astro-ph.GA - 星系天体物理学

    cs.AI - 人工智能 cs.CL - 计算与语言 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.ET - 新兴技术 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.SE - 软件工程 cs.SI - 社交网络与信息网络 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.AG - 代数几何 math.NA - 数值分析 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 physics.comp-ph - 计算物理学 physics.data-an - 数据分析、 统计和概率 physics.geo-ph - 地球物理学 physics.soc-ph - 物理学与社会 q-bio.PE - 人口与发展 q-bio.QM - 定量方法 q-fin.MF - 数学金融 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.GA]Evolutionary Map of the Universe (EMU):Compact radio sources in the SCORPIO field towards the Galactic plane
    • [cs.AI]A Commonsense Reasoning Framework for Explanatory Emotion Attribution, Generation and Re-classification
    • [cs.AI]Are We There Yet? Learning to Localize in Embodied Instruction Following
    • [cs.AI]Learn-n-Route: Learning implicit preferences for vehicle routing
    • [cs.AI]Multi-objective Conflict-based Search for Multi-agent Path Finding
    • [cs.AI]Neurocognitive Informatics Manifesto
    • [cs.AI]Optimizing Hospital Room Layout to Reduce the Risk of Patient Falls
    • [cs.AI]Stabilized Nested Rollout Policy Adaptation
    • [cs.CL]A Gamification of Japanese Dependency Parsing
    • [cs.CL]A Heuristic-driven Ensemble Framework for COVID-19 Fake News Detection
    • [cs.CL]AT-BERT: Adversarial Training BERT for Acronym Identification Winning Solution for SDU@AAAI-21
    • [cs.CL]Adaptive Prototypical Networks with Label Words and Joint Representation Learning for Few-Shot Relation Classification
    • [cs.CL]Automating the Compilation of Potential Core-Outcomes for Clinical Trials
    • [cs.CL]BERT & Family Eat Word Salad: Experiments with Text Understanding
    • [cs.CL]Combating Hostility: Covid-19 Fake News and Hostile Post Detection in Social Media
    • [cs.CL]Constraint 2021: Machine Learning Models for COVID-19 Fake News Detection Shared Task
    • [cs.CL]Context- and Sequence-Aware Convolutional Recurrent Encoder for Neural Machine Translation
    • [cs.CL]Detecting Hostile Posts using Relational Graph Convolutional Network
    • [cs.CL]Graph-of-Tweets: A Graph Merging Approach to Sub-event Identification
    • [cs.CL]Identification of COVID-19 related Fake News via Neural Stacking
    • [cs.CL]Improving Multi-hop Knowledge Base Question Answering by Learning Intermediate Supervision Signals
    • [cs.CL]Learning Better Sentence Representation with Syntax Information
    • [cs.CL]Leveraging Multilingual Transformers for Hate Speech Detection
    • [cs.CL]LightXML: Transformer with Dynamic Negative Sampling for High-Performance Extreme Multi-label Text Classification
    • [cs.CL]Misspelling Correction with Pre-trained Contextual Language Model
    • [cs.CL]Model Generalization on COVID-19 Fake News Detection
    • [cs.CL]Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain Detection
    • [cs.CL]Summaformers @ LaySumm 20, LongSumm 20
    • [cs.CL]Task Adaptive Pretraining of Transformers for Hostility Detection
    • [cs.CL]The Logic for a Mildly Context-Sensitive Fragment of the Lambek-Grishin Calculus
    • [cs.CL]Trankit: A Light-Weight Transformer-based Toolkit for Multilingual Natural Language Processing
    • [cs.CL]Unifying Relational Sentence Generation and Retrieval for Medical Image Report Composition
    • [cs.CV]A novel shape matching descriptor for real-time hand gesture recognition
    • [cs.CV]Active Fire Detection in Landsat-8 Imagery: a Large-Scale Dataset and a Deep-Learning Study
    • [cs.CV]Activity Recognition with Moving Cameras and Few Training Examples: Applications for Detection of Autism-Related Headbanging
    • [cs.CV]ArrowGAN : Learning to Generate Videos by Learning Arrow of Time
    • [cs.CV]CapsField: Light Field-based Face and Expression Recognition in the Wild using Capsule Routing
    • [cs.CV]Channel Boosting Feature Ensemble for Radar-based Object Detection
    • [cs.CV]Cognitive Visual Inspection Service for LCD Manufacturing Industry
    • [cs.CV]Colorectal Polyp Detection in Real-world Scenario: Design and Experiment Study
    • [cs.CV]Combining Neural Network Models for Blood Cell Classification
    • [cs.CV]Coronary Plaque Analysis for CT Angiography Clinical Research
    • [cs.CV]Cycle Generative Adversarial Networks Algorithm With Style Transfer For Image Generation
    • [cs.CV]Deep Adversarial Inconsistent Cognitive Sampling for Multi-view Progressive Subspace Clustering
    • [cs.CV]Deep Learning-based Face Super-resolution: A Survey
    • [cs.CV]Detecting, Localising and Classifying Polyps from Colonoscopy Videos using Deep Learning
    • [cs.CV]Entropy-Based Uncertainty Calibration for Generalized Zero-Shot Learning
    • [cs.CV]Exploring Adversarial Fake Images on Face Manifold
    • [cs.CV]Extracting Pasture Phenotype and Biomass Percentages using Weakly Supervised Multi-target Deep Learning on a Small Dataset
    • [cs.CV]FakeBuster: A DeepFakes Detection Tool for Video Conferencing Scenarios
    • [cs.CV]Heatmap-based Object Detection and Tracking with a Fully Convolutional Neural Network
    • [cs.CV]Horizontal-to-Vertical Video Conversion
    • [cs.CV]Identifying Human Edited Images using a CNN
    • [cs.CV]Investigating the Vision Transformer Model for Image Retrieval Tasks
    • [cs.CV]Learning Semantically Meaningful Features for Interpretable Classifications
    • [cs.CV]Learning from Weakly-labeled Web Videos via Exploring Sub-Concepts
    • [cs.CV]Learning to Segment Rigid Motions from Two Frames
    • [cs.CV]MAAS: Multi-modal Assignation for Active Speaker Detection
    • [cs.CV]Multi-Domain Image-to-Image Translation with Adaptive Inference Graph
    • [cs.CV]Neural Re-Rendering of Humans from a Single Image
    • [cs.CV]ORDNet: Capturing Omni-Range Dependencies for Scene Parsing
    • [cs.CV]Provably Approximated ICP
    • [cs.CV]Pushing the Envelope of Thin Crack Detection
    • [cs.CV]Remote Pulse Estimation in the Presence of Face Masks
    • [cs.CV]RepVGG: Making VGG-style ConvNets Great Again
    • [cs.CV]Semantic Segmentation of Remote Sensing Images with Sparse Annotations
    • [cs.CV]Spherical Transformer: Adapting Spherical Signal to ConvolutionalNetworks
    • [cs.CV]Target Detection and Segmentation in Circular-Scan Synthetic-Aperture-Sonar Images using Semi-Supervised Convolutional Encoder-Decoders
    • [cs.CV]The Diabetic Buddy: A Diet Regulator andTracking System for Diabetics
    • [cs.CV]The Gaze and Mouse Signal as additional Source for User Fingerprints in Browser Applications
    • [cs.CV]The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing
    • [cs.CV]Towards Real-World Blind Face Restoration with Generative Facial Prior
    • [cs.CV]Unchain the Search Space with Hierarchical Differentiable Architecture Search
    • [cs.CV]Unobtrusive Pain Monitoring in Older Adults with Dementia using Pairwise and Contrastive Training
    • [cs.CV]Using Crowdsourcing to Train Facial Emotion Machine Learning Models with Ambiguous Labels
    • [cs.CV]WDR FACE: The First Database for Studying Face Detection in Wide Dynamic Range
    • [cs.CV]WiCV 2020: The Seventh Women In Computer Vision Workshop
    • [cs.CY]A Review of Game-based Mobile E-Learning Applications
    • [cs.CY]Perspectives and Challenges in the Analysis of Prison Systems Data: A Systematic Mapping
    • [cs.CY]Representativeness in Statistics, Politics, and Machine Learning
    • [cs.DB]FlashP: An Analytical Pipeline for Real-time Forecasting of Time-Series Relational Data
    • [cs.DC]A Fault Tolerant Mechanism for Partitioning and Offloading Framework in Pervasive Environments
    • [cs.DC]Con-Pi: A Distributed Container-based Edge and Fog Computing Framework for Raspberry Pis
    • [cs.DC]Distributed Double Machine Learning with a Serverless Architecture
    • [cs.DC]Internet of Things (IoT) Application Model for Smart Farming
    • [cs.DC]Kuksa*: Self-Adaptive Microservices in Automotive Systems
    • [cs.DC]Running Time Analysis of Broadcast Consensus Protocols
    • [cs.DC]SDRBench: Scientific Data Reduction Benchmark for Lossy Compressors
    • [cs.DC]Strengthened Fault Tolerance in Byzantine Fault Tolerant Replication
    • [cs.ET]Quantum Generative Models for Small Molecule Drug Discovery
    • [cs.HC]Machine Learning Uncertainty as a Design Material: A Post-Phenomenological Inquiry
    • [cs.IR]An Unsupervised Normalization Algorithm for Noisy Text: A Case Study for Information Retrieval and Stance Detection
    • [cs.IR]Context-Aware Target Apps Selection and Recommendation for Enhancing Personal Mobile Assistants
    • [cs.IR]Disentangled Self-Attentive Neural Networks for Click-Through Rate Prediction
    • [cs.IR]Generate Natural Language Explanations for Recommendation
    • [cs.IR]Selection of Optimal Parameters in the Fast K-Word Proximity Search Based on Multi-component Key Indexes
    • [cs.IR]Towards Long-term Fairness in Recommendation
    • [cs.IR]Transfer Learning and Augmentation for Word Sense Disambiguation
    • [cs.IT]Cross Domain Iterative Detection for Orthogonal Time Frequency Space Modulation
    • [cs.IT]Delay Minimization in Sliced Multi-Cell Mobile Edge Computing (MEC) Systems
    • [cs.IT]Downlink SCMA Codebook Design with Low Error Rate by Maximizing Minimum Euclidean Distance of Superimposed Codewords
    • [cs.IT]On information projections between multivariate elliptical and location-scale families
    • [cs.IT]Solving phase retrieval with random initial guess is nearly as good as by spectral initialization
    • [cs.IT]The Degraded Discrete-Time Poisson Wiretap Channel
    • [cs.IT]The extended binary quadratic residue code of length 42 holds a 3-design
    • [cs.LG]A Transfer Learning-based State of Charge Estimation for Lithium-Ion Battery at Varying Ambient Temperatures
    • [cs.LG]An Unsupervised Learning Method with Convolutional Auto-Encoder for Vessel Trajectory Similarity Computation
    • [cs.LG]Anomaly Detection for Aggregated Data Using Multi-Graph Autoencoder
    • [cs.LG]Bayesian U-Net for Segmenting Glaciers in SAR Imagery
    • [cs.LG]Benchmarking Machine Learning: How Fast Can Your Algorithms Go?
    • [cs.LG]Condition Assessment of Stay Cables through Enhanced Time Series Classification Using a Deep Learning Approach
    • [cs.LG]Contrastive Learning Improves Critical Event Prediction in COVID-19 Patients
    • [cs.LG]Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation
    • [cs.LG]Curvature-based Feature Selection with Application in Classifying Electronic Health Records
    • [cs.LG]Deep Interactive Bayesian Reinforcement Learning via Meta-Learning
    • [cs.LG]Deep Neural Networks to Recover Unknown Physical Parameters from Oscillating Time Series
    • [cs.LG]Deeplite Neutrino^{TM}: An End-to-End Framework for Constrained Deep Learning Model Optimization
    • [cs.LG]DiPSeN: Differentially Private Self-normalizing Neural Networks For Adversarial Robustness in Federated Learning
    • [cs.LG]Estimation of Missing Data in Intelligent Transportation System
    • [cs.LG]Evaluating Deep Learning Approaches for Covid19 Fake News Detection
    • [cs.LG]Evaluating Disentanglement of Structured Latent Representations
    • [cs.LG]Evolving Reinforcement Learning Algorithms
    • [cs.LG]Explainable Artificial Intelligence (XAI): An Engineering Perspective
    • [cs.LG]FedAR: Activity and Resource-Aware Federated Learning Model for Distributed Mobile Robots
    • [cs.LG]Glacier Calving Front Segmentation Using Attention U-Net
    • [cs.LG]Good Students Play Big Lottery Better
    • [cs.LG]Hierarchical Clustering using Auto-encoded Compact Representation for Time-series Analysis
    • [cs.LG]How to Train Your Energy-Based Models
    • [cs.LG]Identifying Decision Points for Safe and Interpretable Reinforcement Learning in Hypotension Treatment
    • [cs.LG]Impact of Interventional Policies Including Vaccine on Covid-19
    6af0
    Propagation and Socio-Economic Factors
    • [cs.LG]Improved active output selection strategy for noisy environments
    • [cs.LG]Individual Mobility Prediction: An Interpretable Activity-based Hidden Markov Approach
    • [cs.LG]Interpretable Multiple Treatment Revenue Uplift Modeling
    • [cs.LG]Joint Prediction of Remaining Useful Life and Failure Type of Train Wheelsets: A Multi-task Learning Approach
    • [cs.LG]Learning from Satisfying Assignments Using Risk Minimization
    • [cs.LG]Learning to Ignore: Fair and Task Independent Representations
    • [cs.LG]Machine Learning Towards Intelligent Systems: Applications, Challenges, and Opportunities
    • [cs.LG]Modeling Household Online Shopping Demand in the U.S.: A Machine Learning Approach and Comparative Investigation between 2009 and 2017
    • [cs.LG]Occupancy Detection in Room Using Sensor Data
    • [cs.LG]Opportunities of Federated Learning in Connected, Cooperative and Automated Industrial Systems
    • [cs.LG]PowerEvaluationBALD: Efficient Evaluation-Oriented Deep (Bayesian) Active Learning with Stochastic Acquisition Functions
    • [cs.LG]Predicting Patient Outcomes with Graph Representation Learning
    • [cs.LG]Predictive Analysis of Chikungunya
    • [cs.LG]Robust Blockchained Federated Learning with Model Validation and Proof-of-Stake Inspired Consensus
    • [cs.LG]SPAGAN: Shortest Path Graph Attention Network
    • [cs.LG]Second Hand Price Prediction for Tesla Vehicles
    • [cs.LG]Sum-Rate Maximization for UAV-assisted Visible Light Communications using NOMA: Swarm Intelligence meets Machine Learning
    • [cs.LG]Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity
    • [cs.LG]SyReNN: A Tool for Analyzing Deep Neural Networks
    • [cs.LG]Synthetic Glacier SAR Image Generation from Arbitrary Masks Using Pix2Pix Algorithm
    • [cs.LG]System Design for a Data-driven and Explainable Customer Sentiment Monitor
    • [cs.LG]Technology Readiness Levels for Machine Learning Systems
    • [cs.LG]The Semantic Adjacency Criterion in Time Intervals Mining
    • [cs.LG]Time-Series Regeneration with Convolutional Recurrent Generative Adversarial Network for Remaining Useful Life Estimation
    • [cs.LG]Training Deep Architectures Without End-to-End Backpropagation: A Brief Survey
    • [cs.LG]Variational Embeddings for Community Detection and Node Representation
    • [cs.LG]Wheelchair Behavior Recognition for Visualizing Sidewalk Accessibility by Deep Neural Networks
    • [cs.NI]Bandwidth Allocation for Multiple Federated Learning Services in Wireless Edge Networks
    • [cs.NI]Learning Augmented Index Policy for Optimal Service Placement at the Network Edge
    • [cs.NI]Robust and Scalable Routing with Multi-Agent Deep Reinforcement Learning for MANETs
    • [cs.RO]A Cooperative Dynamic Task Assignment Framework for COTSBot AUVs
    • [cs.RO]A review paper of bio-inspired environmental adaptive and precisely maneuverable soft robots
    • [cs.RO]Aligning Robot’s Behaviours and Users’ Perceptions Through Participatory Prototyping
    • [cs.RO]Closing the Planning-Learning Loop with Application to Autonomous Driving in a Crowd
    • [cs.RO]Compliant Fins for Locomotion in Granular Media
    • [cs.RO]Cross-Modal Contrastive Learning of Representations for Navigation using Lightweight, Low-Cost Millimeter Wave Radar for Adverse Environmental Conditions
    • [cs.RO]Exploiting a Fleet of UAVs for Monitoring and Data Acquisition of a Distributed Sensor Network
    • [cs.RO]Investigating the Effect of Sensor Modalities in Multi-Sensor Detection-Prediction Models
    • [cs.RO]Investigation by Driving Simulation of Tractor Overturning Accidents Caused by Steering Instability
    • [cs.RO]Reinforcement Learning Enabled Automatic Impedance Control of a Robotic Knee Prosthesis to Mimic the Intact Knee Motion in a Co-Adapting Environment
    • [cs.RO]Sub-Goal Social Force Model for Collective Pedestrian Motion Under Vehicle Influence
    • [cs.SE]A Neural Question Answering System for Basic Questions about Subroutines
    • [cs.SI]An Early Look at the Parler Online Social Network
    • [cs.SI]Block Modeling and Detectability for Community Structure in Node Attributed Networks
    • [cs.SI]Evaluation of User Dynamics Created by Weak Ties among Divided Communities
    • [cs.SI]TIB’s Visual Analytics Group at MediaEval ‘20: Detecting Fake News on Corona Virus and 5G Conspiracy
    • [cs.SI]VaccinItaly: monitoring Italian conversations around vaccines on Twitter
    • [eess.IV]An Ultra Fast Low Power Convolutional Neural Network Image Sensor with Pixel-level Computing
    • [eess.IV]Analysis of skin lesion images with deep learning
    • [eess.IV]Automatic Polyp Segmentation using Fully Convolutional Neural Network
    • [eess.IV]End-to-end Prostate Cancer Detection in bpMRI via 3D CNNs: Effect of Attention Mechanisms, Clinical Priori and Decoupled False Positive Reduction
    • [eess.IV]Generalize Ultrasound Image Segmentation via Instant and Plug & Play Style Transfer
    • [eess.IV]Learning Rotation Invariant Features for Cryogenic Electron Microscopy Image Reconstruction
    • [eess.SP]Channel Estimation for IRS-aided Multiuser Communications with Reduced Error Propagation
    • [eess.SP]Quantization optimized with respect to the Haar basis
    • [eess.SY]Load Embeddings for Scalable AC-OPF Learning
    • [eess.SY]Privacy-Preserving Transactive Energy Management for IoT-aided Smart Homes via Blockchain
    • [math.AG]Maximum Likelihood Estimation from a Tropical and a Bernstein—Sato Perspective
    • [math.NA]Accuracy and Architecture Studies of Residual Neural Network solving Ordinary Differential Equations
    • [math.NA]Land Use Detection & Identification using Geo-tagged Tweets
    • [math.NA]Randomised maximum likelihood based posterior sampling
    • [math.NA]The shifted ODE method for underdamped Langevin MCMC
    • [math.OC]Marketing Mix Optimization with Practical Constraints
    • [math.PR]Some characterisation results on classical and free Poisson thinning
    • [math.ST]Bayesian estimation of a competing risk model based on Weibull and exponential distributions under right censored data
    • [math.ST]Complexity analysis of Bayesian learning of high-dimensional DAG models and their equivalence classes
    • [math.ST]From Smooth Wasserstein Distance to Dual Sobolev Norm: Empirical Approximation and Statistical Applications
    • [math.ST]HePPCAT: Probabilistic PCA for Data with Heteroscedastic Noise
    • [math.ST]Hidden Markov chains and fields with observations in Riemannian manifolds
    • [math.ST]Multiple Testing in Nonparametric Hidden Markov Models: An Empirical Bayes Approach
    • [physics.comp-ph]Bayesian optimization with improved scalability and derivative information for efficient design of nanophotonic structures
    • [physics.data-an]Persistent Homology of Weighted Visibility Graph from Fractional Gaussian Noise
    • [physics.geo-ph]HypoSVI: Hypocenter inversion with Stein variational inference and Physics Informed Neural Networks
    • [physics.soc-ph]Network clique cover approximation to analyze complex contagions through group interactions
    • [physics.soc-ph]Social networks as an apparatus for managing of information security in the digital economy
    • [q-bio.PE]A stochastic geospatial epidemic model and simulation using an event modulated Gillespie algorithm
    • [q-bio.QM]SARS-Cov-2 RNA Sequence Classification Based on Territory Information
    • [q-bio.QM]Statistical Methods for cis-Mendelian Randomization
    • [q-fin.MF]Deep Reinforcement Learning with Function Properties in Mean Reversion Strategies
    • [q-fin.ST]A Reinforcement Learning Based Encoder-Decoder Framework for Learning Stock Trading Rules
    • [quant-ph]Machine learning approach for quantum non-Markovian noise classification
    • [stat.AP]A Degradation Performance Model With Mixed-type Covariates and Latent Heterogeneity
    • [stat.AP]A Latent Survival Analysis Enabled Simulation Platform For Nursing Home Staffing Strategy Evaluation
    • [stat.AP]Distinction of groups of gamma-ray bursts in the BATSE catalog through fuzzy clustering
    • [stat.AP]The Study of Urban Residential’s Public Space Activeness using Space-centric Approach
    • [stat.AP]Visualizing adverse events using correspondence analysis
    • [stat.AP]gwpcorMapper: an interactive mapping tool for exploring geographically weighted correlation and partial correlation in high-dimensional geospatial datasets
    • [stat.CO]Scaling Up Bayesian Uncertainty Quantification for Inverse Problems using Deep Neural Networks
    • [stat.ME]Adaptive lasso and Dantzig selector for spatial point processes intensity estimation
    • [stat.ME]Bayesian Surrogate Analysis and Uncertainty Propagation with Explicit Surrogate Uncertainties and Implicit Spatio-temporal Correlations
    • [stat.ME]Block Gibbs samplers for logistic mixed models: convergence properties and a comparison with full Gibbs samplers
    • [stat.ME]Compositionally-warped additive mixed modeling for a wide variety of non-Gaussian spatial data
    • [stat.ME]Controlling the EWMA S^2 control chart false alarm behavior when the in-control variance level must be estimated
    • [stat.ME]Fast marginal likelihood estimation of penalties for group-adaptive elastic net
    • [stat.ME]Grid-Parametrize-Split (GriPS) for Improved Scalable Inference in Spatial Big Data Analysis
    • [stat.ME]Hierarchical Dynamic Modeling for Individualized Bayesian Forecasting
    • [stat.ME]Kernel-Distance-Based Covariate Balancing
    • [stat.ME]Modeling Treatment Effect Modification in Multidrug-Resistant Tuberculosis in an Individual Patient Data Meta-Analysis
    • [stat.ME]Modelling Time-Varying Rankings with Autoregressive and Score-Driven Dynamics
    • [stat.ME]Modelling multi-scale state-switching functional data with hidden Markov models
    • [stat.ME]Modelling wind speed with a univariate probability distribution depending on two baseline functions
    • [stat.ML]Correlated Weights in Infinite Limits of Deep Convolutional Neural Networks
    • [stat.ML]Entropic Causal Inference: Identifiability and Finite Sample Results
    • [stat.ML]Preconditioned training of normalizing flows for variational inference in inverse problems
    • [stat.ML]Reinforcement Learning under Model Risk for Biomanufacturing Fermentation Control
    • [stat.ML]The Gaussian Neural Process

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

    • [astro-ph.GA]Evolutionary Map of the Universe (EMU):Compact radio sources in the SCORPIO field towards the Galactic plane
    S. Riggi, G. Umana, C. Trigilio, F. Cavallaro, A. Ingallinera, P. Leto, F. Bufano, R. P. Norris, A. M. Hopkins, M. D. Filipović, H. Andernach, J. Th. van Loon, M. J. Michałowski, C. Bordiu, T. An, C. Buemi, E. Carretti, J. D. Collier, T. Joseph, B. S. Koribalski, R. Kothes, S. Loru, D. McConnell, M. Pommier, E. Sciacca, F. Schilliró, F. Vitello, K. Warhurst, M. Whiting
    http://arxiv.org/abs/2101.03843v1

    • [cs.AI]A Commonsense Reasoning Framework for Explanatory Emotion Attribution, Generation and Re-classification
    Antonio Lieto, Gian Luca Pozzato, Stefano Zoia, Viviana Patti, Rossana Damiano
    http://arxiv.org/abs/2101.04017v1

    • [cs.AI]Are We There Yet? Learning to Localize in Embodied Instruction Following
    Shane Storks, Qiaozi Gao, Govind Thattai, Gokhan Tur
    http://arxiv.org/abs/2101.03431v1

    • [cs.AI]Learn-n-Route: Learning implicit preferences for vehicle routing
    Rocsildes Canoy, Víctor Bucarey, Jayanta Mandi, Tias Guns
    http://arxiv.org/abs/2101.03936v1

    • [cs.AI]Multi-objective Conflict-based Search for Multi-agent Path Finding
    Zhongqiang Ren, Sivakumar Rathinam, Howie Choset
    http://arxiv.org/abs/2101.03805v1

    • [cs.AI]Neurocognitive Informatics Manifesto
    Włodzisław Duch
    http://arxiv.org/abs/2101.03609v1

    • [cs.AI]Optimizing Hospital Room Layout to Reduce the Risk of Patient Falls
    Sarvenaz Chaeibakhsh, Roya Sabbagh Novin, Tucker Hermans, Andrew Merryweather, Alan Kuntz
    http://arxiv.org/abs/2101.03210v1

    • [cs.AI]Stabilized Nested Rollout Policy Adaptation
    Tristan Cazenave, Jean-Baptiste Sevestre, Matthieu Toulemont
    http://arxiv.org/abs/2101.03563v1

    • [cs.CL]A Gamification of Japanese Dependency Parsing
    Masayuki Asahara
    http://arxiv.org/abs/2101.03269v1

    • [cs.CL]A Heuristic-driven Ensemble Framework for COVID-19 Fake News Detection
    Sourya Dipta Das, Ayan Basak, Saikat Dutta
    http://arxiv.org/abs/2101.03545v1

    • [cs.CL]AT-BERT: Adversarial Training BERT for Acronym Identification Winning Solution for SDU@AAAI-21
    Danqing Zhu, Wangli Lin, Yang Zhang, Qiwei Zhong, Guanxiong Zeng, Weilin Wu, Jiayu Tang
    http://arxiv.org/abs/2101.03700v1

    • [cs.CL]Adaptive Prototypical Networks with Label Words and Joint Representation Learning for Few-Shot Relation Classification
    Yan Xiao, Yaochu Jin, Kuangrong Hao
    http://arxiv.org/abs/2101.03526v1

    • [cs.CL]Automating the Compilation of Potential Core-Outcomes for Clinical Trials
    Shwetha Bharadwaj, Melanie Laffin
    http://arxiv.org/abs/2101.04076v1

    • [cs.CL]BERT & Family Eat Word Salad: Experiments with Text Understanding
    Ashim Gupta, Giorgi Kvernadze, Vivek Srikumar
    http://arxiv.org/abs/2101.03453v1

    • [cs.CL]Combating Hostility: Covid-19 Fake News and Hostile Post Detection in Social Media
    Omar Sharif, Eftekhar Hossain, Mohammed Moshiul Hoque
    http://arxiv.org/abs/2101.03291v1

    • [cs.CL]Constraint 2021: Machine Learning Models for COVID-19 Fake News Detection Shared Task
    Thomas Felber
    http://arxiv.org/abs/2101.03717v1

    • [cs.CL]Context- and Sequence-Aware Convolutional Recurrent Encoder for Neural Machine Translation
    Ritam Mallick, Seba Susan, Vaibhaw Agrawal, Rizul Garg, Prateek Rawal
    http://arxiv.org/abs/2101.04030v1

    • [cs.CL]Detecting Hostile Posts using Relational Graph Convolutional Network
    Sarthak, Shikhar Shukla, Govind Mittal, Karm Veer Arya
    http://arxiv.org/abs/2101.03485v1

    • [cs.CL]Graph-of-Tweets: A Graph Merging Approach to Sub-event Identification
    Xiaonan Jing, Julia Taylor Rayz
    http://arxiv.org/abs/2101.03208v1

    • [cs.CL]Identification of COVID-19 related Fake News via Neural Stacking
    Boshko Koloski, Timen Stepišnik Perdih, Senja Pollak, Blaž Škrlj
    http://arxiv.org/abs/2101.03988v1

    • [cs.CL]Improving Multi-hop Knowledge Base Question Answering by Learning Intermediate Supervision Signals
    Gaole He, Yunshi Lan, Jing Jiang, Wayne Xin Zhao, Ji-Rong Wen
    http://arxiv.org/abs/2101.03737v1

    • [cs.CL]Learning Better Sentence Representation with Syntax Information
    Chen Yang
    http://arxiv.org/abs/2101.03343v1

    • [cs.CL]Leveraging Multilingual Transformers for Hate Speech Detection
    Sayar Ghosh Roy, Ujwal Narayan, Tathagata Raha, Zubair Abid, Vasudeva Varma
    http://arxiv.org/abs/2101.03207v1

    • [cs.CL]LightXML: Transformer with Dynamic Negative Sampling for High-Performance Extreme Multi-label Text Classification
    Ting Jiang, Deqing Wang, Leilei Sun, Huayi Yang, Zhengyang Zhao, Fuzhen Zhuang
    http://arxiv.org/abs/2101.03305v1

    • [cs.CL]Misspelling Correction with Pre-trained Contextual Language Model
    Yifei Hu, Xiaonan Jing, Youlim Ko, Julia Taylor Rayz
    http://arxiv.org/abs/2101.03204v1

    • [cs.CL]Model Generalization on COVID-19 Fake News Detection
    Yejin Bang, Etsuko Ishii, Samuel Cahyawijaya, Ziwei Ji, Pascale Fung
    http://arxiv.org/abs/2101.03841v1

    • [cs.CL]Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain Detection
    Alexander Podolskiy, Dmitry Lipin, Andrey Bout, Ekaterina Artemova, Irina Piontkovskaya
    http://arxiv.org/abs/2101.03778v1

    • [cs.CL]Summaformers @ LaySumm 20, LongSumm 20
    Sayar Ghosh Roy, Nikhil Pinnaparaju, Risubh Jain, Manish Gupta, Vasudeva Varma
    http://arxiv.org/abs/2101.03553v1

    • [cs.CL]Task Adaptive Pretraining of Transformers for Hostility Detection
    Tathagata Raha, Sayar Ghosh Roy, Ujwal Narayan, Zubair Abid, Vasudeva Varma
    http://arxiv.org/abs/2101.03382v1

    • [cs.CL]The Logic for a Mildly Context-Sensitive Fragment of the Lambek-Grishin Calculus
    Hiroyoshi Komatsu
    http://arxiv.org/abs/2101.03634v1

    • [cs.CL]Trankit: A Light-Weight Transformer-based Toolkit for Multilingual Natural Language Processing
    Minh Nguyen, Viet Lai, Amir Pouran Ben Veyseh, Thien Huu Nguyen
    http://arxiv.org/abs/2101.03289v1

    • [cs.CL]Unifying Relational Sentence Generation and Retrieval for Medical Image Report Composition
    Fuyu Wang, Xiaodan Liang, Lin Xu, Liang Lin
    http://arxiv.org/abs/2101.03287v1

    • [cs.CV]A novel shape matching descriptor for real-time hand gesture recognition
    Michalis Lazarou, Bo Li, Tania Stathaki
    http://arxiv.org/abs/2101.03923v1

    • [cs.CV]Active Fire Detection in Landsat-8 Imagery: a Large-Scale Dataset and a Deep-Learning Study
    Gabriel Henrique de Almeida Pereira, André Minoro Fusioka, Bogdan Tomoyuki Nassu, Rodrigo Minetto
    http://arxiv.org/abs/2101.03409v1

    • [cs.CV]Activity Recognition with Moving Cameras and Few Training Examples: Applications for Detection of Autism-Related Headbanging
    Peter Washington, Aaron Kline, Onur Cezmi Mutlu, Emilie Leblanc, Cathy Hou, Nate Stockham, Kelley Paskov, Brianna Chrisman, Dennis P. Wall
    http://arxiv.org/abs/2101.03478v1

    • [cs.CV]ArrowGAN : Learning to Generate Videos by Learning Arrow of Time
    Kibeom Hong, Youngjung Uh, Hyeran Byun
    http://arxiv.org/abs/2101.03710v1

    • [cs.CV]CapsField: Light Field-based Face and Expression Recognition in the Wild using Capsule Routing
    Alireza Sepas-Moghaddam, Ali Etemad, Fernando Pereira, Paulo Lobato Correia
    http://arxiv.org/abs/2101.03503v1

    • [cs.CV]Channel Boosting Feature Ensemble for Radar-based Object Detection
    Shoaib Azam, Farzeen Munir, Moongu Jeon
    http://arxiv.org/abs/2101.03531v1

    • [cs.CV]Cognitive Visual Inspection Service for LCD Manufacturing Industry
    Yuanyuan Ding, Junchi Yan, Guoqiang Hu, Jun Zhu
    http://arxiv.org/abs/2101.03747v1

    • [cs.CV]Colorectal Polyp Detection in Real-world Scenario: Design and Experiment Study
    Xinzi Sun, Dechun Wang, Chenxi Zhang, Pengfei Zhang, Zinan Xiong, Yu Cao, Benyuan Liu, Xiaowei Liu, Shuijiao Chen
    http://arxiv.org/abs/2101.04034v1

    • [cs.CV]Combining Neural Network Models for Blood Cell Classification
    Indraneel Ghosh, Siddhant Kundu
    http://arxiv.org/abs/2101.03604v1

    • [cs.CV]Coronary Plaque Analysis for CT Angiography Clinical Research
    Felix Denzinger, Michael Wels, Christian Hopfgartner, Jing Lu, Max Schöbinger, Andreas Maier, Michael Sühling
    http://arxiv.org/abs/2101.03799v1

    • [cs.CV]Cycle Generative Adversarial Networks Algorithm With Style Transfer For Image Generation
    Anugrah Akbar Praramadhan, Guntur Eka Saputra
    http://arxiv.org/abs/2101.03921v1

    • [cs.CV]Deep Adversarial Inconsistent Cognitive Sampling for Multi-view Progressive Subspace Clustering
    Renhao Sun, Yang Wang, Zhao Zhang, Richang Hong, Meng Wang
    http://arxiv.org/abs/2101.03783v1

    • [cs.CV]Deep Learning-based Face Super-resolution: A Survey
    Junjun Jiang, Chenyang Wang, Xianming Liu, Jiayi Ma
    http://arxiv.org/abs/2101.03749v1

    • [cs.CV]Detecting, Localising and Classifying Polyps from Colonoscopy Videos using Deep Learning
    Yu Tian, Leonardo Zorron Cheng Tao Pu, Yuyuan Liu, Gabriel Maicas, Johan W. Verjans, Alastair D. Burt, Seon Ho Shin, Rajvinder Singh, Gustavo Carneiro
    http://arxiv.org/abs/2101.03285v1

    • [cs.CV]Entropy-Based Uncertainty Calibration for Generalized Zero-Shot Learning
    Zhi Chen, Zi Huang, Jingjing Li, Zheng Zhang
    http://arxiv.org/abs/2101.03292v1

    • [cs.CV]Exploring Adversarial Fake Images on Face Manifold
    Dongze Li, Wei Wang, Hongxing Fan, Jing Dong
    http://arxiv.org/abs/2101.03272v1

    • [cs.CV]Extracting Pasture Phenotype and Biomass Percentages using Weakly Supervised Multi-target Deep Learning on a Small Dataset
    Badri Narayanan, Mohamed Saadeldin, Paul Albert, Kevin McGuinness, Brian Mac Namee
    http://arxiv.org/abs/2101.03198v1

    • [cs.CV]FakeBuster: A DeepFakes Detection Tool for Video Conferencing Scenarios
    Vineet Mehta, Parul Gupta, Ramanathan Subramanian, Abhinav Dhall
    http://arxiv.org/abs/2101.03321v1

    • [cs.CV]Heatmap-based Object Detection and Tracking with a Fully Convolutional Neural Network
    Fabian Amherd, Elias Rodriguez
    http://arxiv.org/abs/2101.03541v1

    • [cs.CV]Horizontal-to-Vertical Video Conversion
    Tun Zhu, Daoxin Zhang, Tianran Wang, Jiawei Li, Yao Hu, Jianke Zhu
    http://arxiv.org/abs/2101.04051v1

    • [cs.CV]Identifying Human Edited Images using a CNN
    Jordan Lee, Willy Lin, Konstantinos Ntalis, Anirudh Shah, William Tung, Maxwell Wulff
    http://arxiv.org/abs/2101.03275v1

    • [cs.CV]Investigating the Vision Transformer Model for Image Retrieval Tasks
    Socratis Gkelios, Yiannis Boutalis, Savvas A. Chatzichristofis
    http://arxiv.org/abs/2101.03771v1

    • [cs.CV]Learning Semantically Meaningful Features for Interpretable Classifications
    Sandareka Wickramanayake, Wynne Hsu, Mong Li Lee
    http://arxiv.org/abs/2101.03919v1

    • [cs.CV]Learning from Weakly-labeled Web Videos via Exploring Sub-Concepts
    Kunpeng Li, Zizhao Zhang, Guanhang Wu, Xuehan Xiong, Chen-Yu Lee, Zhichao Lu, Yun Fu, Tomas Pfister
    http://arxiv.org/abs/2101.03713v1

    • [cs.CV]Learning to Segment Rigid Motions from Two Frames
    Gengshan Yang, Deva Ramanan
    http://arxiv.org/abs/2101.03694v1

    • [cs.CV]MAAS: Multi-modal Assignation for Active Speaker Detection
    Juan León-Alcázar, Fabian Caba Heilbron, Ali Thabet, Bernard Ghanem
    http://arxiv.org/abs/2101.03682v1

    • [cs.CV]Multi-Domain Image-to-Image Translation with Adaptive Inference Graph
    The-Phuc Nguyen, Stéphane Lathuilière, Elisa Ricci
    http://arxiv.org/abs/2101.03806v1

    • [cs.CV]Neural Re-Rendering of Humans from a Single Image
    Kripasindhu Sarkar, Dushyant Mehta, Weipeng Xu, Vladislav Golyanik, Christian Theobalt
    http://arxiv.org/abs/2101.04104v1

    • [cs.CV]ORDNet: Capturing Omni-Range Dependencies for Scene Parsing
    Shaofei Huang, Si Liu, Tianrui Hui, Jizhong Han, Bo Li, Jiashi Feng, Shuicheng Yan
    http://arxiv.org/abs/2101.03929v1

    • [cs.CV]Provably Approximated ICP
    Ibrahim Jubran, Alaa Maalouf, Ron Kimmel, Dan Feldman
    http://arxiv.org/abs/2101.03588v1

    • [cs.CV]Pushing the Envelope of Thin Crack Detection
    Liang Xu, Taro Hatsutani, Xing Liu, Engkarat Techapanurak, Han Zou, Takayuki Okatani
    http://arxiv.org/abs/2101.03326v1

    • [cs.CV]Remote Pulse Estimation in the Presence of Face Masks
    Jeremy Speth, Nathan Vance, Patrick Flynn, Kevin Bowyer, Adam Czajka
    http://arxiv.org/abs/2101.04096v1

    • [cs.CV]RepVGG: Making VGG-style ConvNets Great Again
    Xiaohan Ding, Xiangyu Zhang, Ningning Ma, Jungong Han, Guiguang Ding, Jian Sun
    http://arxiv.org/abs/2101.03697v1

    • [cs.CV]Semantic Segmentation of Remote Sensing Images with Sparse Annotations
    Yuansheng Hua, Diego Marcos, Lichao Mou, Xiao Xiang Zhu, Devis Tuia
    http://arxiv.org/abs/2101.03492v1

    • [cs.CV]Spherical Transformer: Adapting Spherical Signal to ConvolutionalNetworks
    Haikuan Du, Hui Cao, Shen Cai, Junchi Yan, Siyu Zhang
    http://arxiv.org/abs/2101.03848v1

    • [cs.CV]Target Detection and Segmentation in Circular-Scan Synthetic-Aperture-Sonar Images using Semi-Supervised Convolutional Encoder-Decoders
    Isaac J. Sledge, Matthew S. Emigh, Jonathan L. King, Denton L. Woods, J. Tory Cobb, Jose C. Principe
    http://arxiv.org/abs/2101.03603v1

    • [cs.CV]The Diabetic Buddy: A Diet Regulator andTracking System for Diabetics
    Muhammad Usman, Kashif Ahmad, Amir Sohail, Marwa Qaraqe
    http://arxiv.org/abs/2101.03203v1

    • [cs.CV]The Gaze and Mouse Signal as additional Source for User Fingerprints in Browser Applications
    Wolfgang Fuhl, Nikolai Sanamrad, Enkelejda Kasneci
    http://arxiv.org/abs/2101.03793v1

    • [cs.CV]The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing
    Andreas Bär, Jonas Löhdefink, Nikhil Kapoor, Serin J. Varghese, Fabian Hüger, Peter Schlicht, Tim Fingscheidt
    http://arxiv.org/abs/2101.03924v1

    • [cs.CV]Towards Real-World Blind Face Restoration with Generative Facial Prior
    Xintao Wang, Yu Li, Honglun Zhang, Ying Shan
    http://arxiv.org/abs/2101.04061v1

    • [cs.CV]Unchain the Search Space with Hierarchical Differentiable Architecture Search
    Guanting Liu, Yujie Zhong, Sheng Guo, Matthew R. Scott, Weilin Huang
    http://arxiv.org/abs/2101.04028v1

    • [cs.CV]Unobtrusive Pain Monitoring in Older Adults with Dementia using Pairwise and Contrastive Training
    Siavash Rezaei, Abhishek Moturu, Shun Zhao, Kenneth M. Prkachin, Thomas Hadjistavropoulos, Babak Taati
    http://arxiv.org/abs/2101.03251v1

    • [cs.CV]Using Crowdsourcing to Train Facial Emotion Machine Learning Models with Ambiguous Labels
    Peter Washington, Onur Cezmi Mutlu, Emilie Leblanc, Aaron Kline, Cathy Hou, Brianna Chrisman, Nate Stockham, Kelley Paskov, Catalin Voss, Nick Haber, Dennis Wall
    http://arxiv.org/abs/2101.03477v1

    • [cs.CV]WDR FACE: The First Database for Studying Face Detection in Wide Dynamic Range
    Ziyi Liu, Jie Yang, Mengchen Lin, Kenneth Kam Fai Lai, Svetlana Yanushkevich, Orly Yadid-Pecht
    http://arxiv.org/abs/2101.03826v1

    • [cs.CV]WiCV 2020: The Seventh Women In Computer Vision Workshop
    Hazel Doughty, Nour Karessli, Kathryn Leonard, Boyi Li, Carianne Martinez, Azadeh Mobasher, Arsha Nagrani, Srishti Yadav
    http://arxiv.org/abs/2101.03787v1

    • [cs.CY]A Review of Game-based Mobile E-Learning Applications
    Carlo H. Godoy Jr
    http://arxiv.org/abs/2101.03683v1

    • [cs.CY]Perspectives and Challenges in the Analysis of Prison Systems Data: A Systematic Mapping
    Glauco de Figueiredo Carneiro, Rafael Antonio Lima Cardoso, Antonio Pedro Dores, José Euclimar Xavier Menezes
    http://arxiv.org/abs/2101.03539v1

    • [cs.CY]Representativeness in Statistics, Politics, and Machine Learning
    Kyla Chasalow, Karen Levy
    http://arxiv.org/abs/2101.03827v1

    • [cs.DB]FlashP: An Analytical Pipeline for Real-time Forecasting of Time-Series Relational Data
    Shuyuan Yan, Bolin Ding, Wei Guo, Jingren Zhou, Zhewei Wei, Xiaowei Jiang, Sheng Xu
    http://arxiv.org/abs/2101.03298v1

    • [cs.DC]A Fault Tolerant Mechanism for Partitioning and Offloading Framework in Pervasive Environments
    Nevin Vunka Jungum, Nawaz Mohamudally, Nimal Nissanke
    http://arxiv.org/abs/2101.03733v1

    • [cs.DC]Con-Pi: A Distributed Container-based Edge and Fog Computing Framework for Raspberry Pis
    Redowan Mahmud, Adel N. Toosi
    http://arxiv.org/abs/2101.03533v1

    • [cs.DC]Distributed Double Machine Learning with a Serverless Architecture
    Malte S. Kurz
    http://arxiv.org/abs/2101.04025v1

    • [cs.DC]Internet of Things (IoT) Application Model for Smart Farming
    Jagruti Sahoo, Kristin Barrett
    http://arxiv.org/abs/2101.03722v1

    • [cs.DC]**Kuksa: Self-Adaptive Microservices in Automotive Systems
    Ahmad Banijamali, Pasi Kuvaja, Markku Oivo, Pooyan Jamshidi
    http://arxiv.org/abs/2101.03524v1

    • [cs.DC]Running Time Analysis of Broadcast Consensus Protocols
    Philipp Czerner, Stefan Jaax
    http://arxiv.org/abs/2101.03780v1

    • [cs.DC]SDRBench: Scientific Data Reduction Benchmark for Lossy Compressors
    Kai Zhao, Sheng Di, Xin Liang, Sihuan Li, Dingwen Tao, Julie Bessac, Zizhong Chen, Franck Cappello
    http://arxiv.org/abs/2101.03201v1

    • [cs.DC]Strengthened Fault Tolerance in Byzantine Fault Tolerant Replication
    Zhuolun Xiang, Dahlia Malkhi, Kartik Nayak, Ling Ren
    http://arxiv.org/abs/2101.03715v1

    • [cs.ET]Quantum Generative Models for Small Molecule Drug Discovery
    Junde Li, Rasit Topaloglu, Swaroop Ghosh
    http://arxiv.org/abs/2101.03438v1

    • [cs.HC]Machine Learning Uncertainty as a Design Material: A Post-Phenomenological Inquiry
    Jesse Josua Benjamin, Arne Berger, Nick Merrill, James Pierce
    http://arxiv.org/abs/2101.04035v1

    • [cs.IR]An Unsupervised Normalization Algorithm for Noisy Text: A Case Study for Information Retrieval and Stance Detection
    Anurag Roy, Shalmoli Ghosh, Kripabandhu Ghosh, Saptarshi Ghosh
    http://arxiv.org/abs/2101.03303v1

    • [cs.IR]Context-Aware Target Apps Selection and Recommendation for Enhancing Personal Mobile Assistants
    Mohammad Aliannejadi, Hamed Zamani, Fabio Crestani, W. Bruce Croft
    http://arxiv.org/abs/2101.03394v1

    • [cs.IR]Disentangled Self-Attentive Neural Networks for Click-Through Rate Prediction
    Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang
    http://arxiv.org/abs/2101.03654v1

    • [cs.IR]Generate Natural Language Explanations for Recommendation
    Hanxiong Chen, Xu Chen, Shaoyun Shi, Yongfeng Zhang
    http://arxiv.org/abs/2101.03392v1

    • [cs.IR]Selection of Optimal Parameters in the Fast K-Word Proximity Search Based on Multi-component Key Indexes
    Alexander B. Veretennikov
    http://arxiv.org/abs/2101.03327v1

    • [cs.IR]Towards Long-term Fairness in Recommendation
    Yingqiang Ge, Shuchang Liu, Ruoyuan Gao, Yikun Xian, Yunqi Li, Xiangyu Zhao, Changhua Pei, Fei Sun, Junfeng Ge, Wenwu Ou, Yongfeng Zhang
    http://arxiv.org/abs/2101.03584v1

    • [cs.IR]Transfer Learning and Augmentation for Word Sense Disambiguation
    Harsh Kohli
    http://arxiv.org/abs/2101.03617v1

    • [cs.IT]Cross Domain Iterative Detection for Orthogonal Time Frequency Space Modulation
    Shuangyang Li, Weijie Yuan, Zhiqiang Wei, Jinhong Yuan
    http://arxiv.org/abs/2101.03822v1

    • [cs.IT]Delay Minimization in Sliced Multi-Cell Mobile Edge Computing (MEC) Systems
    Sheyda Zarandi, Hina Tabassum
    http://arxiv.org/abs/2101.03405v1

    • [cs.IT]Downlink SCMA Codebook Design with Low Error Rate by Maximizing Minimum Euclidean Distance of Superimposed Codewords
    Chinwei Huang, Borching Su, Tingyi Lin, Yenming Huang
    http://arxiv.org/abs/2101.03355v1

    • [cs.IT]On information projections between multivariate elliptical and location-scale families
    Frank Nielsen
    http://arxiv.org/abs/2101.03839v1

    • [cs.IT]Solving phase retrieval with random initial guess is nearly as good as by spectral initialization
    Jianfeng Cai, Meng Huang, Dong Li, Yang Wang
    http://arxiv.org/abs/2101.03540v1

    • [cs.IT]The Degraded Discrete-Time Poisson Wiretap Channel
    Morteza Soltani, Zouheir Rezki
    http://arxiv.org/abs/2101.03650v1

    • [cs.IT]The extended binary quadratic residue code of length 42 holds a 3-design
    Alexis Bonnecaze, Patrick Solé
    http://arxiv.org/abs/2101.03225v1

    • [cs.LG]A Transfer Learning-based State of Charge Estimation for Lithium-Ion Battery at Varying Ambient Temperatures
    Yan Qin, Stefan Adams, Chau Yuen
    http://arxiv.org/abs/2101.03704v1

    • [cs.LG]An Unsupervised Learning Method with Convolutional Auto-Encoder for Vessel Trajectory Similarity Computation
    Maohan Liang, Ryan Wen Liu, Shichen Li, Zhe Xiao, Xin Liu, Feng Lu
    http://arxiv.org/abs/2101.03169v1

    • [cs.LG]Anomaly Detection for Aggregated Data Using Multi-Graph Autoencoder
    Tomer Meirman, Roni Stern, Gilad Katz
    http://arxiv.org/abs/2101.04053v1

    • [cs.LG]Bayesian U-Net for Segmenting Glaciers in SAR Imagery
    Andreas Hartmann, Amirabbas Davari, Thorsten Seehaus, Matthias Braun, Andreas Maier, Vincent Christlein
    http://arxiv.org/abs/2101.03249v1

    • [cs.LG]Benchmarking Machine Learning: How Fast Can Your Algorithms Go?
    Zeyu Ning, Hugues Nelson Iradukunda, Qingquan Zhang, Ting Zhu
    http://arxiv.org/abs/2101.03219v1

    • [cs.LG]Condition Assessment of Stay Cables through Enhanced Time Series Classification Using a Deep Learning Approach
    Zhiming Zhang, Jin Yan, Liangding Li, Hong Pan, Chuanzhi Dong
    http://arxiv.org/abs/2101.03701v1

    • [cs.LG]Contrastive Learning Improves Critical Event Prediction in COVID-19 Patients
    Tingyi Wanyan, Hossein Honarvar, Suraj K. Jaladanki, Chengxi Zang, Nidhi Naik, Sulaiman Somani, Jessica K. De Freitas, Ishan Paranjpe, Akhil Vaid, Riccardo Miotto, Girish N. Nadkarni, Marinka Zitnik, ArifulAzad, Fei Wang, Ying Ding, Benjamin S. Glicksberg
    http://arxiv.org/abs/2101.04013v1

    • [cs.LG]Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation
    Umang Gupta, Aaron Ferber, Bistra Dilkina, Greg Ver Steeg
    http://arxiv.org/abs/2101.04108v1

    • [cs.LG]Curvature-based Feature Selection with Application in Classifying Electronic Health Records
    Zheming Zuo, Jie Li, Noura Al Moubayed
    http://arxiv.org/abs/2101.03581v1

    • [cs.LG]Deep Interactive Bayesian Reinforcement Learning via Meta-Learning
    Luisa Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann
    http://arxiv.org/abs/2101.03864v1

    • [cs.LG]Deep Neural Networks to Recover Unknown Physical Parameters from Oscillating Time Series
    Antoine Garcon, Julian Vexler, Dmitry Budker, Stefan Kramer
    http://arxiv.org/abs/2101.03850v1

    • [cs.LG]Deeplite Neutrino^{TM}: An End-to-End Framework for Constrained Deep Learning Model Optimization
    Anush Sankaran, Olivier Mastropietro, Ehsan Saboori, Yasser Idris, Davis Sawyer, MohammadHossein AskariHemmat, Ghouthi Boukli Hacene
    http://arxiv.org/abs/2101.04073v1

    • [cs.LG]DiPSeN: Differentially Private Self-normalizing Neural Networks For Adversarial Robustness in Federated Learning
    Olakunle Ibitoye, M. Omair Shafiq, Ashraf Matrawy
    http://arxiv.org/abs/2101.03218v1

    • [cs.LG]Estimation of Missing Data in Intelligent Transportation System
    Bahareh Najafi, Saeedeh Parsaeefard, Alberto Leon-Garcia
    http://arxiv.org/abs/2101.03295v1

    • [cs.LG]Evaluating Deep Learning Approaches for Covid19 Fake News Detection
    Apurva Wani, Isha Joshi, Snehal Khandve, Vedangi Wagh, Raviraj Joshi
    http://arxiv.org/abs/2101.04012v1

    • [cs.LG]Evaluating Disentanglement of Structured Latent Representations
    Raphaël Dang-Nhu, Angelika Steger
    http://arxiv.org/abs/2101.04041v1

    • [cs.LG]Evolving Reinforcement Learning Algorithms
    John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Sergey Levine, Quoc V. Le, Honglak Lee, Aleksandra Faust
    http://arxiv.org/abs/2101.03958v1

    • [cs.LG]Explainable Artificial Intelligence (XAI): An Engineering Perspective
    F. Hussain, R. Hussain, E. Hossain
    http://arxiv.org/abs/2101.03613v1

    • [cs.LG]FedAR: Activity and Resource-Aware Federated Learning Model for Distributed Mobile Robots
    Ahmed Imteaj, M. Hadi Amini
    http://arxiv.org/abs/2101.03705v1

    • [cs.LG]Glacier Calving Front Segmentation Using Attention U-Net
    Michael Holzmann, Amirabbas Davari, Thorsten Seehaus, Matthias Braun, Andreas Maier, Vincent Christlein
    http://arxiv.org/abs/2101.03247v1

    • [cs.LG]Good Students Play Big Lottery Better
    Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Chenyu You, Xiaohui Xie, Zhangyang Wang
    http://arxiv.org/abs/2101.03255v1

    • [cs.LG]Hierarchical Clustering using Auto-encoded Compact Representation for Time-series Analysis
    Soma Bandyopadhyay, Anish Datta, Arpan Pal
    http://arxiv.org/abs/2101.03742v1

    • [cs.LG]How to Train Your Energy-Based Models
    Yang Song, Diederik P. Kingma
    http://arxiv.org/abs/2101.03288v1

    • [cs.LG]Identifying Decision Points for Safe and Interpretable Reinforcement Learning in Hypotension Treatment
    Kristine Zhang, Yuanheng Wang, Jianzhun Du, Brian Chu, Leo Anthony Celi, Ryan Kindle, Finale Doshi-Velez
    http://arxiv.org/abs/2101.03309v1

    • [cs.LG]Impact of Interventional Policies Including Vaccine on Covid-19
    6af0
    Propagation and Socio-Economic Factors
    Haonan Wu, Rajarshi Banerjee, Indhumathi Venkatachalam, Daniel Percy-Hughes, Praveen Chougale
    http://arxiv.org/abs/2101.03944v1

    • [cs.LG]Improved active output selection strategy for noisy environments
    Adrian Prochaska, Julien Pillas, Bernard Bäker
    http://arxiv.org/abs/2101.03499v1

    • [cs.LG]Individual Mobility Prediction: An Interpretable Activity-based Hidden Markov Approach
    Baichuan Mo, Zhan Zhao, Haris N. Koutsopoulos, Jinhua Zhao
    http://arxiv.org/abs/2101.03996v1

    • [cs.LG]Interpretable Multiple Treatment Revenue Uplift Modeling
    Robin M. Gubela, Stefan Lessmann
    http://arxiv.org/abs/2101.03336v1

    • [cs.LG]Joint Prediction of Remaining Useful Life and Failure Type of Train Wheelsets: A Multi-task Learning Approach
    Weixin Wang
    http://arxiv.org/abs/2101.03497v1

    • [cs.LG]Learning from Satisfying Assignments Using Risk Minimization
    Manjish Pal. Subham Pokhriyal
    http://arxiv.org/abs/2101.03558v1

    • [cs.LG]Learning to Ignore: Fair and Task Independent Representations
    Linda Helen Boedi, Dr. Helmut Grabner
    http://arxiv.org/abs/2101.04047v1

    • [cs.LG]Machine Learning Towards Intelligent Systems: Applications, Challenges, and Opportunities
    MohammadNoor Injadat, Abdallah Moubayed, Ali Bou Nassif, Abdallah Shami
    http://arxiv.org/abs/2101.03655v1

    • [cs.LG]Modeling Household Online Shopping Demand in the U.S.: A Machine Learning Approach and Comparative Investigation between 2009 and 2017
    Limon Barua, Bo Zou, Yan, Zhou, Yulin Liu
    http://arxiv.org/abs/2101.03690v1

    • [cs.LG]Occupancy Detection in Room Using Sensor Data
    Mohammadhossein Toutiaee
    http://arxiv.org/abs/2101.03616v1

    • [cs.LG]Opportunities of Federated Learning in Connected, Cooperative and Automated Industrial Systems
    Stefano Savazzi, Monica Nicoli, Mehdi Bennis, Sanaz Kianoush, Luca Barbieri
    http://arxiv.org/abs/2101.03367v1

    • [cs.LG]PowerEvaluationBALD: Efficient Evaluation-Oriented Deep (Bayesian) Active Learning with Stochastic Acquisition Functions
    Andreas Kirsch
    http://arxiv.org/abs/2101.03552v1

    • [cs.LG]Predicting Patient Outcomes with Graph Representation Learning
    Emma Rocheteau, Catherine Tong, Petar Veličković, Nicholas Lane, Pietro Liò
    http://arxiv.org/abs/2101.03940v1

    • [cs.LG]Predictive Analysis of Chikungunya
    Sayed Erfan Arefin, Tasnia Ashrafi Heya, Dr Moinul Zaber
    http://arxiv.org/abs/2101.03785v1

    • [cs.LG]Robust Blockchained Federated Learning with Model Validation and Proof-of-Stake Inspired Consensus
    Hang Chen, Syed Ali Asif, Jihong Park, Chien-Chung Shen, Mehdi Bennis
    http://arxiv.org/abs/2101.03300v1

    • [cs.LG]SPAGAN: Shortest Path Graph Attention Network
    Yiding Yang, Xinchao Wang, Mingli Song, Junsong Yuan, Dacheng Tao
    http://arxiv.org/abs/2101.03464v1

    • [cs.LG]Second Hand Price Prediction for Tesla Vehicles
    Sayed Erfan Arefin
    http://arxiv.org/abs/2101.03788v1

    • [cs.LG]Sum-Rate Maximization for UAV-assisted Visible Light Communications using NOMA: Swarm Intelligence meets Machine Learning
    Quoc-Viet Pham, Thien Huynh-The, Mamoun Alazab, Jun Zhao, Won-Joo Hwang
    http://arxiv.org/abs/2101.03498v1

    • [cs.LG]Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity
    William Fedus, Barret Zoph, Noam Shazeer
    http://arxiv.org/abs/2101.03961v1

    • [cs.LG]SyReNN: A Tool for Analyzing Deep Neural Networks
    Matthew Sotoudeh, Aditya V. Thakur
    http://arxiv.org/abs/2101.03263v1

    • [cs.LG]Synthetic Glacier SAR Image Generation from Arbitrary Masks Using Pix2Pix Algorithm
    Rosanna Dietrich-Sussner, Amirabbas Davari, Thorsten Seehaus, Matthias Braun, Vincent Christlein, Andreas Maier, Christian Riess
    http://arxiv.org/abs/2101.03252v1

    • [cs.LG]System Design for a Data-driven and Explainable Customer Sentiment Monitor
    An Nguyen, Stefan Foerstel, Thomas Kittler, Andrey Kurzyukov, Leo Schwinn, Dario Zanca, Tobias Hipp, Da Jun Sun, Michael Schrapp, Eva Rothgang, Bjoern Eskofier
    http://arxiv.org/abs/2101.04086v1

    • [cs.LG]Technology Readiness Levels for Machine Learning Systems
    Alexander Lavin, Ciarán M. Gilligan-Lee, Alessya Visnjic, Siddha Ganju, Dava Newman, Sujoy Ganguly, Danny Lange, Atılım Güneş Baydin, Amit Sharma, Adam Gibson, Yarin Gal, Eric P. Xing, Chris Mattmann, James Parr
    http://arxiv.org/abs/2101.03989v1

    • [cs.LG]The Semantic Adjacency Criterion in Time Intervals Mining
    Alexander Shknevsky, Yuval Shahar, Robert Moskovitch
    http://arxiv.org/abs/2101.03842v1

    • [cs.LG]Time-Series Regeneration with Convolutional Recurrent Generative Adversarial Network for Remaining Useful Life Estimation
    Xuewen Zhang, Yan Qin, Chau Yuen, Lahiru Jayasinghe, Xiang Liu
    http://arxiv.org/abs/2101.03678v1

    • [cs.LG]Training Deep Architectures Without End-to-End Backpropagation: A Brief Survey
    Shiyu Duan, Jose C. Principe
    http://arxiv.org/abs/2101.03419v1

    • [cs.LG]Variational Embeddings for Community Detection and Node Representation
    Rayyan Ahmad Khan, Muhammad Umer Anwaar, Omran Kaddah, Martin Kleinsteuber
    http://arxiv.org/abs/2101.03885v1

    • [cs.LG]Wheelchair Behavior Recognition for Visualizing Sidewalk Accessibility by Deep Neural Networks
    Takumi Watanabe, Hiroki Takahashi, Goh Sato, Yusuke Iwasawa, Yutaka Matsuo, Ikuko Eguchi Yairi
    http://arxiv.org/abs/2101.03724v1

    • [cs.NI]Bandwidth Allocation for Multiple Federated Learning Services in Wireless Edge Networks
    Jie Xu, Heqiang Wang, Lixing Chen
    http://arxiv.org/abs/2101.03627v1

    • [cs.NI]Learning Augmented Index Policy for Optimal Service Placement at the Network Edge
    Guojun Xiong, Rahul Singh, Jian Li
    http://arxiv.org/abs/2101.03641v1

    • [cs.NI]Robust and Scalable Routing with Multi-Agent Deep Reinforcement Learning for MANETs
    Saeed Kaviani, Bo Ryu, Ejaz Ahmed, Kevin A. Larson, Anh Le, Alex Yahja, Jae H. Kim
    http://arxiv.org/abs/2101.03273v1

    • [cs.RO]A Cooperative Dynamic Task Assignment Framework for COTSBot AUVs
    Amin Abbasi, Somaiyeh MahmoudZadeh, Amirmehdi Yazdani
    http://arxiv.org/abs/2101.03696v1

    • [cs.RO]A review paper of bio-inspired environmental adaptive and precisely maneuverable soft robots
    Mengqi Shen
    http://arxiv.org/abs/2101.03171v1

    • [cs.RO]Aligning Robot’s Behaviours and Users’ Perceptions Through Participatory Prototyping
    Pamela Carreno-Medrano, Leimin Tian, Aimee Allen, Shanti Sumartojo, Michael Mintrom, Enrique Coronado, Gentiane Venture, Elizabeth Croft, Dana Kulic
    http://arxiv.org/abs/2101.03660v1

    • [cs.RO]Closing the Planning-Learning Loop with Application to Autonomous Driving in a Crowd
    Panpan Cai, David Hsu
    http://arxiv.org/abs/2101.03834v1

    • [cs.RO]Compliant Fins for Locomotion in Granular Media
    Dongting Li, Sichuan Huang, Yong Tang, Hamidreza Marvi, Daniel M. Aukes
    http://arxiv.org/abs/2101.03624v1

    • [cs.RO]Cross-Modal Contrastive Learning of Representations for Navigation using Lightweight, Low-Cost Millimeter Wave Radar for Adverse Environmental Conditions
    Jui-Te Huang, Chen-Lung Lu, Po-Kai Chang, Ching-I Huang, Chao-Chun Hsu, Zu Lin Ewe, Po-Jui Huang, Hsueh-Cheng Wang
    http://arxiv.org/abs/2101.03525v1

    • [cs.RO]Exploiting a Fleet of UAVs for Monitoring and Data Acquisition of a Distributed Sensor Network
    S. MahmoudZadeh, A. Yazdani, A. Elmi, A. Abbasi, P. Ghanooni
    http://arxiv.org/abs/2101.03693v1

    • [cs.RO]Investigating the Effect of Sensor Modalities in Multi-Sensor Detection-Prediction Models
    Abhishek Mohta, Fang-Chieh Chou, Brian C. Becker, Carlos Vallespi-Gonzalez, Nemanja Djuric
    http://arxiv.org/abs/2101.03279v1

    • [cs.RO]Investigation by Driving Simulation of Tractor Overturning Accidents Caused by Steering Instability
    Masahisa Watanabe, Kenshi Sakai
    http://arxiv.org/abs/2101.03270v1

    • [cs.RO]Reinforcement Learning Enabled Automatic Impedance Control of a Robotic Knee Prosthesis to Mimic the Intact Knee Motion in a Co-Adapting Environment
    Ruofan Wu, Minhan Li, Zhikai Yao, Jennie Si, He, Huang
    http://arxiv.org/abs/2101.03487v1

    • [cs.RO]Sub-Goal Social Force Model for Collective Pedestrian Motion Under Vehicle Influence
    Dongfang Yang, Fatema T. Johora, Keith A. Redmill, Ümit Özgüner, Jörg P. Müller
    http://arxiv.org/abs/2101.03554v1

    • [cs.SE]A Neural Question Answering System for Basic Questions about Subroutines
    Aakash Bansal, Zachary Eberhart, Lingfei Wu, Collin McMillan
    http://arxiv.org/abs/2101.03999v1

    • [cs.SI]An Early Look at the Parler Online Social Network
    Max Aliapoulios, Emmi Bevensee, Jeremy Blackburn, Emiliano De Cristofaro, Gianluca Stringhini, Savvas Zannettou
    http://arxiv.org/abs/2101.03820v1

    • [cs.SI]Block Modeling and Detectability for Community Structure in Node Attributed Networks
    Ren Ren, Jinliang Shao
    http://arxiv.org/abs/2101.03280v1

    • [cs.SI]Evaluation of User Dynamics Created by Weak Ties among Divided Communities
    Takahiro Kubo, Chisa Takano, Masaki Aida
    http://arxiv.org/abs/2101.03980v1

    • [cs.SI]TIB’s Visual Analytics Group at MediaEval ‘20: Detecting Fake News on Corona Virus and 5G Conspiracy
    Gullal S. Cheema, Sherzod Hakimov, Ralph Ewerth
    http://arxiv.org/abs/2101.03529v1

    • [cs.SI]VaccinItaly: monitoring Italian conversations around vaccines on Twitter
    Francesco Pierri, Silvio Pavanetto, Marco Brambilla, Stefano Ceri
    http://arxiv.org/abs/2101.03757v1

    • [eess.IV]An Ultra Fast Low Power Convolutional Neural Network Image Sensor with Pixel-level Computing
    Ruibing Song, Kejie Huang, Zongsheng Wang, Haibin Shen
    http://arxiv.org/abs/2101.03308v1

    • [eess.IV]Analysis of skin lesion images with deep learning
    Josef Steppan, Sten Hanke
    http://arxiv.org/abs/2101.03814v1

    • [eess.IV]Automatic Polyp Segmentation using Fully Convolutional Neural Network
    Nikhil Kumar Tomar
    http://arxiv.org/abs/2101.04001v1

    • [eess.IV]End-to-end Prostate Cancer Detection in bpMRI via 3D CNNs: Effect of Attention Mechanisms, Clinical Priori and Decoupled False Positive Reduction
    Anindo Saha, Matin Hosseinzadeh, Henkjan Huisman
    http://arxiv.org/abs/2101.03244v1

    • [eess.IV]Generalize Ultrasound Image Segmentation via Instant and Plug & Play Style Transfer
    Zhendong Liu, Xiaoqiong Huang, Xin Yang, Rui Gao, Rui Li, Yuanji Zhang, Yankai Huang, Guangquan Zhou, Yi Xiong, Alejandro F Frangi, Dong Ni
    http://arxiv.org/abs/2101.03711v1

    • [eess.IV]Learning Rotation Invariant Features for Cryogenic Electron Microscopy Image Reconstruction
    Koby Bibas, Gili Weiss-Dicker, Dana Cohen, Noa Cahan, Hayit Greenspan
    http://arxiv.org/abs/2101.03549v1

    • [eess.SP]Channel Estimation for IRS-aided Multiuser Communications with Reduced Error Propagation
    Yi Wei, Ming-Min Zhao, Min-Jian Zhao, Yunlong Cai
    http://arxiv.org/abs/2101.03314v1

    • [eess.SP]Quantization optimized with respect to the Haar basis
    Shu Nakamura
    http://arxiv.org/abs/2101.03304v1

    • [eess.SY]Load Embeddings for Scalable AC-OPF Learning
    Terrence W. K. Mak, Ferdinando Fioretto, Pascal VanHentenryck
    http://arxiv.org/abs/2101.03973v1

    • [eess.SY]Privacy-Preserving Transactive Energy Management for IoT-aided Smart Homes via Blockchain
    Qing Yang, Hao Wang
    http://arxiv.org/abs/2101.03840v1

    • [math.AG]Maximum Likelihood Estimation from a Tropical and a Bernstein—Sato Perspective
    Robin van der Veer, Anna-Laura Sattelberger
    http://arxiv.org/abs/2101.03570v1

    • [math.NA]Accuracy and Architecture Studies of Residual Neural Network solving Ordinary Differential Equations
    Changxin Qiu, Aaron Bendickson, Joshua Kalyanapu, Jue Yan
    http://arxiv.org/abs/2101.03583v1

    • [math.NA]Land Use Detection & Identification using Geo-tagged Tweets
    Saeed Khan, Md Shahzamal
    http://arxiv.org/abs/2101.03337v1

    • [math.NA]Randomised maximum likelihood based posterior sampling
    Yuming Ba, Jana de Wiljes, Dean S. Oliver, Sebastian Reich
    http://arxiv.org/abs/2101.03612v1

    • [math.NA]The shifted ODE method for underdamped Langevin MCMC
    James Foster, Terry Lyons, Harald Oberhauser
    http://arxiv.org/abs/2101.03446v1

    • [math.OC]Marketing Mix Optimization with Practical Constraints
    Hsin-Chan Huang, Jiefeng Xu, Alvin Lim
    http://arxiv.org/abs/2101.03663v1

    • [math.PR]Some characterisation results on classical and free Poisson thinning
    Soumendu Sundar Mukherjee
    http://arxiv.org/abs/2101.04105v1

    • [math.ST]Bayesian estimation of a competing risk model based on Weibull and exponential distributions under right censored data
    Hamida Talhi, Hiba Aiachi, Nadji Rahmania
    http://arxiv.org/abs/2101.03550v1

    • [math.ST]Complexity analysis of Bayesian learning of high-dimensional DAG models and their equivalence classes
    Quan Zhou, Hyunwoong Chang
    http://arxiv.org/abs/2101.04084v1

    • [math.ST]From Smooth Wasserstein Distance to Dual Sobolev Norm: Empirical Approximation and Statistical Applications
    Sloan Nietert, Ziv Goldfeld, Kengo Kato
    http://arxiv.org/abs/2101.04039v1

    • [math.ST]HePPCAT: Probabilistic PCA for Data with Heteroscedastic Noise
    David Hong, Kyle Gilman, Laura Balzano, Jeffrey A. Fessler
    http://arxiv.org/abs/2101.03468v1

    • [math.ST]Hidden Markov chains and fields with observations in Riemannian manifolds
    Salem Said, Nicolas Le Bihan, Jonathan H. Manton
    http://arxiv.org/abs/2101.03801v1

    • [math.ST]Multiple Testing in Nonparametric Hidden Markov Models: An Empirical Bayes Approach
    Kweku Abraham, Ismael Castillo, Elisabeth Gassiat
    http://arxiv.org/abs/2101.03838v1

    • [physics.comp-ph]Bayesian optimization with improved scalability and derivative information for efficient design of nanophotonic structures
    Xavier Garcia-Santiago, Sven Burger, Carsten Rockstuhl, Philipp-Immanuel Schneider
    http://arxiv.org/abs/2101.02972v1

    • [physics.data-an]Persistent Homology of Weighted Visibility Graph from Fractional Gaussian Noise
    H. Masoomy, B. Askari, M. N. Najafi, S. M. S. Movahed
    http://arxiv.org/abs/2101.03328v1

    • [physics.geo-ph]HypoSVI: Hypocenter inversion with Stein variational inference and Physics Informed Neural Networks
    Jonathan D. Smith, Zachary E. Ross, Kamyar Azizzadenesheli, Jack B. Muir
    http://arxiv.org/abs/2101.03271v1

    • [physics.soc-ph]Network clique cover approximation to analyze complex contagions through group interactions
    Giulio Burgio, Alex Arenas, Sergio Gómez, Joan T. Matamalas
    http://arxiv.org/abs/2101.03618v1

    • [physics.soc-ph]Social networks as an apparatus for managing of information security in the digital economy
    Anatolii A. Shyian
    http://arxiv.org/abs/2101.03357v1

    • [q-bio.PE]A stochastic geospatial epidemic model and simulation using an event modulated Gillespie algorithm
    Alexander Temerev, Liudmila Rozanova, Olivia Keiser, Janne Estill
    http://arxiv.org/abs/2101.03934v1

    • [q-bio.QM]SARS-Cov-2 RNA Sequence Classification Based on Territory Information
    Jingwei Liu
    http://arxiv.org/abs/2101.03323v1

    • [q-bio.QM]Statistical Methods for cis-Mendelian Randomization
    Apostolos Gkatzionis, Stephen Burgess, Paul J. Newcombe
    http://arxiv.org/abs/2101.04081v1

    • [q-fin.MF]Deep Reinforcement Learning with Function Properties in Mean Reversion Strategies
    Sophia Gu
    http://arxiv.org/abs/2101.03418v1

    • [q-fin.ST]A Reinforcement Learning Based Encoder-Decoder Framework for Learning Stock Trading Rules
    Mehran Taghian, Ahmad Asadi, Reza Safabakhsh
    http://arxiv.org/abs/2101.03867v1

    • [quant-ph]Machine learning approach for quantum non-Markovian noise classification
    Stefano Martina, Stefano Gherardini, Filippo Caruso
    http://arxiv.org/abs/2101.03221v1

    • [stat.AP]A Degradation Performance Model With Mixed-type Covariates and Latent Heterogeneity
    Xuxue Sun, Wenjun Cai, Qiong Zhang, Mingyang Li
    http://arxiv.org/abs/2101.03671v1

    • [stat.AP]A Latent Survival Analysis Enabled Simulation Platform For Nursing Home Staffing Strategy Evaluation
    Xuxue Sun, Nan Kong, Nazmus Sakib, Chao Meng, Kathryn Hyer, Hongdao Meng, Chris Masterson, Mingyang Li
    http://arxiv.org/abs/2101.03254v1

    • [stat.AP]Distinction of groups of gamma-ray bursts in the BATSE catalog through fuzzy clustering
    Soumita Modak
    http://arxiv.org/abs/2101.03536v1

    • [stat.AP]The Study of Urban Residential’s Public Space Activeness using Space-centric Approach
    Billy Pik Lik Lau, Benny Kai Kiat Ng, Chau Yuen, Bige Tuncer, Keng Hua Chong
    http://arxiv.org/abs/2101.03725v1

    • [stat.AP]Visualizing adverse events using correspondence analysis
    Márcio A. Diniz, Gillian Gresham, Sungjim Kim, Michael Luu, N. Lynn Henry, Mourad Tighiouart, Greg Yothers, Patricia Ganz, André Rogatko
    http://arxiv.org/abs/2101.03454v1

    • [stat.AP]gwpcorMapper: an interactive mapping tool for exploring geographically weighted correlation and partial correlation in high-dimensional geospatial datasets
    Joseph Emile Honour Percival, Narumasa Tsutsumida, Daisuke Murakami, Takahiro Yoshida, Tomoki Nakaya
    http://arxiv.org/abs/2101.03491v1

    • [stat.CO]Scaling Up Bayesian Uncertainty Quantification for Inverse Problems using Deep Neural Networks
    Shiwei Lan, Shuyi Li, Babak Shahbaba
    http://arxiv.org/abs/2101.03906v1

    • [stat.ME]Adaptive lasso and Dantzig selector for spatial point processes intensity estimation
    Achmad Choiruddin, Jean-François Coeurjolly, Frédérique Letué
    http://arxiv.org/abs/2101.03698v1

    • [stat.ME]Bayesian Surrogate Analysis and Uncertainty Propagation with Explicit Surrogate Uncertainties and Implicit Spatio-temporal Correlations
    Sascha Ranftl, Wolfgang von der Linden
    http://arxiv.org/abs/2101.04038v1

    • [stat.ME]Block Gibbs samplers for logistic mixed models: convergence properties and a comparison with full Gibbs samplers
    Yalin Rao, Vivekananda Roy
    http://arxiv.org/abs/2101.03849v1

    • [stat.ME]Compositionally-warped additive mixed modeling for a wide variety of non-Gaussian spatial data
    Daisuke Murakami, Mami Kajita, Seiji Kajita, Tomoko Matsui
    http://arxiv.org/abs/2101.03684v1

    • [stat.ME]Controlling the EWMA S^2 control chart false alarm behavior when the in-control variance level must be estimated
    Sven Knoth
    http://arxiv.org/abs/2101.04011v1

    • [stat.ME]Fast marginal likelihood estimation of penalties for group-adaptive elastic net
    Mirrelijn M. van Nee, Tim van de Brug, Mark A. van de Wiel
    http://arxiv.org/abs/2101.03875v1

    • [stat.ME]Grid-Parametrize-Split (GriPS) for Improved Scalable Inference in Spatial Big Data Analysis
    Michele Peruzzi, Sudipto Banerjee, David B. Dunson, Andrew O. Finley
    http://arxiv.org/abs/2101.03579v1

    • [stat.ME]Hierarchical Dynamic Modeling for Individualized Bayesian Forecasting
    Anna K. Yanchenko, Di Daniel Deng, Jinglan Li, Andrew J. Cron, Mike West
    http://arxiv.org/abs/2101.03408v1

    • [stat.ME]Kernel-Distance-Based Covariate Balancing
    Xialing Wen, Ying Yan, Wenliang Pan, Xianyang Zhang
    http://arxiv.org/abs/2101.03463v1

    • [stat.ME]Modeling Treatment Effect Modification in Multidrug-Resistant Tuberculosis in an Individual Patient Data Meta-Analysis
    Yan Liu, Mireille Schnitzer, Guanbo Wang, Edward Kennedy, Piret Viiklepp, Mario H. Vargas, Giovanni Sotgiu, Dick Menzies, Andrea Benedetti
    http://arxiv.org/abs/2101.03997v1

    • [stat.ME]Modelling Time-Varying Rankings with Autoregressive and Score-Driven Dynamics
    Vladimír Holý, Jan Zouhar
    http://arxiv.org/abs/2101.04040v1

    • [stat.ME]Modelling multi-scale state-switching functional data with hidden Markov models
    Evan Sidrow, Nancy Heckman, Sarah M. E. Fortune, Andrew W. Trites, Ian Murphy, Marie Auger-Méthé
    http://arxiv.org/abs/2101.03268v1

    • [stat.ME]Modelling wind speed with a univariate probability distribution depending on two baseline functions
    Fábio V. J. Silveira, Frank Gomes-Silva, Cícero C. R. Brito, Jader S. Jale, Felipe R. S. Gusmão, Sílvio F. A. Xavier-Júnior, João S. Rocha
    http://arxiv.org/abs/2101.03622v1

    • [stat.ML]Correlated Weights in Infinite Limits of Deep Convolutional Neural Networks
    Adrià Garriga-Alonso, Mark van der Wilk
    http://arxiv.org/abs/2101.04097v1

    • [stat.ML]Entropic Causal Inference: Identifiability and Finite Sample Results
    Spencer Compton, Murat Kocaoglu, Kristjan Greenewald, Dmitriy Katz
    http://arxiv.org/abs/2101.03501v1

    • [stat.ML]Preconditioned training of normalizing flows for variational inference in inverse problems
    Ali Siahkoohi, Gabrio Rizzuti, Mathias Louboutin, Philipp A. Witte, Felix J. Herrmann
    http://arxiv.org/abs/2101.03709v1

    • [stat.ML]Reinforcement Learning under Model Risk for Biomanufacturing Fermentation Control
    Bo Wang, Wei Xie, Tugce Martagan, Alp Akcay
    http://arxiv.org/abs/2101.03735v1

    • [stat.ML]The Gaussian Neural Process
    Wessel P. Bruinsma, James Requeima, Andrew Y. K. Foong, Jonathan Gordon, Richard E. Turner
    http://arxiv.org/abs/2101.03606v1