy, Mahdyar Ravanbakhsh, Tristan Kreuziger, Begum Demir
http://arxiv.org/abs/2105.05496v1
• [cs.CV]AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition
Rameswar Panda, Chun-Fu Chen, Quanfu Fan, Ximeng Sun, Kate Saenko, Aude Oliva, Rogerio Feris
http://arxiv.org/abs/2105.05165v2
• [cs.CV]Breaking Shortcut: Exploring Fully Convolutional Cycle-Consistency for Video Correspondence Learning
Yansong Tang, Zhenyu Jiang, Zhenda Xie, Yue Cao, Zheng Zhang, Philip H. S. Torr, Han Hu
http://arxiv.org/abs/2105.05838v1
• [cs.CV]CT-Net: Complementary Transfering Network for Garment Transfer with Arbitrary Geometric Changes
Fan Yang, Guosheng Lin
http://arxiv.org/abs/2105.05497v1
• [cs.CV]Collaborative Regression of Expressive Bodies using Moderation
Yao Feng, Vasileios Choutas, Timo Bolkart, Dimitrios Tzionas, Michael J. Black
http://arxiv.org/abs/2105.05301v1
• [cs.CV]Deep Spiking Convolutional Neural Network for Single Object Localization Based On Deep Continuous Local Learning
Sami Barchid, José Mennesson, Chaabane Djéraba
http://arxiv.org/abs/2105.05609v1
• [cs.CV]Deep and Shallow Covariance Feature Quantization for 3D Facial Expression Recognition
Walid Hariri, Nadir Farah, Dinesh Kumar Vishwakarma
http://arxiv.org/abs/2105.05708v1
• [cs.CV]Directional GAN: A Novel Conditioning Strategy for Generative Networks
Shradha Agrawal, Shankar Venkitachalam, Dhanya Raghu, Deepak Pai
http://arxiv.org/abs/2105.05712v1
• [cs.CV]FDAN: Flow-guided Deformable Alignment Network for Video Super-Resolution
Jiayi Lin, Yan Huang, Liang Wang
http://arxiv.org/abs/2105.05640v1
• [cs.CV]Few-Shot Learning by Integrating Spatial and Frequency Representation
Xiangyu Chen, Guanghui Wang
http://arxiv.org/abs/2105.05348v1
• [cs.CV]FlipReID: Closing the Gap between Training and Inference in Person Re-Identification
Xingyang Ni, Esa Rahtu
http://arxiv.org/abs/2105.05639v1
• [cs.CV]Image interpretation by iterative bottom-up top-down processing
Shimon Ullman, Liav Assif, Alona Strugatski, Ben-Zion Vatashsky, Hila Levy, Aviv Netanyahu, Adam Yaari
http://arxiv.org/abs/2105.05592v1
• [cs.CV]Incremental Few-Shot Instance Segmentation
Dan Andrei Ganea, Bas Boom, Ronald Poppe
http://arxiv.org/abs/2105.05312v1
• [cs.CV]Is Gender “In-the-Wild” Inference Really a Solved Problem?
Tiago Roxo, Hugo Proença
http://arxiv.org/abs/2105.05794v1
• [cs.CV]Label Geometry Aware Discriminator for Conditional Generative Networks
Suman Sapkota, Bidur Khanal, Binod Bhattarai, Bishesh Khanal, Tae-Kyun Kim
http://arxiv.org/abs/2105.05501v1
• [cs.CV]Learning to Generate Novel Scene Compositions from Single Images and Videos
Vadim Sushko, Juergen Gall, Anna Khoreva
http://arxiv.org/abs/2105.05847v1
• [cs.CV]MT: Multi-Perspective Feature Learning Network for Scene Text Detection
Chuang Yang, Mulin Chen, Yuan Yuan, Qi Wang
http://arxiv.org/abs/2105.05455v1
• [cs.CV]Object-Based Augmentation Improves Quality of Remote SensingSemantic Segmentation
Svetlana Illarionova, Sergey Nesteruk, Dmitrii Shadrin, Vladimir Ignatiev, Mariia Pukalchik, Ivan Oseledets
http://arxiv.org/abs/2105.05516v1
• [cs.CV]One-shot Compositional Data Generation for Low Resource Handwritten Text Recognition
Mohamed Ali Souibgui, Ali Furkan Biten, Sounak Dey, Alicia Fornés, Yousri Kessentini, Lluis Gomez, Dimosthenis Karatzas, Josep Lladós
http://arxiv.org/abs/2105.05300v1
• [cs.CV]Operation-wise Attention Network for Tampering Localization Fusion
Polychronis Charitidis, Giorgos Kordopatis-Zilos, Symeon Papadopoulos, Ioannis Kompatsiaris
http://arxiv.org/abs/2105.05515v1
• [cs.CV]PoseContrast: Class-Agnostic Object Viewpoint Estimation in the Wild with Pose-Aware Contrastive Learning
Yang Xiao, Yuming Du, Renaud Marlet
http://arxiv.org/abs/2105.05643v1
• [cs.CV]ROSEFusion: Random Optimization for Online Dense Reconstruction under Fast Camera Motion
Jiazhao Zhang, Chenyang Zhu, Lintao Zheng, Kai Xu
http://arxiv.org/abs/2105.05600v1
• [cs.CV]SauvolaNet: Learning Adaptive Sauvola Network for Degraded Document Binarization
Deng Li, Yue Wu, Yicong Zhou
http://arxiv.org/abs/2105.05521v1
• [cs.CV]Segmenter: Transformer for Semantic Segmentation
Robin Strudel, Ricardo Garcia, Ivan Laptev, Cordelia Schmid
http://arxiv.org/abs/2105.05633v1
• [cs.CV]Structure Guided Lane Detection
Jinming Su, Chao Chen, Ke Zhang, Junfeng Luo, Xiaoming Wei, Xiaolin Wei
http://arxiv.org/abs/2105.05403v1
• [cs.CV]TextOCR: Towards large-scale end-to-end reasoning for arbitrary-shaped scene text
Amanpreet Singh, Guan Pang, Mandy Toh, Jing Huang, Wojciech Galuba, Tal Hassner
http://arxiv.org/abs/2105.05486v1
• [cs.CV]The DEVIL is in the Details: A Diagnostic Evaluation Benchmark for Video Inpainting
Ryan Szeto, Jason J. Corso
http://arxiv.org/abs/2105.05332v1
• [cs.CV]Unsupervised Representation Learning from Pathology Images with Multi-directional Contrastive Predictive Coding
Jacob Carse, Frank Carey, Stephen McKenna
http://arxiv.org/abs/2105.05345v1
• [cs.CV]VL-NMS: Breaking Proposal Bottlenecks in Two-Stage Visual-Language Matching
Wenbo Ma, Long Chen, Hanwang Zhang, Jian Shao, Yueting Zhuang, Jun Xiao
http://arxiv.org/abs/2105.05636v1
• [cs.CV]Video Frame Interpolation via Structure-Motion based Iterative Fusion
Xi Li, Meng Cao, Yingying Tang, Scott Johnston, Zhendong Hong, Huimin Ma, Jiulong Shan
http://arxiv.org/abs/2105.05353v1
• [cs.CV]When Does Contrastive Visual Representation Learning Work?
Elijah Cole, Xuan Yang, Kimberly Wilber, Oisin Mac Aodha, Serge Belongie
http://arxiv.org/abs/2105.05837v1
• [cs.CV]WildGait: Learning of Gait Representations from Raw Surveillance Streams
Adrian Cosma, Emilian Radoi
http://arxiv.org/abs/2105.05528v1
• [cs.CY]An Introduction to Algorithmic Fairness
Hilde J. P. Weerts
http://arxiv.org/abs/2105.05595v1
• [cs.CY]Profiling the Cybercriminal: A Systematic Review of Research
Maria Bada, Jason R. C. Nurse
http://arxiv.org/abs/2105.02930v2
• [cs.DB]Automating Data Science: Prospects and Challenges
Tijl De Bie, Luc De Raedt, José Hernández-Orallo, Holger H. Hoos, Padhraic Smyth, Christopher K. I. Williams
http://arxiv.org/abs/2105.05699v1
• [cs.DC]A survey of size counting in population protocols
David Doty, Mahsa Eftekhari
http://arxiv.org/abs/2105.05408v1
• [cs.DC]CoCoNet: Co-Optimizing Computation and Communication for Distributed Machine Learning
Abhinav Jangda, Jun Huang, Guodong Liu, Amir Hossein Nodehi Sabet, Madanlal Musuvathi, Olli Sarikivi, Todd Mytkowicz, Youshan Miao
http://arxiv.org/abs/2105.05720v1
• [cs.DC]Distributed In-memory Data Management for Workflow Executions
Renan Souza, Vítor Silva, Alexandre A. B. Lima, Daniel de Oliveira, Patrick Valduriez, Marta Mattoso
http://arxiv.org/abs/2105.04720v2
• [cs.DS]Distributed Graph Coloring Made Easy
Yannic Maus
http://arxiv.org/abs/2105.05575v1
• [cs.DS]How to Design Robust Algorithms using Noisy Comparison Oracle
Raghavendra Addanki, Sainyam Galhotra, Barna Saha
http://arxiv.org/abs/2105.05782v1
• [cs.DS]Locally Checkable Labelings with Small Messages
Alkida Balliu, Keren Censor-Hillel, Yannic Maus, Dennis Olivetti, Jukka Suomela
http://arxiv.org/abs/2105.05574v1
• [cs.HC]“Alexa, what do you do for fun?” Characterizing playful requests with virtual assistants
Chen Shani, Alexander Libov, Sofia Tolmach, Liane Lewin-Eytan, Yoelle Maarek, Dafna Shahaf
http://arxiv.org/abs/2105.05571v1
• [cs.HC]Electrotactile feedback for hand interactions:A systematic review, meta-analysis,and future directions
Panagiotis Kourtesis, Ferran Argelaguet, Sebastian Vizcay, Maud Marchal, Claudio Pacchierotti
http://arxiv.org/abs/2105.05343v1
• [cs.HC]From Human-Computer Interaction to Human-AI Interaction: New Challenges and Opportunities for Enabling Human-Centered AI
Wei Xu, Marvin J. Dainoff, Liezhong Ge, Zaifeng Gao
http://arxiv.org/abs/2105.05424v1
• [cs.HC]Intelligent interactive technologies for mental health and well-being
Mladjan Jovanovic, Aleksandar Jevremovic, Milica Pejovic-Milovancevic
http://arxiv.org/abs/2105.05306v1
• [cs.IR]Co-Factorization Model for Collaborative Filtering with Session-based Data
Binh Nguyen, Atsuhiro Takasu
http://arxiv.org/abs/2105.05389v1
• [cs.IR]Fairness and Discrimination in Information Access Systems
Michael D. Ekstrand, Anubrata Das, Robin Burke, Fernando Diaz
http://arxiv.org/abs/2105.05779v1
• [cs.IR]Looking at CTR Prediction Again: Is Attention All You Need?
Yuan Cheng, Yanbo Xue
http://arxiv.org/abs/2105.05563v1
• [cs.IR]Multi-Field Models in Neural Recipe Ranking — An Early Exploratory Study
Kentaro Takiguchi, Niall Twomey, Luis M Vaquero
http://arxiv.org/abs/2105.05710v1
• [cs.IR]Thematic recommendations on knowledge graphs using multilayer networks
Mariano Beguerisse-Díaz, Dimitrios Korkinof, Till Hoffmann
http://arxiv.org/abs/2105.05733v1
• [cs.IR]kMatrix: A Space Efficient Streaming Graph Summarization Technique
Oshan Mudannayake, Nalin Ranasinghe
http://arxiv.org/abs/2105.05503v1
• [cs.IT]A Statistical Threshold for Adversarial Classification in Laplace Mechanisms
Ayşe Ünsal, Melek Önen
http://arxiv.org/abs/2105.05610v1
• [cs.IT]Bayesian variational regularization on the ball
Matthew A. Price, Jason D. McEwen
http://arxiv.org/abs/2105.05518v1
• [cs.IT]Capacity Bounds and User Identification Costs in Rayleigh-Fading Many-Access Channel
Jyotish Robin, Elza Erkip
http://arxiv.org/abs/2105.05603v1
• [cs.IT]Cyclically Equivariant Neural Decoders for Cyclic Codes
Xiangyu Chen, Min Ye
http://arxiv.org/abs/2105.05540v1
• [cs.IT]Global Optimization for IRS-Assisted Wireless Communications: from Physics and Electromagnetic Perspectives
Xin Cheng, Yan Lin, Weiping Shi, Jiayu Li, Cunhua Pan, Feng Shu, Jiangzhou Wang
http://arxiv.org/abs/2105.05618v1
• [cs.IT]Indoor positioning systems: Smart fusion of a variety of sensor readings
M. Arnold, F. Schaich
http://arxiv.org/abs/2105.05438v1
• [cs.IT]Multi-Access Coded Caching with Secure Delivery
K. K. Krishnan Namboodiri, B. Sundar Rajan
http://arxiv.org/abs/2105.05611v1
• [cs.IT]On Compressed Sensing of Binary Signals for the Unsourced Random Access Channel
Elad Romanov, Or Ordentlich
http://arxiv.org/abs/2105.05350v1
• [cs.IT]On Parameter Optimization and Reach Enhancement for the Improved Soft-Aided Staircase Decoder
Yi Lei, Bin Chen, Gabriele Liga, Alex Alvarado
http://arxiv.org/abs/2105.05419v1
• [cs.IT]Symmetric Private Information Retrieval with User-Side Common Randomness
Zhusheng Wang, Sennur Ulukus
http://arxiv.org/abs/2105.05807v1
• [cs.IT]Trimmed Minimum Error Entropy for Robust Online Regression
Sajjad Bahrami, Ertem Tuncel
http://arxiv.org/abs/2105.05321v1
• [cs.IT]Unlimited Sampling from Theory to Practice: Fourier-Prony Recovery and Prototype ADC
Ayush Bhandari, Felix Krahmer, Thomas Poskitt
http://arxiv.org/abs/2105.05818v1
• [cs.IT]Wireless Covert Communications Aided by Distributed Cooperative Jamming over Slow Fading Channels
Tong-Xing Zheng, Ziteng Yang, Chao Wang, Zan Li, Jinhong Yuan, Xiaohong Guan
http://arxiv.org/abs/2105.05485v1
• [cs.IT]XOR-Based Codes for Private Information Retrieval with Private Side Information
Murali Krishnan K. H., J. Harshan
http://arxiv.org/abs/2105.05788v1
• [cs.LG]A new framework for experimental design using Bayesian Evidential Learning: the case of wellhead protection area
Robin Thibaut, Eric Laloy, Thomas Hermans
http://arxiv.org/abs/2105.05539v1
• [cs.LG]Accuracy-Privacy Trade-off in Deep Ensemble
Shahbaz Rezaei, Zubair Shafiq, Xin Liu
http://arxiv.org/abs/2105.05381v1
• [cs.LG]Adversarial Reinforcement Learning in Dynamic Channel Access and Power Control
Feng Wang, M. Cenk Gursoy, Senem Velipasalar
http://arxiv.org/abs/2105.05817v1
• [cs.LG]An Efficient Learning Framework For Federated XGBoost Using Secret Sharing And Distributed Optimization
Lunchen Xie, Jiaqi Liu, Songtao Lu, Tsung-hui Chang, Qingjiang Shi
http://arxiv.org/abs/2105.05717v1
• [cs.LG]An Empirical Experiment on Deep Learning Models for Predicting Traffic Data
Hyunwook Lee, Cheonbok Park, Seungmin Jin, Hyeshin Chu, Jaegul Choo, Sungahn Ko
http://arxiv.org/abs/2105.05504v1
• [cs.LG]An efficient projection neural network for -regularized logistic regression
Majid Mohammadi, Amir Ahooye Atashin, Damian A. Tamburri
http://arxiv.org/abs/2105.05449v1
• [cs.LG]Autoencoding Under Normalization Constraints
Sangwoong Yoon, Yung-Kyun Noh, Frank Chongwoo Park
http://arxiv.org/abs/2105.05735v1
• [cs.LG]Automatic Classification of Games using Support Vector Machine
Ismo Horppu, Antti Nikander, Elif Buyukcan, Jere Mäkiniemi, Amin Sorkhei, Frederick Ayala-Gómez
http://arxiv.org/abs/2105.05674v1
• [cs.LG]Comparing interpretability and explainability for feature selection
Jack Dunn, Luca Mingardi, Ying Daisy Zhuo
http://arxiv.org/abs/2105.05328v1
• [cs.LG]Convergence Analysis of Over-parameterized Deep Linear Networks, and the Principal Components Bias
Guy Hacohen, Daphna Weinshall
http://arxiv.org/abs/2105.05553v1
• [cs.LG]Cross-Modal and Multimodal Data Analysis Based on Functional Mapping of Spectral Descriptors and Manifold Regularization
Maysam Behmanesh, Peyman Adibi, Jocelyn Chanussot, Sayyed Mohammad Saeed Ehsani
http://arxiv.org/abs/2105.05631v1
• [cs.LG]Diffusion Models Beat GANs on Image Synthesis
Prafulla Dhariwal, Alex Nichol
http://arxiv.org/abs/2105.05233v2
• [cs.LG]Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces
Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank Reddi, Sanjiv Kumar
http://arxiv.org/abs/2105.05736v1
• [cs.LG]Early prediction of respiratory failure in the intensive care unit
Matthias Hüser, Martin Faltys, Xinrui Lyu, Chris Barber, Stephanie L. Hyland, Tobias M. Merz, Gunnar Rätsch
http://arxiv.org/abs/2105.05728v1
• [cs.LG]Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization
Damien Teney, Ehsan Abbasnejad, Simon Lucey, Anton van den Hengel
http://arxiv.org/abs/2105.05612v1
• [cs.LG]Exploring the Similarity of Representations in Model-Agnostic Meta-Learning
Thomas Goerttler, Klaus Obermayer
http://arxiv.org/abs/2105.05757v1
• [cs.LG]Hermitian Symmetric Spaces for Graph Embeddings
Federico López, Beatrice Pozzetti, Steve Trettel, Anna Wienhard
http://arxiv.org/abs/2105.05275v1
• [cs.LG]High-Dimensional Experimental Design and Kernel Bandits
Romain Camilleri, Julian Katz-Samuels, Kevin Jamieson
http://arxiv.org/abs/2105.05806v1
• [cs.LG]Homogeneous vector bundles and -equivariant convolutional neural networks
Jimmy Aronsson
http://arxiv.org/abs/2105.05400v1
• [cs.LG]Interpretable performance analysis towards offline reinforcement learning: A dataset perspective
Chenyang Xi, Bo Tang, Jiajun Shen, Xinfu Liu, Feiyu Xiong, Xueying Li
http://arxiv.org/abs/2105.05473v1
• [cs.LG]Learning Graphs from Smooth Signals under Moment Uncertainty
Xiaolu Wang, Yuen-Man Pun, Anthony Man-Cho So
http://arxiv.org/abs/2105.05458v1
• [cs.LG]Learning Uncertainty with Artificial Neural Networks for Improved Remaining Time Prediction of Business Processes
Hans Weytjens, Jochen De Weerdt
http://arxiv.org/abs/2105.05559v1
• [cs.LG]LipBaB: Computing exact Lipschitz constant of ReLU networks
Aritra Bhowmick, Meenakshi D’Souza, G. Srinivasa Raghavan
http://arxiv.org/abs/2105.05495v1
• [cs.LG]Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning
Ming Jin, Yizhen Zheng, Yuan-Fang Li, Chen Gong, Chuan Zhou, Shirui Pan
http://arxiv.org/abs/2105.05682v1
• [cs.LG]Multi-version Tensor Completion for Time-delayed Spatio-temporal Data
Cheng Qian, Nikos Kargas, Cao Xiao, Lucas Glass, Nicholas Sidiropoulos, Jimeng Sun
http://arxiv.org/abs/2105.05326v1
• [cs.LG]On risk-based active learning for structural health monitoring
A. J. Hughes, L. A. Bull, P. Gardner, R. J. Barthorpe, N. Dervilis, K. Worden
http://arxiv.org/abs/2105.05622v1
• [cs.LG]On the reproducibility of fully convolutional neural networks for modeling time-space evolving physical systems
Wagner Gonçalves Pinto, Antonio Alguacil, Michaël Bauerheim
http://arxiv.org/abs/2105.05482v1
• [cs.LG]Return-based Scaling: Yet Another Normalisation Trick for Deep RL
Tom Schaul, Georg Ostrovski, Iurii Kemaev, Diana Borsa
http://arxiv.org/abs/2105.05347v1
• [cs.LG]Robust Learning of Fixed-Structure Bayesian Networks in Nearly-Linear Time
Yu Cheng, Honghao Lin
http://arxiv.org/abs/2105.05555v1
• [cs.LG]The FeatureCloud AI Store for Federated Learning in Biomedicine and Beyond
Julian Matschinske, Julian Späth, Reza Nasirigerdeh, Reihaneh Torkzadehmahani, Anne Hartebrodt, Balázs Orbán, Sándor Fejér, Olga Zolotareva, Mohammad Bakhtiari, Béla Bihari, Marcus Bloice, Nina C Donner, Walid Fdhila, Tobias Frisch, Anne-Christin Hauschild, Dominik Heider, Andreas Holzinger, Walter Hötzendorfer, Jan Hospes, Tim Kacprowski, Markus Kastelitz, Markus List, Rudolf Mayer, Mónika Moga, Heimo Müller, Anastasia Pustozerova, Richard Röttger, Anna Saranti, Harald HHW Schmidt, Christof Tschohl, Nina K Wenke, Jan Baumbach
http://arxiv.org/abs/2105.05734v1
• [cs.LG]Winograd Algorithm for AdderNet
Wenshuo Li, Hanting Chen, Mingqiang Huang, Xinghao Chen, Chunjing Xu, Yunhe Wang
http://arxiv.org/abs/2105.05530v1
• [cs.NI]A Survey on Reinforcement Learning-Aided Caching in Mobile Edge Networks
Nikolaos Nomikos, Spyros Zoupanos, Themistoklis Charalambous, Ioannis Krikids, Athina Petropulu
http://arxiv.org/abs/2105.05564v1
• [cs.RO]A Resilient and Energy-Aware Task Allocation Framework for Heterogeneous Multi-Robot Systems
Gennaro Notomista, Siddharth Mayya, Yousef Emam, Christopher Kroninger, Addison Bohannon, Seth Hutchinson, Magnus Egerstedt
http://arxiv.org/abs/2105.05586v1
• [cs.RO]A Study on Simultaneous Use of a Robotic Walker and a Pneumatic Walking Assist Device Designed for PD Patients
Abdul Ali, Rikuo Kawamoto, Tomohiro Shibata
http://arxiv.org/abs/2105.04763v2
• [cs.RO]Adaptive and Risk-Aware Target Tracking with Heterogeneous Robot Teams
Siddharth Mayya, Ragesh K. Ramachandran, Lifeng Zhou, Gaurav S. Sukhatme, Vijay Kumar
http://arxiv.org/abs/2105.03813v1
• [cs.RO]Brief Industry Paper: Budget-based real-time Executor for Micro-ROS
Jan Staschulat, Ralph Lange, Dakshina Narahari Dasari
http://arxiv.org/abs/2105.05590v1
• [cs.RO]Learning a Skill-sequence-dependent Policy for Long-horizon Manipulation Tasks
Zhihao Li, Zhenglong Sun, Jionglong SU, Jiaming Zhang
http://arxiv.org/abs/2105.05484v1
• [cs.RO]Rearrangement on Lattices with Swaps: Optimality Structures and Efficient Algorithms
Jingjin Yu
http://arxiv.org/abs/2105.05366v1
• [cs.RO]Target-Following Double Deep Q-Networks for UAVs
Sarthak Bhagat, P. B. Sujit
http://arxiv.org/abs/2105.05464v1
• [cs.SD]A Statistical Model for Melody Reduction
Tianxue Hu, Claire Arthur
http://arxiv.org/abs/2105.05385v1
• [cs.SD]Global Structure-Aware Drum Transcription Based on Self-Attention Mechanisms
Ryoto Ishizuka, Ryo Nishikimi, Kazuyoshi Yoshii
http://arxiv.org/abs/2105.05791v1
• [cs.SE]An Appraisal Transition System for Event-driven Emotions in Agent-based Player Experience Testing
Saba Gholizadeh Ansari, I. S. W. B. Prasetya, Mehdi Dastani, Frank Dignum, Gabriele Keller
http://arxiv.org/abs/2105.05589v1
• [cs.SI]An Empirical Study of Compression-friendly Community Detection Methods
Muhammad Irfan Yousuf, Izza Anwer, Muhammad Abid
http://arxiv.org/abs/2105.05273v1
• [cs.SI]Forecasting election results by studying brand importance in online news
A. Fronzetti Colladon
http://arxiv.org/abs/2105.05762v1
• [cs.SI]Using social network analysis to prevent money laundering
A. Fronzetti Colladon, E. Remondi
http://arxiv.org/abs/2105.05793v1
• [econ.EM]The Local Approach to Causal Inference under Network Interference
Eric Auerbach, Max Tabord-Meehan
http://arxiv.org/abs/2105.03810v2
• [eess.IV]20-fold Accelerated 7T fMRI Using Referenceless Self-Supervised Deep Learning Reconstruction
Omer Burak Demirel, Burhaneddin Yaman, Logan Dowdle, Steen Moeller, Luca Vizioli, Essa Yacoub, John Strupp, Cheryl A. Olman, Kâmil Uğurbil, Mehmet Akçakaya
http://arxiv.org/abs/2105.05827v1
• [eess.IV]AVA: Adversarial Vignetting Attack against Visual Recognition
Binyu Tian, Felix Juefei-Xu, Qing Guo, Xiaofei Xie, Xiaohong Li, Yang Liu
http://arxiv.org/abs/2105.05558v1
• [eess.IV]Deep Snapshot HDR Reconstruction Based on the Polarization Camera
Juiwen Ting, Xuesong Wu, Kangkang Hu, Hong Zhang
http://arxiv.org/abs/2105.05824v1
• [eess.IV]GANs for Medical Image Synthesis: An Empirical Study
Youssef Skandarani, Pierre-Marc Jodoin, Alain Lalande
http://arxiv.org/abs/2105.05318v1
• [eess.IV]Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation
Hu Cao, Yueyue Wang, Joy Chen, Dongsheng Jiang, Xiaopeng Zhang, Qi Tian, Manning Wang
http://arxiv.org/abs/2105.05537v1
• [eess.SY]Discrete-time Contraction-based Control of Nonlinear Systems with Parametric Uncertainties using Neural Networks
Lai Wei, Ryan McCloy, Jie Bao
http://arxiv.org/abs/2105.05432v1
• [math.NA]Machine learning moment closure models for the radiative transfer equation I: directly learning a gradient based closure
Juntao Huang, Yingda Cheng, Andrew J. Christlieb, Luke F. Roberts
http://arxiv.org/abs/2105.05690v1
• [math.PR]Distribution of the Scaled Condition Number of Single-spiked Complex Wishart Matrices
Pasan Dissanayake, Prathapasinghe Dharmawansa, Yang Chen
http://arxiv.org/abs/2105.05307v1
• [math.ST]Estimation of population size based on capture recapture designs and evaluation of the estimation reliability
Yue You, Mark van der Laan, Philip Collender, Qu Cheng, Alan Hubbard, Nicholas P Jewell, Zhiyue Tom Hu, Robin Mejia, Justin Remais
http://arxiv.org/abs/2105.05373v1
• [math.ST]Trimmed extreme value estimators for censored heavy-tailed data
Martin Bladt, Hansjoerg Albrecher, Jan Beirlant
http://arxiv.org/abs/2105.05523v1
• [physics.ao-ph]Real-time Ionospheric Imaging of S4 Scintillation from Limited Data with Parallel Kalman Filters and Smoothness
Alexandra Koulouri
http://arxiv.org/abs/2105.05360v1
• [physics.soc-ph]Capturing the diversity of multilingual societies
Thomas Louf, David Sanchez, Jose J. Ramasco
http://arxiv.org/abs/2105.02570v2
• [q-bio.NC]CCN GAC Workshop: Issues with learning in biological recurrent neural networks
Luke Y. Prince, Ellen Boven, Roy Henha Eyono, Arna Ghosh, Joe Pemberton, Franz Scherr, Claudia Clopath, Rui Ponte Costa, Wolfgang Maass, Blake A. Richards, Cristina Savin, Katharina Anna Wilmes
http://arxiv.org/abs/2105.05382v1
• [q-bio.PE]EpiCovDA: a mechanistic COVID-19 forecasting model with data assimilation
Hannah R. Biegel, Joceline Lega
http://arxiv.org/abs/2105.05471v1
• [quant-ph]Causal networks and freedom of choice in Bell’s theorem
Rafael Chaves, George Moreno, Emanuele Polino, Davide Poderini, Iris Agresti, Alessia Suprano, Mariana R. Barros, Gonzalo Carvacho, Elie Wolfe, Askery Canabarro, Robert W. Spekkens, Fabio Sciarrino
http://arxiv.org/abs/2105.05721v1
• [quant-ph]Structural risk minimization for quantum linear classifiers
Casper Gyurik, Dyon van Vreumingen, Vedran Dunjko
http://arxiv.org/abs/2105.05566v1
• [stat.AP]Bayesian Inverse Uncertainty Quantification of a MOOSE-based Melt Pool Model for Additive Manufacturing Using Experimental Data
Ziyu Xie, Wen Jiang, Congjian Wang, Xu Wu
http://arxiv.org/abs/2105.05370v1
• [stat.AP]Estimation of mask effectiveness perception for small domains using multiple data sources
Aditi Sen, Partha Lahiri
http://arxiv.org/abs/2105.05290v1
• [stat.AP]Joint Fairness Model with Applications to Risk Predictions for Under-represented Populations
Hyungrok Do, Shinjini Nandi, Preston Putzel, Padhraic Smyth, Judy Zhong
http://arxiv.org/abs/2105.04648v2
• [stat.AP]Path Analysis Of Covid-19 with the Influence of Air Pressure, Air Temperature, and Relative Humidity
Marvin G. Pizon, Ronald R. Baldo, Ruthlyn N. Villarante, Jessica D. Balatero
http://arxiv.org/abs/2105.05451v1
• [stat.ME]A Langevinized Ensemble Kalman Filter for Large-Scale Static and Dynamic Learning
Peiyi Zhang, Qifan Song, Faming Liang
http://arxiv.org/abs/2105.05363v1
• [stat.ME]A better measure of relative prediction accuracy for model selection and model estimation
Chris Tofallis
http://arxiv.org/abs/2105.05249v1
• [stat.ME]A local MCMC algorithm for variable selection with dimension-free mixing time
Quan Zhou, Jun Yang, Dootika Vats, Gareth O. Roberts, Jeffrey S. Rosenthal
http://arxiv.org/abs/2105.05719v1
• [stat.ME]An Encoding Approach for Stable Change Point Detection
Xiaodong Wang, Fushing Hsieh
http://arxiv.org/abs/2105.05341v1
• [stat.ME]Autoregressive Optimal Transport Models
Changbo Zhu, Hans-Georg Müller
http://arxiv.org/abs/org/abs/2105.05439v1
• [stat.ME]Gaussian graphical models with graph constraints for magnetic moment interaction in high entropy alloys
Xinrui Liu, Yifeng Wu, Douglas L. Irving, Meng Li
http://arxiv.org/abs/2105.05280v1
• [stat.ME]Generalized Autoregressive Moving Average Models with GARCH Errors
Tingguo Zheng, Han Xiao, Rong Chen
http://arxiv.org/abs/2105.05532v1
• [stat.ME]Modeling space-time trends and dependence in extreme precipitations of Burkina Faso by the approach of the Peaks-Over-Threshold
Béwentaoré Sawadogo, Diakarya Barro
http://arxiv.org/abs/2105.05548v1
• [stat.ME]Modeling spatial extremes using normal mean-variance mixtures
Zhongwei Zhang, Raphaël Huser, Thomas Opitz, Jennifer L. Wadsworth
http://arxiv.org/abs/2105.05314v1
• [stat.ME]Sample size planning for pilot studies
Chi-Hong Tseng, Danielle Sim
http://arxiv.org/abs/2105.05483v1
• [stat.ME]Synthetic Area Weighting for Measuring Public Opinion in Small Areas
Shiro Kuriwaki, Soichiro Yamauchi
http://arxiv.org/abs/2105.05829v1
• [stat.ML]Kernel Thinning
Raaz Dwivedi, Lester Mackey
http://arxiv.org/abs/2105.05842v1
• [stat.ML]Look-Ahead Screening Rules for the Lasso
Johan Larsson
http://arxiv.org/abs/2105.05648v1
• [stat.ML]Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference
Shumao Zhang, Pengchuan Zhang, Thomas Y. Hou
http://arxiv.org/abs/2105.05489v1
• [stat.ML]Surrogate assisted active subspace and active subspace assisted surrogate — A new paradigm for high dimensional structural reliability analysis
Navaneeth N., Souvik Chakraborty
http://arxiv.org/abs/2105.04979v2
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