astro-ph.IM - 仪器仪表和天体物理学方法
cond-mat.mtrl-sci - 材料科学
cond-mat.stat-mech - 统计数学
cs.AI - 人工智能
cs.CL - 计算与语言
cs.CR - 加密与安全
cs.CV - 机器视觉与模式识别
cs.CY - 计算与社会
cs.DC - 分布式、并行与集群计算
cs.GR - 计算机图形学
cs.IR - 信息检索
cs.IT - 信息论
cs.LG - 自动学习
cs.MM - 多媒体
cs.NE - 神经与进化计算
cs.PF - 计算性能
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.GN - 一般经济学
eess.IV - 图像与视频处理
eess.SP - 信号处理
eess.SY - 系统和控制
math.OC - 优化与控制
math.ST - 统计理论
physics.geo-ph - 地球物理学
physics.soc-ph - 物理学与社会
q-bio.NC - 神经元与认知
q-bio.QM - 定量方法
q-fin.ST - 统计金融学
quant-ph - 量子物理
stat.AP - 应用统计
stat.CO - 统计计算
stat.ME - 统计方法论
stat.ML - (统计)机器学习
• [astro-ph.IM]Prediction of Apophis Asteroid Flyby Optimal Trajectories and Data Fusion of Earth-Apophis Mission Launch Windows using Deep Neural Networks
• [cond-mat.mtrl-sci]Understanding Fission Gas Bubble Distribution, Lanthanide Transportation, and Thermal Conductivity Degradation in Neutron-irradiated α-U Using Machine Learning
• [cond-mat.stat-mech]Variational Autoencoder Analysis of Ising Model Statistical Distributions and Phase Transitions
• [cs.AI]Agents for Automated User Experience Testing
• [cs.AI]AutoOED: Automated Optimal Experiment Design Platform
• [cs.AI]BlockGNN: Towards Efficient GNN Acceleration Using Block-Circulant Weight Matrices
• [cs.AI]Future is not One-dimensional: Graph Modeling based Complex Event Schema Induction for Event Prediction
• [cs.AI]Gradient Kernel Regression
• [cs.AI]Group Recommendation Techniques for Feature Modeling and Configuration
• [cs.AI]Level Generation for Angry Birds with Sequential VAE and Latent Variable Evolution
• [cs.AI]On the Computational Intelligibility of Boolean Classifiers
• [cs.AI]Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads
• [cs.AI]Two-stage training algorithm for AI robot soccer
• [cs.CL]A Replication Study of Dense Passage Retriever
• [cs.CL]Bridging the Gap Between Clean Data Training and Real-World Inference for Spoken Language Understanding
• [cs.CL]Deep Learning for Prominence Detection in Children’s Read Speech
• [cs.CL]Detoxifying Language Models Risks Marginalizing Minority Voices
• [cs.CL]DirectProbe: Studying Representations without Classifiers
• [cs.CL]Discourse Probing of Pretrained Language Models
• [cs.CL]Document-Level Event Argument Extraction by Conditional Generation
• [cs.CL]EXPLAINABOARD: An Explainable Leaderboard for NLP
• [cs.CL]Equivalence of Segmental and Neural Transducer Modeling: A Proof of Concept
• [cs.CL]Evaluating Saliency Methods for Neural Language Models
• [cs.CL]Experiments of ASR-based mispronunciation detection for children and adult English learners
• [cs.CL]Family of Origin and Family of Choice: Massively Parallel Lexiconized Iterative Pretraining for Severely Low Resource Machine Translation
• [cs.CL]Few-shot Intent Classification and Slot Filling with Retrieved Examples
• [cs.CL]Fighting the COVID-19 Infodemic with a Holistic BERT Ensemble
• [cs.CL]Finding Concept-specific Biases in Form—Meaning Associations
• [cs.CL]From partners to populations: A hierarchical Bayesian account of coordination and convention
• [cs.CL]GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity Recognition
• [cs.CL]Gender Bias in Machine Translation
• [cs.CL]Learning from Executions for Semantic Parsing
• [cs.CL]Learning to Synthesize Data for Semantic Parsing
• [cs.CL]Lessons on Parameter Sharing across Layers in Transformers
• [cs.CL]Mediators in Determining what Processing BERT Performs First
• [cs.CL]Modeling the dynamics of language change: logistic regression, Piotrowski’s law, and a handful of examples in Polish
• [cs.CL]Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval
• [cs.CL]MultiModalQA: Complex Question Answering over Text, Tables and Images
• [cs.CL]Multilingual Transfer Learning for Code-Switched Language and Speech Neural Modeling
• [cs.CL]On the Impact of Knowledge-based Linguistic Annotations in the Quality of Scientific Embeddings
• [cs.CL]On the Impact of Random Seeds on the Fairness of Clinical Classifiers
• [cs.CL]On the Use of Linguistic Features for the Evaluation of Generative Dialogue Systems
• [cs.CL]Paragraph-level Simplification of Medical Texts
• [cs.CL]Plot-guided Adversarial Example Construction for Evaluating Open-domain Story Generation
• [cs.CL]QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
• [cs.CL]QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization
• [cs.CL]Reducing Discontinuous to Continuous Parsing with Pointer Network Reordering
• [cs.CL]Relational world knowledge representation in contextual language models: A review
• [cs.CL]Restoring and Mining the Records of the Joseon Dynasty via Neural Language Modeling and Machine Translation
• [cs.CL]Semantic maps and metrics for science Semantic maps and metrics for science using deep transformer encoders
• [cs.CL]SpartQA: : A Textual Question Answering Benchmark for Spatial Reasoning
• [cs.CL]Structural analysis of an all-purpose question answering model
• [cs.CL]Targeted Adversarial Training for Natural Language Understanding
• [cs.CL]Towards a parallel corpus of Portuguese and the Bantu language Emakhuwa of Mozambique
• [cs.CL]Transformer-based Methods for Recognizing Ultra Fine-grained Entities (RUFES)
• [cs.CL]UPB at SemEval-2021 Task 7: Adversarial Multi-Task Learning for Detecting and Rating Humor and Offense
• [cs.CL]Understanding Hard Negatives in Noise Contrastive Estimation
• [cs.CL]Understanding Transformers for Bot Detection in Twitter
• [cs.CL]What’s in your Head? Emergent Behaviour in Multi-Task Transformer Models
• [cs.CR]Fall of Giants: How popular text-based MLaaS fall against a simple evasion attack
• [cs.CR]On Mignotte Secret Sharing Schemes over Gaussian Integers
• [cs.CV]All you need are a few pixels: semantic segmentation with PixelPick
• [cs.CV]Anomaly Detection in Image Datasets Using Convolutional Neural Networks, Center Loss, and Mahalanobis Distance
• [cs.CV]Automatic Correction of Internal Units in Generative Neural Networks
• [cs.CV]BARF: Bundle-Adjusting Neural Radiance Fields
• [cs.CV]Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds
• [cs.CV]CLEVR_HYP: A Challenge Dataset and Baselines for Visual Question Answering with Hypothetical Actions over Images
• [cs.CV]Co-Scale Conv-Attentional Image Transformers
• [cs.CV]Common Limitations of Image Processing Metrics: A Picture Story
• [cs.CV]Contrastive Context-Aware Learning for 3D High-Fidelity Mask Face Presentation Attack Detection
• [cs.CV]Crossover Learning for Fast Online Video Instance Segmentation
• [cs.CV]Dealing with Missing Modalities in the Visual Question Answer-Difference Prediction Task through Knowledge Distillation
• [cs.CV]Deep learning using Havrda-Charvat entropy for classification of pulmonary endomicroscopy
• [cs.CV]Disentangled Motif-aware Graph Learning for Phrase Grounding
• [cs.CV]Domain Adaptive Monocular Depth Estimation With Semantic Information
• [cs.CV]DropLoss for Long-Tail Instance Segmentation
• [cs.CV]Dynamic Fusion Network For Light Field Depth Estimation
• [cs.CV]Dynamic Texture Synthesis By Incorporating Long-range Spatial and Temporal Correlations
• [cs.CV]Event-based Timestamp Image Encoding Network for Human Action Recognition and Anticipation
• [cs.CV]Fast Hierarchical Games for Image Explanations
• [cs.CV]First and Second Order Dynamics in a Hierarchical SOM system for Action Recognition
• [cs.CV]Generalizable Multi-Camera 3D Pedestrian Detection
• [cs.CV]Geometry-aware data augmentation for monocular 3D object detection
• [cs.CV]Global Transport for Fluid Reconstruction with Learned Self-Supervision
• [cs.CV]IMAGINE: Image Synthesis by Image-Guided Model Inversion
• [cs.CV]Improving Long-Tailed Classification from Instance Level
• [cs.CV]Interpretability-Driven Sample Selection Using Self Supervised Learning For Disease Classification And Segmentation
• [cs.CV]Learning Multi-modal Information for Robust Light Field Depth Estimation
• [cs.CV]Lite-HRNet: A Lightweight High-Resolution Network
• [cs.CV]Localization-Based Tracking
• [cs.CV]MESD: Exploring Optical Flow Assessment on Edge of Motion Objects with Motion Edge Structure Difference
• [cs.CV]Mixed supervision for surface-defect detection: from weakly to fully supervised learning
• [cs.CV]Multi-View Image-to-Image Translation Supervised by 3D Pose
• [cs.CV]NewsCLIPpings: Automatic Generation of Out-of-Context Multimodal Media
• [cs.CV]OCM3D: Object-Centric Monocular 3D Object Detection
• [cs.CV]Object-Centric Representation Learning for Video Question Answering
• [cs.CV]PHI-MVS: Plane Hypothesis Inference Multi-view Stereo for Large-Scale Scene Reconstruction
• [cs.CV]Pointly-Supervised Instance Segmentation
• [cs.CV]SPARK: SPAcecraft Recognition leveraging Knowledge of Space Environment
• [cs.CV]SRR-Net: A Super-Resolution-Involved Reconstruction Method for High Resolution MR Imaging
• [cs.CV]Self-supervised object detection from audio-visual correspondence
• [cs.CV]Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalization
• [cs.CV]Shape and Material Capture at Home
• [cs.CV]Spatially Varying Label Smoothing: Capturing Uncertainty from Expert Annotations
• [cs.CV]StereoPIFu: Depth Aware Clothed Human Digitization via Stereo Vision
• [cs.CV]Towards Extremely Compact RNNs for Video Recognition with Fully Decomposed Hierarchical Tucker Structure
• [cs.CV]Towards Fast and Accurate Real-World Depth Super-Resolution: Benchmark Dataset and Baseline
• [cs.CV]UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-identification
• [cs.CV]VR3Dense: Voxel Representation Learning for 3D Object Detection and Monocular Dense Depth Reconstruction
• [cs.CV]VariTex: Variational Neural Face Textures
• [cs.CV]Very Lightweight Photo Retouching Network with Conditional Sequential Modulation
• [cs.CV]View-Guided Point Cloud Completion
• [cs.CV]Visual Goal-Step Inference using wikiHow
• [cs.CY]The AppChk Crowd-Sourcing Platform: Which third parties are iOS apps talking to?
• [cs.CY]What’s Your Value of Travel Time? Collecting Traveler-Centered Mobility Data via Crowdsourcing
• [cs.DC]Communication Efficient Federated Learning with Adaptive Quantization
• [cs.DC]High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models
• [cs.DC]Optimal Data Placement for Data-Sharing Scientific Workflows in Heterogeneous Edge-Cloud Computing Environments
• [cs.DC]The Programming of Deep Learning Accelerators as a Constraint Satisfaction Problem
• [cs.GR]ShapeMOD: Macro Operation Discovery for 3D Shape Programs
• [cs.IR]An Adversarial Imitation Click Model for Information Retrieval
• [cs.IR]Generating Code with the Help of Retrieved Template Functions and Stack Overflow Answers
• [cs.IR]On the instability of embeddings for recommender systems: the case of Matrix Factorization
• [cs.IT]Joint Optimization of Preamble Selection and Access Barring for MTC with Correlated Device Activities
• [cs.IT]Large-scale IRS-aided MIMO over Double-scattering Channel: An Asymptotic Approach
• [cs.IT]List Message Passing Decoding of Non-binary Low-Density Parity-Check Codes
• [cs.IT]No-Pain No-Gain: DRL Assisted Optimization in Energy-Constrained CR-NOMA Networks
• [cs.IT]On Minimax Detection of Gaussian Stochastic Sequences and Gaussian Stationary Signals
• [cs.IT]On the efficiency of polar-like decoding for symmetric codes
• [cs.IT]Probabilistic Accumulate-then-Transmit in Wireless-Powered Covert Communications
• [cs.IT]Secure Cognitive Radio Communication via Intelligent Reflecting Surface
• [cs.IT]Wireless Environment as a Service Enabled by Reconfigurable Intelligent Surfaces: The RISE-6G Perspective
• [cs.LG]-CLUE: Diverse Sets of Explanations for Uncertainty Estimates
• [cs.LG]1-bit LAMB: Communication Efficient Large-Scale Large-Batch Training with LAMB’s Convergence Speed
• [cs.LG]A Recipe for Global Convergence Guarantee in Deep Neural Networks
• [cs.LG]A Tale of Two Lexica Testing Computational Hypotheses with Deep Convolutional Neural Networks
• [cs.LG]Active learning for medical code assignment
• [cs.LG]Adversarial autoencoders and adversarial LSTM for improved forecasts of urban air pollution simulations
• [cs.LG]Censored Semi-Bandits for Resource Allocation
• [cs.LG]Conclusive Local Interpretation Rules for Random Forests
• [cs.LG]Contextual HyperNetworks for Novel Feature Adaptation
• [cs.LG]Data-Driven Reinforcement Learning for Virtual Character Animation Control
• [cs.LG]Distilling Wikipedia mathematical knowledge into neural network models
• [cs.LG]Does My Representation Capture X? Probe-Ably
• [cs.LG]Efficient Optimal Transport Algorithm by Accelerated Gradient descent
• [cs.LG]Enhancing User’ s Income Estimation with Super-App Alternative Data
• [cs.LG]Finite Volume Neural Network: Modeling Subsurface Contaminant Transport
• [cs.LG]GSA-Forecaster: Forecasting Graph-Based Time-Dependent Data with Graph Sequence Attention
• [cs.LG]Hierarchical Adaptive Pooling by Capturing High-order Dependency for Graph Representation Learning
• [cs.LG]Learning and Planning in Complex Action Spaces
• [cs.LG]Learning to recover orientations from projections in single-particle cryo-EM
• [cs.LG]LioNets: A Neural-Specific Local Interpretation Technique Exploiting Penultimate Layer Information
• [cs.LG]Meta-Regularization: An Approach to Adaptive Choice of the Learning Rate in Gradient Descent
• [cs.LG]Mitigating Adversarial Attack for Compute-in-Memory Accelerator Utilizing On-chip Finetune
• [cs.LG]Model Learning with Personalized Interpretability Estimation (ML-PIE)
• [cs.LG]Muesli: Combining Improvements in Policy Optimization
• [cs.LG]Multivariate Deep Evidential Regression
• [cs.LG]Neural Network for Weighted Signal Temporal Logic
• [cs.LG]Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx
• [cs.LG]Neuro-Symbolic VQA: A review from the perspective of AGI desiderata
• [cs.LG]On the validity of kernel approximations for orthogonally-initialized neural networks
• [cs.LG]One-class Autoencoder Approach for Optimal Elect
1362
rode Set-up Identification in Wearable EEG Event Monitoring
• [cs.LG]Online and Offline Reinforcement Learning by Planning with a Learned Model
• [cs.LG]Optimizing the Long-Term Average Reward for Continuing MDPs: A Technical Report
• [cs.LG]Podracer architectures for scalable Reinforcement Learning
• [cs.LG]Practical Defences Against Model Inversion Attacks for Split Neural Networks
• [cs.LG]Probing Negative Sampling Strategies to Learn GraphRepresentations via Unsupervised Contrastive Learning
• [cs.LG]Real-time Forecast Models for TBM Load Parameters Based on Machine Learning Methods
• [cs.LG]Recurrent Equilibrium Networks: Unconstrained Learning of Stable and Robust Dynamical Models
• [cs.LG]Revisiting Bayesian Autoencoders with MCMC
• [cs.LG]Reward Shaping with Dynamic Trajectory Aggregation
• [cs.LG]Sample-based and Feature-based Federated Learning via Mini-batch SSCA
• [cs.LG]Semiring Primitives for Sparse Neighborhood Methods on the GPU
• [cs.LG]Sequential Ski Rental Problem
• [cs.LG]Simpler Certified Radius Maximization by Propagating Covariances
• [cs.LG]The Impact of Activation Sparsity on Overfitting in Convolutional Neural Networks
• [cs.LG]The Many Faces of 1-Lipschitz Neural Networks
• [cs.LG]Thief, Beware of What Get You There: Towards Understanding Model Extraction Attack
• [cs.LG]Tracking translation invariance in CNNs
• [cs.LG]Which Hyperparameters to Optimise? An Investigation of Evoluationary Hyperaprameter Optimisation in Graph Neural Network For Molecular Property Prediction
• [cs.MM]”Subverting the Jewtocracy”: Online Antisemitism Detection Using Multimodal Deep Learning
• [cs.NE]A coevolutionary approach to deep multi-agent reinforcement learning
• [cs.NE]An Adaptive Synaptic Array using Fowler-Nordheim Dynamic Analog Memory
• [cs.NE]Multiple regression techniques for modeling dates of first performances of Shakespeare-era plays
• [cs.PF]NekRS, a GPU-Accelerated Spectral Element Navier-Stokes Solver
• [cs.RO]Cobbler Stick With Your Reads: People’s Perceptions of Gendered Robots Performing Gender Stereotypical Tasks
• [cs.RO]Deep Deterministic Path Following
• [cs.RO]Generative Design of NU’s Husky Carbon, A Morpho-Functional, Legged Robot
• [cs.RO]Group Surfing: A Pedestrian-Based Approach to Sidewalk Robot Navigation
• [cs.RO]Inertial Collaborative Localisation for Autonomous Vehicles using a Minimum Energy Filter
• [cs.RO]Online Recognition of Actions Involving Objects
• [cs.RO]Optimal Multi-Manipulator Arm Placement for Maximal Dexterity during Robotics Surgery
• [cs.RO]RECON: Rapid Exploration for Open-World Navigation with Latent Goal Models
• [cs.RO]Terrain assessment for precision agriculture using vehicle dynamic modelling
• [cs.RO]Towards a Next Generation Computing Paradigm: Approximate Computing in Robotics Systems and Environment-Experimentation, Case Study and Practical Implications
• [cs.RO]Trimanipulation: Evaluation of human performance in a 3-handed coordination task
• [cs.RO]What is the appropriate speed for an autonomous vehicle? Designing a Pedestrian Aware Contextual Speed Controller
• [cs.SD]NoiseVC: Towards High Quality Zero-Shot Voice Conversion
• [cs.SD]Visually Informed Binaural Audio Generation without Binaural Audios
• [cs.SE]Detecting Operational Adversarial Examples for Reliable Deep Learning
• [cs.SE]Evaluating Pre-Trained Models for User Feedback Analysis in Software Engineering: A Study on Classification of App-Reviews
• [cs.SI]Clustering of temporal nodes profiles in dynamic networks of contacts
• [cs.SI]Media Cloud: Massive Open Source Collection of Global News on the Open Web
• [cs.SI]On Representation Learning for Scientific News Articles Using Heterogeneous Knowledge Graphs
• [cs.SI]Relevance-Aware Anomalous Users Detection in Social Network
• [econ.GN]Analysis of the tradeoff between health and economic impacts of the Covid-19 epidemic
• [eess.IV]A State-of-the-art Survey of Artificial Neural Networks for Whole-slide Image Analysis:from Popular Convolutional Neural Networks to Potential Visual Transformers
• [eess.IV]COVID-19 detection using chest X-rays: is lung segmentation important for generalization?
• [eess.IV]Efficient Space-time Video Super Resolution using Low-Resolution Flow and Mas
787
k Upsampling
• [eess.IV]Fibro-CoSANet: Pulmonary Fibrosis Prognosis Prediction using a Convolutional Self Attention Network
• [eess.IV]Latent Correlation Representation Learning for Brain Tumor Segmentation with Missing MRI Modalities
• [eess.IV]Spatiotemporal Entropy Model is All You Need for Learned Video Compression
• [eess.IV]Unifying domain adaptation and self-supervised learning for CXR segmentation via AdaIN-based knowledge distillation
• [eess.SP]Jittering Effects Analysis and Beam Training Design for UAV Millimeter Wave Communications
• [eess.SP]Joint Secure Design of Downlink and D2D Cooperation Strategies for Multi-User Systems
• [eess.SP]Orthogonal Time Sequency Multiplexing Modulation: Analysis and Low-Complexity Receiver Design
• [eess.SY]Bi-level Off-policy Reinforcement Learning for Volt/VAR Control Involving Continuous and Discrete Devices
• [eess.SY]Evidence-based Prescriptive Analytics, CAUSAL Digital Twin and a Learning Estimation Algorithm
• [math.OC]On the Linear Ordering Problem and the Rankability of Data
• [math.OC]Optimization of Reconfigurable Intelligent Surfaces with Electromagnetic Field Exposure Constraints
• [math.ST]Bahadur efficiency of the maximum likelihood estimator and one-step estimator for quasi-arithmetic means of the Cauchy distribution
• [math.ST]Characterizations of the maximum likelihood estimator of the Cauchy distribution
• [math.ST]Confidence disc for Cauchy distributions
• [math.ST]Limit theorems for quasi-arithmetic means of random variables with applications to point estimations for the Cauchy distribution
• [physics.geo-ph]Learning by example: fast reliability-aware seismic imaging with normalizing flows
• [physics.geo-ph]Predicting the Accuracy of Early-est Earthquake Magnitude Estimates with an LSTM Neural Network: A Preliminary Analysis
• [physics.soc-ph]The world-wide waste web
• [q-bio.NC]Temporal EigenPAC for dyslexia diagnosis
• [q-bio.QM]Bayesian Optimisation for a Biologically Inspired Population Neural Network
• [q-fin.ST]Loss of structural balance in stock markets
• [quant-ph]Equivalence of quantum barren plateaus to cost concentration and narrow gorges
• [stat.AP]A review and evaluation of secondary school accountability in England: Statistical strengths, weaknesses, and challenges for ‘Progress 8’
• [stat.AP]Inferring Risks of Coronavirus Transmission from Community Household Data
• [stat.CO]The computational asymptotics of Gaussian variational inference
• [stat.ME]A spatial modeling framework for monitoring surveys with different sampling protocols with a case study for bird populations in mid-Scandinavia
• [stat.ME]Center-specific causal inference with multicenter trials: reinterpreting trial evidence in the context of each participating center
• [stat.ME]Deconfounding Scores: Feature Representations for Causal Effect Estimation with Weak Overlap
• [stat.ME]Optimal scaling of random walk Metropolis algorithms using Bayesian large-sample asymptotics
• [stat.ME]Optimal transport couplings of Gibbs samplers on partitions for unbiased estimation
• [stat.ME]Poisson Network Autoregression
• [stat.ML]COVID-19 case data for Italy stratified by age class
• [stat.ML]Deep imagination is a close to optimal policy for planning in large decision trees under limited resources
• [stat.ML]Thresholded Graphical Lasso Adjusts for Latent Variables: Application to Functional Neural Connectivity
• [stat.ML]Towards Unbiased Random Features with LowerVariance For Stationary Indefinite Kernels
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• [astro-ph.IM]Prediction of Apophis Asteroid Flyby Optimal Trajectories and Data Fusion of Earth-Apophis Mission Launch Windows using Deep Neural Networks
Manuel Ntumba, Saurabh Gore, Jean-Baptiste Awanyo
http://arxiv.org/abs/2104.06249v1
• [cond-mat.mtrl-sci]Understanding Fission Gas Bubble Distribution, Lanthanide Transportation, and Thermal Conductivity Degradation in Neutron-irradiated α-U Using Machine Learning
Lu Cai, Fei Xu, Fidelma Dilemma, Daniel J. Murray, Cynthia A. Adkins, Larry K Aagesen Jr, Min Xian, Luca Caprriot, Tiankai Yao
http://arxiv.org/abs/2104.05786v1
• [cond-mat.stat-mech]Variational Autoencoder Analysis of Ising Model Statistical Distributions and Phase Transitions
David Yevick
http://arxiv.org/abs/2104.06368v1
• [cs.AI]Agents for Automated User Experience Testing
Pedro M. Fernandes, Manuel Lopes, Rui Prada
http://arxiv.org/abs/2104.06220v1
• [cs.AI]AutoOED: Automated Optimal Experiment Design Platform
Yunsheng Tian, Mina Konaković Luković, Timothy Erps, Michael Foshey, Wojciech Matusik
http://arxiv.org/abs/2104.05959v1
• [cs.AI]BlockGNN: Towards Efficient GNN Acceleration Using Block-Circulant Weight Matrices
Zhe Zhou, Bizhao Shi, Zhe Zhang, Yijin Guan, Guangyu Sun, Guojie Luo
http://arxiv.org/abs/2104.06214v1
• [cs.AI]Future is not One-dimensional: Graph Modeling based Complex Event Schema Induction for Event Prediction
Manling Li, Sha Li, Zhenhailong Wang, Lifu Huang, Kyunghyun Cho, Heng Ji, Jiawei Han, Clare Voss
http://arxiv.org/abs/2104.06344v1
• [cs.AI]Gradient Kernel Regression
Matt Calder
http://arxiv.org/abs/2104.05874v1
• [cs.AI]Group Recommendation Techniques for Feature Modeling and Configuration
Viet-Man Le
http://arxiv.org/abs/2104.06054v1
• [cs.AI]Level Generation for Angry Birds with Sequential VAE and Latent Variable Evolution
Takumi Tanabe, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
http://arxiv.org/abs/2104.06106v1
• [cs.AI]On the Computational Intelligibility of Boolean Classifiers
Gilles Audemard, Steve Bellart, Louenas Bounia, Frédéric Koriche, Jean-Marie Lagniez, Pierre Marquis
http://arxiv.org/abs/2104.06172v1
• [cs.AI]Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads
Evangelos Georganas, Dhiraj Kalamkar, Sasikanth Avancha, Menachem Adelman, Cristina Anderson, Alexander Breuer, Abhisek Kundu, Vasimuddin Md, Sanchit Misra, Ramanarayan Mohanty, Hans Pabst, Barukh Ziv, Alexander Heinecke
http://arxiv.org/abs/2104.05755v1
• [cs.AI]Two-stage training algorithm for AI robot soccer
Taeyoung Kim, Luiz Felipe Vecchietti, Kyujin Choi, Sanem Sariel, Dongsoo Har
http://arxiv.org/abs/2104.05931v1
• [cs.CL]A Replication Study of Dense Passage Retriever
Xueguang Ma, Kai Sun, Ronak Pradeep, Jimmy Lin
http://arxiv.org/abs/2104.05740v1
• [cs.CL]Bridging the Gap Between Clean Data Training and Real-World Inference for Spoken Language Understanding
Di Wu, Yiren Chen, Liang Ding, Dacheng Tao
http://arxiv.org/abs/2104.06393v1
• [cs.CL]Deep Learning for Prominence Detection in Children’s Read Speech
Kamini Sabu, Mithilesh Vaidya, Preeti Rao
http://arxiv.org/abs/2104.05488v2
• [cs.CL]Detoxifying Language Models Risks Marginalizing Minority Voices
Albert Xu, Eshaan Pathak, Eric Wallace, Suchin Gururangan, Maarten Sap, Dan Klein
http://arxiv.org/abs/2104.06390v1
• [cs.CL]DirectProbe: Studying Representations without Classifiers
Yichu Zhou, Vivek Srikumar
http://arxiv.org/abs/2104.05904v1
• [cs.CL]Discourse Probing of Pretrained Language Models
Fajri Koto, Jey Han Lau, Timothy Baldwin
http://arxiv.org/abs/2104.05882v1
• [cs.CL]Document-Level Event Argument Extraction by Conditional Generation
Sha Li, Heng Ji, Jiawei Han
http://arxiv.org/abs/2104.05919v1
• [cs.CL]EXPLAINABOARD: An Explainable Leaderboard for NLP
Pengfei Liu, Jinlan Fu, Yang Xiao, Weizhe Yuan, Shuaicheng Chang, Junqi Dai, Yixin Liu, Zihuiwen Ye, Graham Neubig
http://arxiv.org/abs/2104.06387v1
• [cs.CL]Equivalence of Segmental and Neural Transducer Modeling: A Proof of Concept
Wei Zhou, Albert Zeyer, André Merboldt, Ralf Schlüter, Hermann Ney
http://arxiv.org/abs/2104.06104v1
• [cs.CL]Evaluating Saliency Methods for Neural Language Models
Shuoyang Ding, Philipp Koehn
http://arxiv.org/abs/2104.05824v1
• [cs.CL]Experiments of ASR-based mispronunciation detection for children and adult English learners
Nina Hosseini-Kivanani, Roberto Gretter, Marco Matassoni, Giuseppe Daniele Falavigna
http://arxiv.org/abs/2104.05980v1
• [cs.CL]Family of Origin and Family of Choice: Massively Parallel Lexiconized Iterative Pretraining for Severely Low Resource Machine Translation
Zhong Zhou, Alex Waibel
http://arxiv.org/abs/2104.05848v1
• [cs.CL]Few-shot Intent Classification and Slot Filling with Retrieved Examples
Dian Yu, Luheng He, Yuan Zhang, Xinya Du, Panupong Pasupat, Qi Li
http://arxiv.org/abs/2104.05763v1
• [cs.CL]Fighting the COVID-19 Infodemic with a Holistic BERT Ensemble
Giorgos Tziafas, Konstantinos Kogkalidis, Tommaso Caselli
http://arxiv.org/abs/2104.05745v1
• [cs.CL]Finding Concept-specific Biases in Form—Meaning Associations
Tiago Pimentel, Brian Roark, Søren Wichmann, Ryan Cotterell, Damián Blasi
http://arxiv.org/abs/2104.06325v1
• [cs.CL]From partners to populations: A hierarchical Bayesian account of coordination and convention
Robert D. Hawkins, Michael Franke, Michael C. Frank, Kenny Smith, Thomas L. Griffiths, Noah D. Goodman
http://arxiv.org/abs/2104.05857v1
• [cs.CL]GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity Recognition
Xinyan Zhao, Haibo Ding, Zhe Feng
http://arxiv.org/abs/2104.06230v1
• [cs.CL]Gender Bias in Machine Translation
Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, Marco Turchi
http://arxiv.org/abs/2104.06001v1
• [cs.CL]Learning from Executions for Semantic Parsing
Bailin Wang, Mirella Lapata, Ivan Titov
http://arxiv.org/abs/2104.05819v1
• [cs.CL]Learning to Synthesize Data for Semantic Parsing
Bailin Wang, Wenpeng Yin, Xi Victoria Lin, Caiming Xiong
http://arxiv.org/abs/2104.05827v1
• [cs.CL]Lessons on Parameter Sharing across Layers in Transformers
Sho Takase, Shun Kiyono
http://arxiv.org/abs/2104.06022v1
• [cs.CL]Mediators in Determining what Processing BERT Performs First
Aviv Slobodkin, Leshem Choshen, Omri Abend
http://arxiv.org/abs/2104.06400v1
• [cs.CL]Modeling the dynamics of language change: logistic regression, Piotrowski’s law, and a handful of examples in Polish
Rafał L. Górski, Maciej Eder
http://arxiv.org/abs/2104.06324v1
• [cs.CL]Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval
Chen Zhao, Chenyan Xiong, Jordan Boyd-Graber, Hal Daumé III
http://arxiv.org/abs/2104.05883v1
• [cs.CL]MultiModalQA: Complex Question Answering over Text, Tables and Images
Alon Talmor, Ori Yoran, Amnon Catav, Dan Lahav, Yizhong Wang, Akari Asai, Gabriel Ilharco, Hannaneh Hajishirzi, Jonathan Berant
http://arxiv.org/abs/2104.06039v1
• [cs.CL]Multilingual Transfer Learning for Code-Switched Language and Speech Neural Modeling
Genta Indra Winata
http://arxiv.org/abs/2104.06268v1
• [cs.CL]On the Impact of Knowledge-based Linguistic Annotations in the Quality of Scientific Embeddings
Andres Garcia-Silva, Ronald Denaux, Jose Manuel Gomez-Perez
http://arxiv.org/abs/2104.06200v1
• [cs.CL]On the Impact of Random Seeds on the Fairness of Clinical Classifiers
Silvio Amir, Jan-Willem van de Meent, Byron C. Wallace
http://arxiv.org/abs/2104.06338v1
• [cs.CL]On the Use of Linguistic Features for the Evaluation of Generative Dialogue Systems
Ian Berlot-Attwell, Frank Rudzicz
http://arxiv.org/abs/2104.06335v1
• [cs.CL]Paragraph-level Simplification of Medical Texts
Ashwin Devaraj, Iain J. Marshall, Byron C. Wallace, Junyi Jessy Li
http://arxiv.org/abs/2104.05767v1
• [cs.CL]Plot-guided Adversarial Example Construction for Evaluating Open-domain Story Generation
Sarik Ghazarian, Zixi Liu, Akash SM, Ralph Weischedel, Aram Galstyan, Nanyun Peng
http://arxiv.org/abs/2104.05801v1
• [cs.CL]QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
Michihiro Yasunaga, Hongyu Ren, Antoine Bosselut, Percy Liang, Jure Leskovec
http://arxiv.org/abs/2104.06378v1
• [cs.CL]QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization
Ming Zhong, Da Yin, Tao Yu, Ahmad Zaidi, Mutethia Mutuma, Rahul Jha, Ahmed Hassan Awadallah, Asli Celikyilmaz, Yang Liu, Xipeng Qiu, Dragomir Radev
http://arxiv.org/abs/2104.05938v1
• [cs.CL]Reducing Discontinuous to Continuous Parsing with Pointer Network Reordering
Daniel Fernández-González, Carlos Gómez-Rodríguez
http://arxiv.org/abs/2104.06239v1
• [cs.CL]Relational world knowledge representation in contextual language models: A review
Tara Safavi, Danai Koutra
http://arxiv.org/abs/2104.05837v1
• [cs.CL]Restoring and Mining the Records of the Joseon Dynasty via Neural Language Modeling and Machine Translation
Kyeongpil Kang, Kyohoon Jin, Soyoung Yang, Sujin Jang, Jaegul Choo, Yougbin Kim
http://arxiv.org/abs/2104.05964v1
• [cs.CL]Semantic maps and metrics for science Semantic maps and metrics for science using deep transformer encoders
Brendan Chambers, James Evans
http://arxiv.org/abs/2104.05928v1
• [cs.CL]SpartQA: : A Textual Question Answering Benchmark for Spatial Reasoning
Roshanak Mirzaee, Hossein Rajaby Faghihi, Qiang Ning, Parisa Kordjmashidi
http://arxiv.org/abs/2104.05832v1
• [cs.CL]Structural analysis of an all-purpose question answering model
Vincent Micheli, Quentin Heinrich, François Fleuret, Wacim Belblidia
http://arxiv.org/abs/2104.06045v1
• [cs.CL]Targeted Adversarial Training for Natural Language Understanding
Lis Pereira, Xiaodong Liu, Hao Cheng, Hoifung Poon, Jianfeng Gao, Ichiro Kobayashi
http://arxiv.org/abs/2104.05847v1
• [cs.CL]Towards a parallel corpus of Portuguese and the Bantu language Emakhuwa of Mozambique
Felermino D. M. A. Ali, Andrew Caines, Jaimito L. A. Malavi
http://arxiv.org/abs/2104.05753v1
• [cs.CL]Transformer-based Methods for Recognizing Ultra Fine-grained Entities (RUFES)
Emanuela Boros, Antoine Doucet
http://arxiv.org/abs/2104.06048v1
• [cs.CL]UPB at SemEval-2021 Task 7: Adversarial Multi-Task Learning for Detecting and Rating Humor and Offense
Răzvan-Alexandru Smădu, Dumitru-Clementin Cercel, Mihai Dascalu
http://arxiv.org/abs/2104.06063v1
• [cs.CL]Understanding Hard Negatives in Noise Contrastive Estimation
Wenzheng Zhang, Karl Stratos
http://arxiv.org/abs/2104.06245v1
• [cs.CL]Understanding Transformers for Bot Detection in Twitter
Andres Garcia-Silva, Cristian Berrio, Jose Manuel Gomez-Perez
http://arxiv.org/abs/2104.06182v1
• [cs.CL]What’s in your Head? Emergent Behaviour in Multi-Task Transformer Models
Mor Geva, Uri Katz, Aviv Ben-Arie, Jonathan Berant
http://arxiv.org/abs/2104.06129v1
• [cs.CR]Fall of Giants: How popular text-based MLaaS fall against a simple evasion attack
Luca Pajola, Mauro Conti
http://arxiv.org/abs/2104.05996v1
• [cs.CR]On Mignotte Secret Sharing Schemes over Gaussian Integers
Diego Munuera-Merayo
http://arxiv.org/abs/2104.06361v1
• [cs.CV]All you need are a few pixels: semantic segmentation with PixelPick
Gyungin Shin, Weidi Xie, Samuel Albanie
http://arxiv.org/abs/2104.06394v1
• [cs.CV]Anomaly Detection in Image Datasets Using Convolutional Neural Networks, Center Loss, and Mahalanobis Distance
Garnik Vareldzhan, Kirill Yurkov, Konstantin Ushenin
http://arxiv.org/abs/2104.06193v1
• [cs.CV]Automatic Correction of Internal Units in Generative Neural Networks
Ali Tousi, Haedong Jeong, Jiyeon Han, Hwanil Choi, Jaesik Choi
http://arxiv.org/abs/2104.06118v1
• [cs.CV]BARF: Bundle-Adjusting Neural Radiance Fields
Chen-Hsuan Lin, Wei-Chiu Ma, Antonio Torralba, Simon Lucey
http://arxiv.org/abs/2104.06405v1
• [cs.CV]Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds
Bowen Cheng, Lu Sheng, Shaoshuai Shi, Ming Yang, Dong Xu
http://arxiv.org/abs/2104.06114v1
• [cs.CV]CLEVR_HYP: A Challenge Dataset and Baselines for Visual Question Answering with Hypothetical Actions over Images
Shailaja Keyur Sampat, Akshay Kumar, Yezhou Yang, Chitta Baral
http://arxiv.org/abs/2104.05981v1
• [cs.CV]Co-Scale Conv-Attentional Image Transformers
Weijian Xu, Yifan Xu, Tyler Chang, Zhuowen Tu
http://arxiv.org/abs/2104.06399v1
• [cs.CV]Common Limitations of Image Processing Metrics: A Picture Story
Annika Reinke, Matthias Eisenmann, Minu D. Tizabi, Carole H. Sudre, Tim Rädsch, Michela Antonelli, Tal Arbel, Spyridon Bakas, M. Jorge Cardoso, Veronika Cheplygina, Keyvan Farahani, Ben Glocker, Doreen Heckmann-Nötzel, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Jens Kleesiek, Tahsin Kurc, Michal Kozubek, Bennett A. Landman, Geert Litjens, Klaus Maier-Hein, Bjoern Menze, Henning Müller, Jens Petersen, Mauricio Reyes, Nicola Rieke, Bram Stieltjes, Ronald M. Summers, Sotirios A. Tsaftaris, Bram van Ginneken, Annette Kopp-Schneider, Paul Jäger, Lena Maier-Hein
http://arxiv.org/abs/2104.05642v2
• [cs.CV]Contrastive Context-Aware Learning for 3D High-Fidelity Mask Face Presentation Attack Detection
Ajian Liu, Chenxu Zhao, Zitong Yu, Jun Wan, Anyang Su, Xing Liu, Zichang Tan, Sergio Escalera, Junliang Xing, Yanyan Liang, Guodong Guo, Zhen Lei, Stan Z. Li, Du Zhang
http://arxiv.org/abs/2104.06148v1
• [cs.CV]Crossover Learning for Fast Online Video Instance Segmentation
Shusheng Yang, Yuxin Fang, Xinggang Wang, Yu Li, Chen Fang, Ying Shan, Bin Feng, Wenyu Liu
http://arxiv.org/abs/2104.05970v1
• [cs.CV]Dealing with Missing Modalities in the Visual Question Answer-Difference Prediction Task through Knowledge Distillation
Jae Won Cho, Dong-Jin Kim, Jinsoo Choi, Yunjae Jung, In So Kweon
http://arxiv.org/abs/2104.05965v1
• [cs.CV]Deep learning using Havrda-Charvat entropy for classification of pulmonary endomicroscopy
Thibaud Brochet, Jerome Lapuyade-Lahorgue, Sebastien Bougleux, Mathieu Salaun, Su Ruan
http://arxiv.org/abs/2104.05450v2
• [cs.CV]Disentangled Motif-aware Graph Learning for Phrase Grounding
Zongshen Mu, Siliang Tang, Jie Tan, Qiang Yu, Yueting Zhuang
http://arxiv.org/abs/2104.06008v1
• [cs.CV]Domain Adaptive Monocular Depth Estimation With Semantic Information
Fei Lu, Hyeonwoo Yu, Jean Oh
http://arxiv.org/abs/2104.05764v1
• [cs.CV]DropLoss for Long-Tail Instance Segmentation
Ting-I Hsieh, Esther Robb, Hwann-Tzong Chen, Jia-Bin Huang
http://arxiv.org/abs/2104.06402v1
• [cs.CV]Dynamic Fusion Network For Light Field Depth Estimation
Yongri Piao, Yukun Zhang, Miao Zhang, Xinxin Ji
http://arxiv.org/abs/2104.05969v1
• [cs.CV]Dynamic Texture Synthesis By Incorporating Long-range Spatial and Temporal Correlations
Kaitai Zhang, Bin Wang, Hong-Shuo Chen, Ye Wang, Shiyu Mou, C. -C. Jay Kuo
http://arxiv.org/abs/2104.05940v1
• [cs.CV]Event-based Timestamp Image Encoding Network for Human Action Recognition and Anticipation
Chaoxing Huang
http://arxiv.org/abs/2104.05145v2
• [cs.CV]Fast Hierarchical Games for Image Explanations
Jacopo Teneggi, Alexandre Luster, Jeremias Sulam
http://arxiv.org/abs/2104.06164v1
• [cs.CV]First and Second Order Dynamics in a Hierarchical SOM system for Action Recognition
Zahra Gharaee, Peter Gärdenfors, Magnus Johnsson
http://arxiv.org/abs/2104.06059v1
• [cs.CV]Generalizable Multi-Camera 3D Pedestrian Detection
João Paulo Lima, Rafael Roberto, Lucas Figueiredo, Francisco Simões, Veronica Teichrieb
http://arxiv.org/abs/2104.05813v1
• [cs.CV]Geometry-aware data augmentation for monocular 3D object detection
Qing Lian, Botao Ye, Ruijia Xu, Weilong Yao, Tong Zhang
http://arxiv.org/abs/2104.05858v1
• [cs.CV]Global Transport for Fluid Reconstruction with Learned Self-Supervision
Erik Franz, Barbara Solenthaler, Nils Thuerey
http://arxiv.org/abs/2104.06031v1
• [cs.CV]IMAGINE: Image Synthesis by Image-Guided Model Inversion
Pei Wang, Yijun Li, Krishna Kumar Singh, Jingwan Lu, Nuno Vasconcelos
http://arxiv.org/abs/2104.05895v1
• [cs.CV]Improving Long-Tailed Classification from Instance Level
Yan Zhao, Weicong Chen, Xu Tan, Kai Huang, Jin Xu, Changhu Wang, Jihong Zhu
http://arxiv.org/abs/2104.06094v1
• [cs.CV]Interpretability-Driven Sample Selection Using Self Supervised Learning For Disease Classification And Segmentation
Dwarikanath Mahapatra
http://arxiv.org/abs/2104.06087v1
• [cs.CV]Learning Multi-modal Information for Robust Light Field Depth Estimation
Yongri Piao, Xinxin Ji, Miao Zhang, Yukun Zhang
http://arxiv.org/abs/2104.05971v1
• [cs.CV]Lite-HRNet: A Lightweight High-Resolution Network
Changqian Yu, Bin Xiao, Changxin Gao, Lu Yuan, Lei Zhang, Nong Sang, Jingdong Wang
http://arxiv.org/abs/2104.06403v1
• [cs.CV]Localization-Based Tracking
Derek Gloudemans, Daniel B. Work
http://arxiv.org/abs/2104.05823v1
• [cs.CV]MESD: Exploring Optical Flow Assessment on Edge of Motion Objects with Motion Edge Structure Difference
Bin Liao, Jinlong Hu
http://arxiv.org/abs/2104.05916v1
• [cs.CV]Mixed supervision for surface-defect detection: from weakly to fully supervised learning
Jakob Božič, Domen Tabernik, Danijel Skočaj
http://arxiv.org/abs/2104.06064v1
• [cs.CV]Multi-View Image-to-Image Translation Supervised by 3D Pose
Idit Diamant, Oranit Dror, Hai Victor Habi, Arnon Netzer
http://arxiv.org/abs/2104.05779v1
• [cs.CV]NewsCLIPpings: Automatic Generation of Out-of-Context Multimodal Media
Grace Luo, Trevor Darrell, Anna Rohrbach
http://arxiv.org/abs/2104.05893v1
• [cs.CV]OCM3D: Object-Centric Monocular 3D Object Detection
Liang Peng, Fei Liu, Senbo Yan, Xiaofei He, Deng Cai
http://arxiv.org/abs/2104.06041v1
• [cs.CV]Object-Centric Representation Learning for Video Question Answering
Long Hoang Dang, Thao Minh Le, Vuong Le, Truyen Tran
http://arxiv.org/abs/2104.05166v2
• [cs.CV]PHI-MVS: Plane Hypothesis Inference Multi-view Stereo for Large-Scale Scene Reconstruction
Shang Sun, Yunan Zheng, Xuelei Shi, Zhenyu Xu, Yiguang Liu
http://arxiv.org/abs/2104.06165v1
• [cs.CV]Pointly-Supervised Instance Segmentation
Bowen Cheng, Omkar Parkhi, Alexander Kirillov
http://arxiv.org/abs/2104.06404v1
• [cs.CV]SPARK: SPAcecraft Recognition leveraging Knowledge of Space Environment
Mohamed Adel Musallam, Kassem Al Ismaeil, Oyebade Oyedotun, Marcos Damian Perez, Michel Poucet, Djamila Aouada
http://arxiv.org/abs/2104.05978v1
• [cs.CV]SRR-Net: A Super-Resolution-Involved Reconstruction Method for High Resolution MR Imaging
Wenqi Huang, Sen Jia, Ziwen Ke, Zhuo-Xu Cui, Jing Cheng, Yanjie Zhu, Dong Liang
http://arxiv.org/abs/2104.05901v1
• [cs.CV]Self-supervised object detection from audio-visual correspondence
Triantafyllos Afouras, Yuki M. Asano, Francois Fagan, Andrea Vedaldi, Florian Metze
http://arxiv.org/abs/2104.06401v1
• [cs.CV]Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalization
Daiqing Li, Junlin Yang, Karsten Kreis, Antonio Torralba, Sanja Fidler
http://arxiv.org/abs/2104.05833v1
• [cs.CV]Shape and Material Capture at Home
Daniel Lichy, Jiaye Wu, Soumyadip Sengupta, David W. Jacobs
http://arxiv.org/abs/2104.06397v1
• [cs.CV]Spatially Varying Label Smoothing: Capturing Uncertainty from Expert Annotations
Mobarakol Islam, Ben Glocker
http://arxiv.org/abs/2104.05788v1
• [cs.CV]StereoPIFu: Depth Aware Clothed Human Digitization via Stereo Vision
Yang Hong, Juyong Zhang, Boyi Jiang, Yudong Guo, Ligang Liu, Hujun Bao
http://arxiv.org/abs/2104.05289v2
• [cs.CV]Towards Extremely Compact RNNs for Video Recognition with Fully Decomposed Hierarchical Tucker Structure
Miao Yin, Siyu Liao, Xiao-Yang Liu, Xiaodong Wang, Bo Yuan
http://arxiv.org/abs/2104.05758v1
• [cs.CV]Towards Fast and Accurate Real-World Depth Super-Resolution: Benchmark Dataset and Baseline
Lingzhi He, Hongguang Zhu, Feng Li, Huihui Bai, Runmin Cong, Chunjie Zhang, Chunyu Lin, Meiqin Liu, Yao Zhao
http://arxiv.org/abs/2104.06174v1
• [cs.CV]UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-identification
Daniel Organisciak, Brian K. S. Isaac-Medina, Matthew Poyser, Shanfeng Hu, Toby P. Breckon, Hubert P. H. Shum
http://arxiv.org/abs/2104.06219v1
• [cs.CV]VR3Dense: Voxel Representation Learning for 3D Object Detection and Monocular Dense Depth Reconstruction
Shubham Shrivastava
http://arxiv.org/abs/2104.05932v1
• [cs.CV]VariTex: Variational Neural Face Textures
Marcel C. Bühler, Abhimitra Meka, Gengyan Li, Thabo Beeler, Otmar Hilliges
http://arxiv.org/abs/2104.05988v1
• [cs.CV]Very Lightweight Photo Retouching Network with Conditional Sequential Modulation
Yihao Liu, Jingwen He, Xiangyu Chen, Zhengwen Zhang, Hengyuan Zhao, Chao Dong, Yu Qiao
http://arxiv.org/abs/2104.06279v1
• [cs.CV]View-Guided Point Cloud Completion
Xuancheng Zhang, Yutong Feng, Siqi Li, Changqing Zou, Hai Wan, Xibin Zhao, Yandong Guo, Yue Gao
http://arxiv.org/abs/2104.05666v2
• [cs.CV]Visual Goal-Step Inference using wikiHow
Yue Yang, Artemis Panagopoulou, Qing Lyu, Li Zhang, Mark Yatskar, Chris Callison-Burch
http://arxiv.org/abs/2104.05845v1
• [cs.CY]The AppChk Crowd-Sourcing Platform: Which third parties are iOS apps talking to?
Oleg Geier, Dominik Herrmann
http://arxiv.org/abs/2104.06167v1
• [cs.CY]What’s Your Value of Travel Time? Collecting Traveler-Centered Mobility Data via Crowdsourcing
Cristian Consonni, Silvia Basile, Matteo Manca, Ludovico Boratto, André Freitas, Tatiana Kovacikova, Ghadir Pourhashem, Yannick Cornet
http://arxiv.org/abs/2104.05809v1
• [cs.DC]Communication Efficient Federated Learning with Adaptive Quantization
Yuzhu Mao, Zihao Zhao, Guangfeng Yan, Yang Liu, Tian Lan, Linqi Song, Wenbo Ding
http://arxiv.org/abs/2104.06023v1
• [cs.DC]High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models
Dheevatsa Mudigere, Yuchen Hao, Jianyu Huang, Andrew Tulloch, Srinivas Sridharan, Xing Liu, Mustafa Ozdal, Jade Nie, Jongsoo Park, Liang Luo, Jie Amy Yang, Leon Gao, Dmytro Ivchenko, Aarti Basant, Yuxi Hu, Jiyan Yang, Ehsan K. Ardestani, Xiaodong Wang, Rakesh Komuravelli, Ching-Hsiang Chu, Serhat Yilmaz, Huayu Li, Jiyuan Qian, Zhuobo Feng, Yinbin Ma, Junjie Yang, Ellie Wen, Hong Li, Lin Yang, Chonglin Sun, Whitney Zhao, Krishna Dhulipala, KR Kishore, Tyler Graf, Assaf Eisenman, Kiran Kumar Matam, Adi Gangidi, Pallab Bhattacharya, Guoqiang Jerry Chen, Manoj Krishnan, Krishnakumar Nair, Petr Lapukhov, Maxim Naumov, Lin Qiao, Mikhail Smelyanskiy, Bill Jia, Vijay Rao
http://arxiv.org/abs/2104.05158v2
• [cs.DC]Optimal Data Placement for Data-Sharing Scientific Workflows in Heterogeneous Edge-Cloud Computing Environments
Xin Du, Songtao Tang, Zhihui Lu, Keke Gai, Jie Wu, Patrick C. K. Hung
http://arxiv.org/abs/2104.06274v1
• [cs.DC]The Programming of Deep Learning Accelerators as a Constraint Satisfaction Problem
Dennis Rieber, Axel Acosta, Holger Fröning
http://arxiv.org/abs/2104.04731v2
• [cs.GR]ShapeMOD: Macro Operation Discovery for 3D Shape Programs
R. Kenny Jones, David Charatan, Paul Guerrero, Niloy J. Mitra, Daniel Ritchie
http://arxiv.org/abs/2104.06392v1
• [cs.IR]An Adversarial Imitation Click Model for Information Retrieval
Xinyi Dai, Jianghao Lin, Weinan Zhang, Shuai Li, Weiwen Liu, Ruiming Tang, Xiuqiang He, Jianye Hao, Jun Wang, Yong Yu
http://arxiv.org/abs/2104.06077v1
• [cs.IR]Generating Code with the Help of Retrieved Template Functions and Stack Overflow Answers
Dawn Drain, Changran Hu, Chen Wu, Mikhail Breslav, Neel Sundaresan
http://arxiv.org/abs/2104.05310v2
• [cs.IR]On the instability of embeddings for recommender systems: the case of Matrix Factorization
Giovanni Gabbolini, Edoardo D’Amico, Cesare Bernardis, Paolo Cremonesi
http://arxiv.org/abs/2104.05796v1
• [cs.IT]Joint Optimization of Preamble Selection and Access Barring for MTC with Correlated Device Activities
Wang Liu, Ying Cui, Lianghui Ding, Jun Sun, Yangyang Liu, Yang Li, Li Zhang
http://arxiv.org/abs/2104.05977v1
• [cs.IT]Large-scale IRS-aided MIMO over Double-scattering Channel: An Asymptotic Approach
Xin Zhang, Xianghao Yu, S. H. Song, Khaled B. Letaief
http://arxiv.org/abs/2104.06125v1
• [cs.IT]List Message Passing Decoding of Non-binary Low-Density Parity-Check Codes
Emna Ben Yacoub
http://arxiv.org/abs/2104.06328v1
• [cs.IT]No-Pain No-Gain: DRL Assisted Optimization in Energy-Constrained CR-NOMA Networks
Zhiguo Ding, Robert Schober, H. Vincent Poor
http://arxiv.org/abs/2104.06007v1
• [cs.IT]On Minimax Detection of Gaussian Stochastic Sequences and Gaussian Stationary Signals
M. V. Burnashev
http://arxiv.org/abs/2104.06355v1
• [cs.IT]On the efficiency of polar-like decoding for symmetric codes
Kirill Ivanov, Rüdiger Urbanke
http://arxiv.org/abs/2104.06084v1
• [cs.IT]Probabilistic Accumulate-then-Transmit in Wireless-Powered Covert Communications
Yida Wang, Shihao Yan, Weiwei Yang, Caijun Zhong, Derrick Wing Kwan Ng
http://arxiv.org/abs/2104.06160v1
• [cs.IT]Secure Cognitive Radio Communication via Intelligent Reflecting Surface
Limeng Dong, Hui-Ming Wang, Haitao Xiao
http://arxiv.org/abs/2104.05012v1
• [cs.IT]Wireless Environment as a Service Enabled by Reconfigurable Intelligent Surfaces: The RISE-6G Perspective
Emilio Calvanese Strinati, George C. Alexandropoulos, Vincenzo Sciancalepore, Marco Di Renzo, Henk Wymeersch, Dinh-Thuy Phan-huy, Maurizio Crozzoli, Raffaele D’Errico, Elisabeth De Carvalho, Petar Popovski, Paolo Di Lorenzo, Luca Bastianelli, Mathieu Belouar, Julien Etienne Mascolo, Gabriele Gradoni, Sendy Phang, Geoffroy Lerosey, Benoît Denis
http://arxiv.org/abs/2104.06265v1
• [cs.LG]-CLUE: Diverse Sets of Explanations for Uncertainty Estimates
Dan Ley, Umang Bhatt, Adrian Weller
http://arxiv.org/abs/2104.06323v1
• [cs.LG]1-bit LAMB: Communication Efficient Large-Scale Large-Batch Training with LAMB’s Convergence Speed
Conglong Li, Ammar Ahmad Awan, Hanlin Tang, Samyam Rajbhandari, Yuxiong He
http://arxiv.org/abs/2104.06069v1
• [cs.LG]A Recipe for Global Convergence Guarantee in Deep Neural Networks
Kenji Kawaguchi, Qingyun Sun
http://arxiv.org/abs/2104.05785v1
• [cs.LG]A Tale of Two Lexica Testing Computational Hypotheses with Deep Convolutional Neural Networks
Enes Avcu, Olivia Newman, David Gow
http://arxiv.org/abs/2104.06271v1
• [cs.LG]Active learning for medical code assignment
Martha Dais Ferreira, Michal Malyska, Nicola Sahar, Riccardo Miotto, Fernando Paulovich, Evangelos Milios
http://arxiv.org/abs/2104.05741v1
• [cs.LG]Adversarial autoencoders and adversarial LSTM for improved forecasts of urban air pollution simulations
César Quilodrán-Casas, Rossella Arcucci, Laetitia Mottet, Yike Guo, Christopher Pain
http://arxiv.org/abs/2104.06297v1
• [cs.LG]Censored Semi-Bandits for Resource Allocation
Arun Verma, Manjesh K. Hanawal, Arun Rajkumar, Raman Sankaran
http://arxiv.org/abs/2104.05781v1
• [cs.LG]Conclusive Local Interpretation Rules for Random Forests
Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas
http://arxiv.org/abs/2104.06040v1
• [cs.LG]Contextual HyperNetworks for Novel Feature Adaptation
*Angus Lamb, Evgeny Saveliev, Yingzhen Li, Sebastian Tschiatschek, Camilla Longden, Simon Woodhead, José Miguel Hernández-Lobato, Richard E. Turner, bef
Pashmina Cameron, Cheng Zhang*
http://arxiv.org/abs/2104.05860v1
• [cs.LG]Data-Driven Reinforcement Learning for Virtual Character Animation Control
Vihanga Gamage, Cathy Ennis, Robert Ross
http://arxiv.org/abs/2104.06358v1
• [cs.LG]Distilling Wikipedia mathematical knowledge into neural network models
Joanne T. Kim, Mikel Landajuela Larma, Brenden K. Petersen
http://arxiv.org/abs/2104.05930v1
• [cs.LG]Does My Representation Capture X? Probe-Ably
Deborah Ferreira, Julia Rozanova, Mokanarangan Thayaparan, Marco Valentino, André Freitas
http://arxiv.org/abs/2104.05807v1
• [cs.LG]Efficient Optimal Transport Algorithm by Accelerated Gradient descent
Dongsheng An, Na Lei, Xianfeng Gu
http://arxiv.org/abs/2104.05802v1
• [cs.LG]Enhancing User’ s Income Estimation with Super-App Alternative Data
Gabriel Suarez, Juan Raful, Maria A. Luque, Carlos F. Valencia, Alejandro Correa-Bahnsen
http://arxiv.org/abs/2104.05831v1
• [cs.LG]Finite Volume Neural Network: Modeling Subsurface Contaminant Transport
Timothy Praditia, Matthias Karlbauer, Sebastian Otte, Sergey Oladyshkin, Martin V. Butz, Wolfgang Nowak
http://arxiv.org/abs/2104.06010v1
• [cs.LG]GSA-Forecaster: Forecasting Graph-Based Time-Dependent Data with Graph Sequence Attention
Yang Li, Di Wang, José M. F. Moura
http://arxiv.org/abs/2104.05914v1
• [cs.LG]Hierarchical Adaptive Pooling by Capturing High-order Dependency for Graph Representation Learning
Ning Liu, Songlei Jian, Dongsheng Li, Yiming Zhang, Zhiquan Lai, Hongzuo Xu
http://arxiv.org/abs/2104.05960v1
• [cs.LG]Learning and Planning in Complex Action Spaces
Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Mohammadamin Barekatain, Simon Schmitt, David Silver
http://arxiv.org/abs/2104.06303v1
• [cs.LG]Learning to recover orientations from projections in single-particle cryo-EM
Jelena Banjac, Laurène Donati, Michaël Defferrard
http://arxiv.org/abs/2104.06237v1
• [cs.LG]LioNets: A Neural-Specific Local Interpretation Technique Exploiting Penultimate Layer Information
Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas
http://arxiv.org/abs/2104.06057v1
• [cs.LG]Meta-Regularization: An Approach to Adaptive Choice of the Learning Rate in Gradient Descent
Guangzeng Xie, Hao Jin, Dachao Lin, Zhihua Zhang
s/2104.05447v1](http://arxiv.org/abs/762
s/2104.05447v1)
• [cs.LG]Mitigating Adversarial Attack for Compute-in-Memory Accelerator Utilizing On-chip Finetune
Shanshi Huang, Hongwu Jiang, Shimeng Yu
http://arxiv.org/abs/2104.06377v1
• [cs.LG]Model Learning with Personalized Interpretability Estimation (ML-PIE)
Marco Virgolin, Andrea De Lorenzo, Francesca Randone, Eric Medvet, Mattias Wahde
http://arxiv.org/abs/2104.06060v1
• [cs.LG]Muesli: Combining Improvements in Policy Optimization
Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado van Hasselt
http://arxiv.org/abs/2104.06159v1
• [cs.LG]Multivariate Deep Evidential Regression
Nis Meinert
http://arxiv.org/abs/2104.06135v1
• [cs.LG]Neural Network for Weighted Signal Temporal Logic
Ruixuan Yan, Agung Julius
http://arxiv.org/abs/2104.05435v1
• [cs.LG]Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx
Kin G. Olivares, Cristian Challu, Grzegorz Marcjasz, Rafał Weron, Artur Dubrawski
http://arxiv.org/abs/2104.05522v2
• [cs.LG]Neuro-Symbolic VQA: A review from the perspective of AGI desiderata
Ian Berlot-Attwell
http://arxiv.org/abs/2104.06365v1
• [cs.LG]On the validity of kernel approximations for orthogonally-initialized neural networks
James Martens
http://arxiv.org/abs/2104.05878v1
• [cs.LG]**One-class Autoencoder Approach for Optimal Elect
1362
rode Set-up Identification in Wearable EEG Event Monitoring**
Laura M. Ferrari, Guy Abi Hanna, Paolo Volpe, Esma Ismailova, François Bremond, Maria A. Zuluaga
http://arxiv.org/abs/2104.04546v2
• [cs.LG]Online and Offline Reinforcement Learning by Planning with a Learned Model
Julian Schrittwieser, Thomas Hubert, Amol Mandhane, Mohammadamin Barekatain, Ioannis Antonoglou, David Silver
http://arxiv.org/abs/2104.06294v1
• [cs.LG]Optimizing the Long-Term Average Reward for Continuing MDPs: A Technical Report
Chao Xu, Yiping Xie, Xijun Wang, Howard H. Yang, Dusit Niyato, Tony Q. S. Quek
http://arxiv.org/abs/2104.06139v1
• [cs.LG]Podracer architectures for scalable Reinforcement Learning
Matteo Hessel, Manuel Kroiss, Aidan Clark, Iurii Kemaev, John Quan, Thomas Keck, Fabio Viola, Hado van Hasselt
http://arxiv.org/abs/2104.06272v1
• [cs.LG]Practical Defences Against Model Inversion Attacks for Split Neural Networks
Tom Titcombe, Adam J. Hall, Pavlos Papadopoulos, Daniele Romanini
http://arxiv.org/abs/2104.05743v1
• [cs.LG]Probing Negative Sampling Strategies to Learn GraphRepresentations via Unsupervised Contrastive Learning
Shiyi Chen, Ziao Wang, Xinni Zhang, Xiaofeng Zhang, Dan Peng
http://arxiv.org/abs/2104.06317v1
• [cs.LG]Real-time Forecast Models for TBM Load Parameters Based on Machine Learning Methods
Xianjie Gao, Xueguan Song, Maolin Shi, Chao Zhang, Hongwei Zhang
http://arxiv.org/abs/2104.06353v1
• [cs.LG]Recurrent Equilibrium Networks: Unconstrained Learning of Stable and Robust Dynamical Models
Max Revay, Ruigang Wang, Ian R. Manchester
http://arxiv.org/abs/2104.05942v1
• [cs.LG]Revisiting Bayesian Autoencoders with MCMC
Rohitash Chandra, Mahir Jain, Manavendra Maharana, Pavel N. Krivitsky
http://arxiv.org/abs/2104.05915v1
• [cs.LG]Reward Shaping with Dynamic Trajectory Aggregation
Takato Okudo, Seiji Yamada
http://arxiv.org/abs/2104.06163v1
• [cs.LG]Sample-based and Feature-based Federated Learning via Mini-batch SSCA
Chencheng Ye, Ying Cui
http://arxiv.org/abs/2104.06011v1
• [cs.LG]Semiring Primitives for Sparse Neighborhood Methods on the GPU
Corey J. Nolet, Divye Gala, Edward Raff, Joe Eaton, Brad Rees, John Zedlewski, Tim Oates
http://arxiv.org/abs/2104.06357v1
• [cs.LG]Sequential Ski Rental Problem
Anant Shah, Arun Rajkumar
http://arxiv.org/abs/2104.06050v1
• [cs.LG]Simpler Certified Radius Maximization by Propagating Covariances
Xingjian Zhen, Rudrasis Chakraborty, Vikas Singh
http://arxiv.org/abs/2104.05888v1
• [cs.LG]The Impact of Activation Sparsity on Overfitting in Convolutional Neural Networks
Karim Huesmann, Luis Garcia Rodriguez, Lars Linsen, Benjamin Risse
http://arxiv.org/abs/2104.06153v1
• [cs.LG]The Many Faces of 1-Lipschitz Neural Networks
Louis Béthune, Alberto González-Sanz, Franck Mamalet, Mathieu Serrurier
http://arxiv.org/abs/2104.05097v2
• [cs.LG]Thief, Beware of What Get You There: Towards Understanding Model Extraction Attack
Xinyi Zhang, Chengfang Fang, Jie Shi
http://arxiv.org/abs/2104.05921v1
• [cs.LG]Tracking translation invariance in CNNs
Johannes C. Myburgh, Coenraad Mouton, Marelie H. Davel
http://arxiv.org/abs/2104.05997v1
• [cs.LG]Which Hyperparameters to Optimise? An Investigation of Evoluationary Hyperaprameter Optimisation in Graph Neural Network For Molecular Property Prediction
Yingfang Yuan, Wenjun Wang, Wei Pang
http://arxiv.org/abs/2104.06046v1
• [cs.MM]“Subverting the Jewtocracy”: Online Antisemitism Detection Using Multimodal Deep Learning
Mohit Chandra, Dheeraj Pailla, Himanshu Bhatia, Aadilmehdi Sanchawala, Manish Gupta, Manish Shrivastava, Ponnurangam Kumaraguru
http://arxiv.org/abs/2104.05947v1
• [cs.NE]A coevolutionary approach to deep multi-agent reinforcement learning
Daan Klijn, A. E. Eiben
http://arxiv.org/abs/2104.05610v2
• [cs.NE]An Adaptive Synaptic Array using Fowler-Nordheim Dynamic Analog Memory
Darshit Mehta, Kenji Aono, Shantanu Chakrabartty
http://arxiv.org/abs/2104.05926v1
• [cs.NE]Multiple regression techniques for modeling dates of first performances of Shakespeare-era plays
Pablo Moscato, Hugh Craig, Gabriel Egan, Mohammad Nazmul Haque, Kevin Huang, Julia Sloan, Jon Corrales de Oliveira
http://arxiv.org/abs/2104.05929v1
• [cs.PF]NekRS, a GPU-Accelerated Spectral Element Navier-Stokes Solver
Paul Fischer, Stefan Kerkemeier, Misun Min, Yu-Hsiang Lan, Malachi Phillips, Thilina Rathnayake, Elia Merzari, Ananias Tomboulides, Ali Karakus, Noel Chalmers, Tim Warburton
http://arxiv.org/abs/2104.05829v1
• [cs.RO]Cobbler Stick With Your Reads: People’s Perceptions of Gendered Robots Performing Gender Stereotypical Tasks
Sven Y. Neuteboom, Maartje M. A. de Graaf
http://arxiv.org/abs/2104.06127v1
• [cs.RO]Deep Deterministic Path Following
Georg Hess, William Ljungbergh
http://arxiv.org/abs/2104.06014v1
• [cs.RO]Generative Design of NU’s Husky Carbon, A Morpho-Functional, Legged Robot
Alireza Ramezani, Pravin Dangol, Eric Sihite, Andrew Lessieur, Peter Kelly
http://arxiv.org/abs/2104.05834v1
• [cs.RO]Group Surfing: A Pedestrian-Based Approach to Sidewalk Robot Navigation
Yuqing Du, Nicholas J. Hetherington, Chu Lip Oon, Wesley P. Chan, Camilo Perez Quintero, Elizabeth Croft, H. F. Machiel Van der Loos, .
http://arxiv.org/abs/2104.05933v1
• [cs.RO]Inertial Collaborative Localisation for Autonomous Vehicles using a Minimum Energy Filter
Jack Henderson, Mohammad Zamani, Robert Mahony, Jochen Trumpf
http://arxiv.org/abs/2104.05897v1
• [cs.RO]Online Recognition of Actions Involving Objects
Zahra Gharaee, Peter Gärdenfors, Magnus Johnsson
http://arxiv.org/abs/2104.06070v1
• [cs.RO]Optimal Multi-Manipulator Arm Placement for Maximal Dexterity during Robotics Surgery
James Di, Mingwei Xu, Nikhil Das, Michael C. Yip
http://arxiv.org/abs/2104.06348v1
• [cs.RO]RECON: Rapid Exploration for Open-World Navigation with Latent Goal Models
Dhruv Shah, Benjamin Eysenbach, Gregory Kahn, Nicholas Rhinehart, Sergey Levine
http://arxiv.org/abs/2104.05859v1
• [cs.RO]Terrain assessment for precision agriculture using vehicle dynamic modelling
Giulio Reina, Annalisa Milella, Rocco Galati
http://arxiv.org/abs/2104.06326v1
• [cs.RO]Towards a Next Generation Computing Paradigm: Approximate Computing in Robotics Systems and Environment-Experimentation, Case Study and Practical Implications
Hrishav Bakul Barua
http://arxiv.org/abs/2104.05773v1
• [cs.RO]Trimanipulation: Evaluation of human performance in a 3-handed coordination task
Yanpei Huang, Jonathan Eden, Ekaterina Ivanova, Soo Jay Phee, Etienne Burdet
http://arxiv.org/abs/2104.06080v1
• [cs.RO]What is the appropriate speed for an autonomous vehicle? Designing a Pedestrian Aware Contextual Speed Controller
Daniel Jiang, Stewart Worrall, Mao Shan
http://arxiv.org/abs/2104.06147v1
• [cs.SD]NoiseVC: Towards High Quality Zero-Shot Voice Conversion
Shijun Wang, Damian Borth
http://arxiv.org/abs/2104.06074v1
• [cs.SD]Visually Informed Binaural Audio Generation without Binaural Audios
Xudong Xu, Hang Zhou, Ziwei Liu, Bo Dai, Xiaogang Wang, Dahua Lin
http://arxiv.org/abs/2104.06162v1
• [cs.SE]Detecting Operational Adversarial Examples for Reliable Deep Learning
Xingyu Zhao, Wei Huang, Sven Schewe, Yi Dong, Xiaowei Huang
http://arxiv.org/abs/2104.06015v1
• [cs.SE]Evaluating Pre-Trained Models for User Feedback Analysis in Software Engineering: A Study on Classification of App-Reviews
Mohammad Abdul Hadi, Fatemeh H. Fard
http://arxiv.org/abs/2104.05861v1
• [cs.SI]Clustering of temporal nodes profiles in dynamic networks of contacts
Mehdi Djellabi, Bertrand Jouve
http://arxiv.org/abs/2104.05982v1
• [cs.SI]Media Cloud: Massive Open Source Collection of Global News on the Open Web
Hal Roberts, Rahul Bhargava, Linas Valiukas, Dennis Jen, Momin M. Malik, Momin M. Malik, Emily Ndulue, Aashka Dave, Justin Clark, Bruce Etling, Rob Faris, Anushka Shah, Jasmin Rubinovitz, Alexis Hope, Catherine D’Ignazio, Fernando Bermejo, Yochai Benkler, Ethan Zuckerman
http://arxiv.org/abs/2104.03702v2
• [cs.SI]On Representation Learning for Scientific News Articles Using Heterogeneous Knowledge Graphs
Angelika Romanou, Panayiotis Smeros, Karl Aberer
http://arxiv.org/abs/2104.05866v1
• [cs.SI]Relevance-Aware Anomalous Users Detection in Social Network
Yangyang Li, Jingyi Wang, Shaoning Li, Shulong He, Yinhao Cao, Xiong Li, Jun Shi, Yangchao Yang, Yifeng Liu
http://arxiv.org/abs/2104.06095v1
• [econ.GN]Analysis of the tradeoff between health and economic impacts of the Covid-19 epidemic
Samson Lasaulce, Chao Zhang, Vineeth Varma, Irinel Constantin Morarescu
http://arxiv.org/abs/2104.06169v1
• [eess.IV]A State-of-the-art Survey of Artificial Neural Networks for Whole-slide Image Analysis:from Popular Convolutional Neural Networks to Potential Visual Transformers
Chen Li, Xintong Li, Xiaoyan Li, Md Mamunur Rahaman, Xiaoqi Li, Jian Wu, Yudong Yao, Marcin Grzegorzek
http://arxiv.org/abs/2104.06243v1
• [eess.IV]COVID-19 detection using chest X-rays: is lung segmentation important for generalization?
Pedro R. A. S. Bassi, Romis Attux
http://arxiv.org/abs/2104.06176v1
• [eess.IV]**Efficient Space-time Video Super Resolution using Low-Resolution Flow and Mas
787
k Upsampling**
Saikat Dutta, Nisarg A. Shah, Anurag Mittal
http://arxiv.org/abs/2104.05778v1
• [eess.IV]Fibro-CoSANet: Pulmonary Fibrosis Prognosis Prediction using a Convolutional Self Attention Network
Zabir Al Nazi, Fazla Rabbi Mashrur, Md Amirul Islam, Shumit Saha
http://arxiv.org/abs/2104.05889v1
• [eess.IV]Latent Correlation Representation Learning for Brain Tumor Segmentation with Missing MRI Modalities
Tongxue Zhou, St\ephane Canu, Pierre Vera, Su Ruan
http://arxiv.org/abs/2104.06231v1
• [eess.IV]Spatiotemporal Entropy Model is All You Need for Learned Video Compression
Zhenhong Sun, Zhiyu Tan, Xiuyu Sun, Fangyi Zhang, Dongyang Li, Yichen Qian, Hao Li
http://arxiv.org/abs/2104.06083v1
• [eess.IV]Unifying domain adaptation and self-supervised learning for CXR segmentation via AdaIN-based knowledge distillation
Yujin Oh, Jong Chul Ye
http://arxiv.org/abs/2104.05892v1
• [eess.SP]Jittering Effects Analysis and Beam Training Design for UAV Millimeter Wave Communications
Wei Wang, Wei Zhang
http://arxiv.org/abs/2104.05872v1
• [eess.SP]Joint Secure Design of Downlink and D2D Cooperation Strategies for Multi-User Systems
Seok-Hwan Park, Xianglan Jin
http://arxiv.org/abs/2104.06003v1
• [eess.SP]Orthogonal Time Sequency Multiplexing Modulation: Analysis and Low-Complexity Receiver Design
Tharaj Thaj, Emanuele Viterbo, Yi Hong
http://arxiv.org/abs/2104.05939v1
• [eess.SY]Bi-level Off-policy Reinforcement Learning for Volt/VAR Control Involving Continuous and Discrete Devices
Haotian Liu, Wenchuan Wu
http://arxiv.org/abs/2104.05902v1
• [eess.SY]Evidence-based Prescriptive Analytics, CAUSAL Digital Twin and a Learning Estimation Algorithm
PG Madhavan
http://arxiv.org/abs/2104.05828v1
• [math.OC]On the Linear Ordering Problem and the Rankability of Data
Thomas R. Cameron, Sebastian Charmot, Jonad Pulaj
http://arxiv.org/abs/2104.05816v1
• [math.OC]Optimization of Reconfigurable Intelligent Surfaces with Electromagnetic Field Exposure Constraints
Alessio Zappone, Marco Di Renzo
http://arxiv.org/abs/2104.06283v1
• [math.ST]Bahadur efficiency of the maximum likelihood estimator and one-step estimator for quasi-arithmetic means of the Cauchy distribution
Yuichi Akaoka, Kazuki Okamura, Yoshiki Otobe
http://arxiv.org/abs/2104.06112v1
• [math.ST]Characterizations of the maximum likelihood estimator of the Cauchy distribution
Kazuki Okamura, Yoshiki Otobe
http://arxiv.org/abs/2104.06130v1
• [math.ST]Confidence disc for Cauchy distributions
Yuichi Akaoka, Kazuki Okamura, Yoshiki Otobe
http://arxiv.org/abs/2104.06124v1
• [math.ST]Limit theorems for quasi-arithmetic means of random variables with applications to point estimations for the Cauchy distribution
Yuichi Akaoka, Kazuki Okamura, Yoshiki Otobe
http://arxiv.org/abs/2104.06110v1
• [physics.geo-ph]Learning by example: fast reliability-aware seismic imaging with normalizing flows
Ali Siahkoohi, Felix J. Herrmann
http://arxiv.org/abs/2104.06255v1
• [physics.geo-ph]Predicting the Accuracy of Early-est Earthquake Magnitude Estimates with an LSTM Neural Network: A Preliminary Analysis
Massimo Nazaria
http://arxiv.org/abs/2104.05712v1
• [physics.soc-ph]The world-wide waste web
Johann H. Martínez, Ernesto Estrada
http://arxiv.org/abs/2104.05711v1
• [q-bio.NC]Temporal EigenPAC for dyslexia diagnosis
Nicolás Gallego-Molina, Marco Formoso, Andrés Ortiz, Francisco J. Martínez-Murcia, Juan L. Luque
http://arxiv.org/abs/2104.05991v1
• [q-bio.QM]Bayesian Optimisation for a Biologically Inspired Population Neural Network
Mahak Kothari, Swapna Sasi, Jun Chen, Elham Zareian, Basabdatta Sen Bhattacharya
http://arxiv.org/abs/2104.05989v1
• [q-fin.ST]Loss of structural balance in stock markets
E. Ferreira, S. Orbe, J. Ascorbebeitia, B. Álvarez Pereira, E. Estrada
http://arxiv.org/abs/2104.06254v1
• [quant-ph]Equivalence of quantum barren plateaus to cost concentration and narrow gorges
Andrew Arrasmith, Zoë Holmes, M. Cerezo, Patrick J. Coles
http://arxiv.org/abs/2104.05868v1
• [stat.AP]A review and evaluation of secondary school accountability in England: Statistical strengths, weaknesses, and challenges for ‘Progress 8’
Lucy Prior, John Jerrim, Dave Thomson, George Leckie
http://arxiv.org/abs/2104.06299v1
• [stat.AP]Inferring Risks of Coronavirus Transmission from Community Household Data
Thomas House, Lorenzo Pellis, Koen B. Pouwels, Sebastian Bacon, Arturas Eidukas, Kaveh Jahanshahi, Rosalind M. Eggo, A. Sarah Walker
http://arxiv.org/abs/2104.04605v2
• [stat.CO]The computational asymptotics of Gaussian variational inference
Zuheng Xu, Trevor Campbell
http://arxiv.org/abs/2104.05886v1
• [stat.ME]A spatial modeling framework for monitoring surveys with different sampling protocols with a case study for bird populations in mid-Scandinavia
Jorge Sicacha-Parada, Diego Pavon-Jordan, Ingelin Steinsland, Roel May, Bård Stokke, Ingar Jostein Øien
http://arxiv.org/abs/2104.05751v1
• [stat.ME]Center-specific causal inference with multicenter trials: reinterpreting trial evidence in the context of each participating center
Sarah E. Robertson, Jon A. Steingrimsson, Nina R. Joyce, Elizabeth A. Stuart, Issa J. Dahabreh
http://arxiv.org/abs/2104.05905v1
• [stat.ME]Deconfounding Scores: Feature Representations for Causal Effect Estimation with Weak Overlap
Alexander D’Amour, Alexander Franks
http://arxiv.org/abs/2104.05762v1
• [stat.ME]Optimal scaling of random walk Metropolis algorithms using Bayesian large-sample asymptotics
Sebastian M Schmon, Philippe Gagnon
http://arxiv.org/abs/2104.06384v1
• [stat.ME]Optimal transport couplings of Gibbs samplers on partitions for unbiased estimation
Brian L. Trippe, Tin D. Nguyen, Tamara Broderick
http://arxiv.org/abs/2104.04514v2
• [stat.ME]Poisson Network Autoregression
Mirko Armillotta, Konstantinos Fokianos
http://arxiv.org/abs/2104.06296v1
• [stat.ML]COVID-19 case data for Italy stratified by age class
Giuseppe Calafiore, Giulia Fracastoro
http://arxiv.org/abs/2104.06199v1
• [stat.ML]Deep imagination is a close to optimal policy for planning in large decision trees under limited resources
Ruben Moreno-Bote, Chiara Mastrogiuseppe
http://arxiv.org/abs/2104.06339v1
• [stat.ML]Thresholded Graphical Lasso Adjusts for Latent Variables: Application to Functional Neural Connectivity
Minjie Wang, Genevera I. Allen
http://arxiv.org/abs/2104.06389v1
• [stat.ML]Towards Unbiased Random Features with LowerVariance For Stationary Indefinite Kernels
Qin Luo, Kun Fang, Jie Yang, Xiaolin Huang
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