归档 - 今日学术视野(2021.9.30) - 《爱可可老师分享》

astro-ph.IM - 仪器仪表和天体物理学方法
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.DB - 数据库
cs.DC - 分布式、并行与集群计算
cs.DL - 数字图书馆
cs.DM - 离散数学
cs.GT - 计算机科学与博弈论
cs.HC - 人机接口
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.RO - 机器人学
cs.SD - 声音处理
cs.SI - 社交网络与信息网络
econ.EM - 计量经济学
eess.AS - 语音处理
eess.IV - 图像与视频处理
eess.SP - 信号处理
eess.SY - 系统和控制
hep-th - 高能物理理论
math.CO - 组合数学
math.PR - 概率
math.ST - 统计理论
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.NC - 神经元与认知
q-fin.ST - 统计金融学
quant-ph - 量子物理
stat.AP - 应用统计
stat.ME - 统计方法论
stat.ML - (统计)机器学习

• [astro-ph.IM]Graph Neural Network-based Resource AllocationStrategies for Multi-Object Spectroscopy
• [cs.AI]A taxonomy of strategic human interactions in traffic conflicts
• [cs.AI]Explainable Machine Larning for liver transplantation
• [cs.AI]The Tensor Brain: A Unified Theory of Perception, Memory and Semantic Decoding
• [cs.CL]”How Robust r u?”: Evaluating Task-Oriented Dialogue Systems on Spoken Conversations
• [cs.CL]Active Learning for Argument Mining: A Practical Approach
• [cs.CL]Agreeing to Disagree: Annotating Offensive Language Datasets with Annotators’ Disagreement
• [cs.CL]Analyzing the Use of Character-Level Translation with Sparse and Noisy Datasets
• [cs.CL]Automatic Generation of Word Problems for Academic Education via Natural Language Processing (NLP)
• [cs.CL]Chekhov’s Gun Recognition
• [cs.CL]Cross-lingual Intermediate Fine-tuning improves Dialogue State Tracking
• [cs.CL]Expectation-based Minimalist Grammars
• [cs.CL]Exploring Teacher-Student Learning Approach for Multi-lingual Speech-to-Intent Classification
• [cs.CL]Generating texts under constraint through discriminator-guided MCTS
• [cs.CL]How Different Text-preprocessing Techniques Using The BERT Model Affect The Gender Profiling of Authors
• [cs.CL]Identifying and Mitigating Gender Bias in Hyperbolic Word Embeddings
• [cs.CL]Instance-Based Neural Dependency Parsing
• [cs.CL]Micromodels for Efficient, Explainable, and Reusable Systems: A Case Study on Mental Health
• [cs.CL]Multilingual Counter Narrative Type Classification
• [cs.CL]Nana-HDR: A Non-attentive Non-autoregressive Hybrid Model for TTS
• [cs.CL]On Homophony and Rényi Entropy
• [cs.CL]On Isotropy Calibration of Transformers
• [cs.CL]One to rule them all: Towards Joint Indic Language Hate Speech Detection
• [cs.CL]SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases
• [cs.CL]Sentiment Analysis in Twitter for Macedonian
• [cs.CL]Single-dataset Experts for Multi-dataset Question Answering
• [cs.CL]TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation
• [cs.CL]Template-free Prompt Tuning for Few-shot NER
• [cs.CL]Temporal Information and Event Markup Language: TIE-ML Markup Process and Schema Version 1.0
• [cs.CL]Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
• [cs.CL]Translating from Morphologically Complex Languages: A Paraphrase-Based Approach
• [cs.CL]Visually Grounded Reasoning across Languages and Cultures
• [cs.CR]Are iPhones Really Better for Privacy? Comparative Study of iOS and Android Apps
• [cs.CR]GANG-MAM: GAN based enGine for Modifying Android Malware
• [cs.CV] $今日学术视野(2021.9.30) - 图1$ -Cal: Calibrated aleatoric uncertainty estimation from neural networks for robot perception
• [cs.CV]3D Hand Pose and Shape Estimation from RGB Images for Improved Keypoint-Based Hand-Gesture Recognition
• [cs.CV]A Contrastive Learning Approach to Auroral Identification and Classification
• [cs.CV]A Strong Baseline for the VIPriors Data-Efficient Image Classification Challenge
• [cs.CV]A hierarchical residual network with compact triplet-center loss for sketch recognition
• [cs.CV]Adaptive Attribute and Structure Subspace Clustering Network
• [cs.CV]An Efficient Network Design for Face Video Super-resolution
• [cs.CV]CIDEr-R: Robust Consensus-based Image Description Evaluation
• [cs.CV]Compound eye inspired flat lensless imaging with spatially-coded Voronoi-Fresnel phase
• [cs.CV]Convolutional Shapelet Transform: A new approach for time series shapelets
• [cs.CV]Efficient Computer Vision on Edge Devices with Pipeline-Parallel Hierarchical Neural Networks
• [cs.CV]Efficient Global-Local Memory for Real-time Instrument Segmentation of Robotic Surgical Video
• [cs.CV]Evaluation of Deep Neural Network Domain Adaptation Techniques for Image Recognition
• [cs.CV]Fail-Safe Human Detection for Drones Using a Multi-Modal Curriculum Learning Approach
• [cs.CV]Image scaling by de la Vallée-Poussin filtered interpolation
• [cs.CV]Information Elevation Network for Fast Online Action Detection
• [cs.CV]KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D
• [cs.CV]Modelling Neighbor Relation in Joint Space-Time Graph for Video Correspondence Learning
• [cs.CV]Motion Deblurring with Real Events
• [cs.CV]Multi-Semantic Image Recognition Model and Evaluating Index for explaining the deep learning models
• [cs.CV]Not Color Blind: AI Predicts Racial Identity from Black and White Retinal Vessel Segmentations
• [cs.CV]PDC-Net+: Enhanced Probabilistic Dense Correspondence Network
• [cs.CV]PFENet++: Boosting Few-shot Semantic Segmentation with the Noise-filtered Context-aware Prior Mask
• [cs.CV]SiamEvent: Event-based Object Tracking via Edge-aware Similarity Learning with Siamese Networks
• [cs.CV]Stable training of autoencoders for hyperspectral unmixing
• [cs.CV]StereoSpike: Depth Learning with a Spiking Neural Network
• [cs.CV]The VVAD-LRS3 Dataset for Visual Voice Activity Detection
• [cs.CV]To Which Out-Of-Distribution Object Orientations Are DNNs Capable of Generalizing?
• [cs.CV]Towards Rotation Invariance in Object Detection
• [cs.CV]Turning old models fashion again: Recycling classical CNN networks using the Lattice Transformation
• [cs.CV]ViT Cane: Visual Assistant for the Visually Impaired
• [cs.CV]Warp-Refine Propagation: Semi-Supervised Auto-labeling via Cycle-consistency
• [cs.CV]WarpedGANSpace: Finding non-linear RBF paths in GAN latent space
• [cs.CV]Weakly Supervised Keypoint Discovery
• [cs.CY]A deep dive into the accuracy of IP Geolocation Databases and its impact on online advertising
• [cs.CY]CS Education for the Socially-Just Worlds We Need: The Case for Justice-Centered Approaches to CS in Higher Education
• [cs.CY]Fighting the Fog: Evaluating the Clarity of Privacy Disclosures in the Age of CCPA
• [cs.CY]The Role of Communication Technology Across the Life Course: A Field Guide to Social Support in East York
• [cs.CY]Using Comics to Introduce and Reinforce Programming Concepts in CS1
• [cs.DB]CateCom: a practical data-centric approach to categorization of computational models
• [cs.DC]Dynamics in Coded Edge Computing for IoT: A Fractional Evolutionary Game Approach
• [cs.DC]EdgePier: P2P-based Container Image Distribution in Edge Computing Environments
• [cs.DC]How Low Can You Go? Practical cold-start performance limits in FaaS
• [cs.DC]Restructuring Serverless Computing with Data-Centric Function Orchestration
• [cs.DC]The Megopolis Resampler: Memory Coalesced Resampling on GPUs
• [cs.DL]Modeling Ephraim Chambers’ Knowledge Structure from a Naive Standpoint
• [cs.DM]Compact Redistricting Plans Have Many Spanning Trees
• [cs.GT]Equilibria and learning dynamics in mixed network coordination/anti-coordination games
• [cs.GT]Learning Attacker’s Bounded Rationality Model in Security Games
• [cs.HC]Intelligent Decision Assistance Versus Automated Decision-Making: Enhancing Knowledge Work Through Explainable Artificial Intelligence
• [cs.HC]Opportunistic Implicit User Authentication for Health-Tracking IoT Wearables
• [cs.HC]Trustworthy AI and Robotics and the Implications for the AEC Industry: A Systematic Literature Review and Future Potentials
• [cs.IR]Concept-Aware Denoising Graph Neural Network for Micro-Video Recommendation
• [cs.IR]Exploring The Role of Local and Global Explanations in Recommender Systems
• [cs.IR]Synerise at RecSys 2021: Twitter user engagement prediction with a fast neural model
• [cs.IR]The eDiscovery Medicine Show
• [cs.IT]An Open Problem on the Bentness of Mesnager’s Functions
• [cs.IT]An extended Krylov subspace method for decoding edge-based compressed images by homogeneous diffusion
• [cs.IT]Extended Irreducible Binary Sextic Goppa codes
• [cs.IT]Intelligent Reflecting Surface Aided Wireless Networks: From Single-Reflection to Multi-Reflection Design and Optimization
• [cs.IT]Millimeter Wave and Terahertz Urban Microcell Propagation Measurements and Models
• [cs.IT]New Interleaving Constructions of Asymptotically Optimal Periodic Quasi-Complementary Sequence Sets
• [cs.IT]On Joint Detection and Decoding in Short-Packet Communications
• [cs.IT]The $今日学术视野(2021.9.30) - 图2$ -ary antiprimitive BCH codes
• [cs.IT]Three New Infinite Families of Optimal Locally Repairable Codes from Matrix-Product Codes
• [cs.IT]Two-Stage Channel Estimation Approach for Cell-Free IoT With Massive Random Access
• [cs.IT]Weighted Secrecy Coverage Analysis and the Impact of Friendly Jamming over UAV-Enabled Networks
• [cs.LG]A First-Occupancy Representation for Reinforcement Learning
• [cs.LG]A PAC-Bayesian Analysis of Distance-Based Classifiers: Why Nearest-Neighbour works!
• [cs.LG]A multi-stage semi-supervised improved deep embedded clustering (MS-SSIDEC) method for bearing fault diagnosis under the situation of insufficient labeled samples
• [cs.LG]An Adaptive Deep Learning Framework for Day-ahead Forecasting of Photovoltaic Power Generation
• [cs.LG]An Automated Data Engineering Pipeline for Anomaly Detection of IoT Sensor Data
• [cs.LG]Anomaly Detection for High-Dimensional Data Using Large Deviations Principle
• [cs.LG]Automated Estimation of Construction Equipment Emission using Inertial Sensors and Machine Learning Models
• [cs.LG]Bayesian Transfer Learning: An Overview of Probabilistic Graphical Models for Transfer Learning
• [cs.LG]Cluster Analysis of a Symbolic Regression Search Space
• [cs.LG]Clustering to the Fewest Clusters Under Intra-Cluster Dissimilarity Constraints
• [cs.LG]Confusion-based rank similarity filters for computationally-efficient machine learning on high dimensional data
• [cs.LG]Convergence of Deep Convolutional Neural Networks
• [cs.LG]DEBOSH: Deep Bayesian Shape Optimization
• [cs.LG]DOODLER: Determining Out-Of-Distribution Likelihood from Encoder Reconstructions
• [cs.LG]Deep Reinforcement Learning with Adjustments
• [cs.LG]Delve into the Performance Degradation of Differentiable Architecture Search
• [cs.LG]Discriminative Attribution from Counterfactuals
• [cs.LG]DynG2G: An Efficient Stochastic Graph Embedding Method for Temporal Graphs
• [cs.LG]Exploratory State Representation Learning
• [cs.LG]Exploring More When It Needs in Deep Reinforcement Learning
• [cs.LG]Exposing Paid Opinion Manipulation Trolls
• [cs.LG]FedIPR: Ownership Verification for Federated Deep Neural Network Models
• [cs.LG]IGAN: Inferent and Generative Adversarial Networks
• [cs.LG]Improving Time Series Classification Algorithms Using Octave-Convolutional Layers
• [cs.LG]Introducing the viewpoint in the resource description using machine learning
• [cs.LG]Learning from Small Samples: Transformation-Invariant SVMs with Composition and Locality at Multiple Scales
• [cs.LG]Learning to Superoptimize Real-world Programs
• [cs.LG]Lithium-ion Battery State of Health Estimation based on Cycle Synchronization using Dynamic Time Warping
• [cs.LG]Lyapunov-Net: A Deep Neural Network Architecture for Lyapunov Function Approximation
• [cs.LG]Machine learning methods for prediction of cancer driver genes: a survey paper
• [cs.LG]Making Curiosity Explicit in Vision-based RL
• [cs.LG]Multimodality in Meta-Learning: A Comprehensive Survey
• [cs.LG]Multiwavelet-based Operator Learning for Differential Equations
• [cs.LG]Near-Linear Time Algorithm with Near-Logarithmic Regret Per Switch for Mixable/Exp-Concave Losses
• [cs.LG]Physics-Augmented Learning: A New Paradigm Beyond Physics-Informed Learning
• [cs.LG]Probabilistic modeling of lake surface water temperature using a Bayesian spatio-temporal graph convolutional neural network
• [cs.LG]Reinforcement Learning for Quantitative Trading
• [cs.LG]ST-MAML: A Stochastic-Task based Method for Task-Heterogeneous Meta-Learning
• [cs.LG]Symbolic Regression by Exhaustive Search: Reducing the Search Space Using Syntactical Constraints and Efficient Semantic Structure Deduplication
• [cs.LG]The Fragility of Optimized Bandit Algorithms
• [cs.LG]The Role of Lookahead and Approximate Policy Evaluation in Policy Iteration with Linear Value Function Approximation
• [cs.LG]Unrolling SGD: Understanding Factors Influencing Machine Unlearning
• [cs.LG]Unsolved Problems in ML Safety
• [cs.LG]VoxCeleb Enrichment for Age and Gender Recognition
• [cs.LG]What to Prioritize? Natural Language Processing for the Development of a Modern Bug Tracking Solution in Hardware Development
• [cs.LG]When in Doubt: Improving Classification Performance with Alternating Normalization
• [cs.MM]Audio-to-Image Cross-Modal Generation
• [cs.NE]Extensible Logging and Empirical Attainment Function for IOHexperimenter
• [cs.NE]Faster Improvement Rate Population Based Training
• [cs.NE]Half a Dozen Real-World Applications of Evolutionary Multitasking and More
• [cs.RO]Adaptive Informative Path Planning Using Deep Reinforcement Learning for UAV-based Active Sensing
• [cs.RO]Affordance Template Registration via Human-in-the-loop Corrections
• [cs.RO]Bimanual Telemanipulation with Force and Haptic Feedback and Predictive Limit Avoidance
• [cs.RO]Bottom-Up Skill Discovery from Unsegmented Demonstrations for Long-Horizon Robot Manipulation
• [cs.RO]Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets
• [cs.RO]CRANE: a 10 Degree-of-Freedom, Tele-surgical System for Dexterous Manipulation within Imaging Bores
• [cs.RO]Control Barrier Functions for Singularity Avoidance in Passivity-Based Manipulator Control
• [cs.RO]Cooperative Object Transportation using Gibbs Random Fields
• [cs.RO]Designed to Cooperate: A Kant-Inspired Ethic of Machine-to-Machine Cooperation
• [cs.RO]Interactive Dynamic Walking: Learning Gait Switching Policies with Generalization Guarantees
• [cs.RO]Literature Review on Endoscopic Robotic Systems in Ear and Sinus Surgery
• [cs.RO]Meta Reinforcement Learning Based Sensor Scanning in 3D Uncertain Environments for Heterogeneous Multi-Robot Systems
• [cs.RO]Model-based Motion Imitation for Agile, Diverse and Generalizable Quadupedal Locomotion
• [cs.RO]Multiple-Pilot Collaboration for Advanced Remote Intervention using Reinforcement Learning
• [cs.RO]NimbRo Avatar: Interactive Immersive Telepresence with Force-Feedback Telemanipulation
• [cs.RO]Not Only Domain Randomization: Universal Policy with Embedding System Identification
• [cs.RO]On the Empirical Evaluation of Information Gain Criteria for Active Action Selection
• [cs.RO]Online Object Model Reconstruction and Reuse for Lifelong Improvement of Robot Manipulation
• [cs.RO]Runtime Safety Assurance
1000
for Learning-enabled Control of Autonomous Driving Vehicles
• [cs.RO]SafetyNet: Safe planning for real-world self-driving vehicles using machine-learned policies
• [cs.RO]Scan Context++: Structural Place Recognition Robust to Rotation and Lateral Variations in Urban Environments
• [cs.RO]Solving Challenging Control Problems Using Two-Staged Deep Reinforcement Learning
• [cs.RO]Targetless Extrinsic Calibration of Stereo Cameras, Thermal Cameras, and Laser Sensors in the Wild
• [cs.RO]Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradients
• [cs.SD]Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme
• [cs.SI]Exploring the spatiotemporal heterogeneity in the relationship between human mobility and COVID-19 prevalence using dynamic time warping
• [cs.SI]Extracting Attentive Social Temporal Excitation for Sequential Recommendation
• [cs.SI]Fake News Detection using Semi-Supervised Graph Convolutional Network
• [cs.SI]Learning Ideological Embeddings from Information Cascades
• [cs.SI]Success at high peaks: a multiscale approach combining individual and expedition-wide factors
• [econ.EM]Gaussian and Student’s $今日学术视野(2021.9.30) - 图3$ mixture vector autoregressive model
• [econ.EM]Macroeconomic forecasting with LSTM and mixed frequency time series data
• [econ.EM]bqror: An R package for Bayesian Quantile Regression in Ordinal Models
• [eess.AS]The JHU submission to VoxSRC-21: Track 3
• [eess.IV]Metal Artifact Reduction in 2D CT Images with Self-supervised Cross-domain Learning
• [eess.IV]Real-Time Glaucoma Detection from Digital Fundus Images using Self-ONNs
• [eess.IV]Unsupervised Diffeomorphic Surface Registration and Non-Linear Modelling
• [eess.SP]Index Modulation with Circularly-Shifted Chirps for Dual-Function Radar and Communications
• [eess.SP]Transfer Learning based Evolutionary Deep Neural Network for Intelligent Fault Diagnosis
• [eess.SY]DeepPSL: End-to-end perception and reasoning with applications to zero shot learning
• [eess.SY]Model-Free Reinforcement Learning for Optimal Control of MarkovDecision Processes Under Signal Temporal Logic Specifications
• [hep-th]The edge of chaos: quantum field theory and deep neural networks
• [math.CO]Multiple contractions of permutation arrays
• [math.PR]Perturbation theory for killed Markov processes and quasi-stationary distributions
• [math.ST]A functional central limit theorem for the empirical Ripley’s K-function
• [math.ST]An exact test for significance of clusters in binary data
• [math.ST]Dynamic Ranking with the BTL Model: A Nearest Neighbor based Rank Centrality Method
• [math.ST]Fairness guarantee in multi-class classification
• [math.ST]On eigenvalues of a high dimensional Kendall’s rank correlation matrix with dependences
• [math.ST]Optimal Orthogonal Group Synchronization and Rotation Group Synchronization
• [math.ST]Sharp multiple testing boundary for sparse sequences
• [math.ST]Simulation of non-stationary and non-Gaussian random processes by 3rd-order Spectral Representation Method: Theory and POD implementation
• [math.ST]Statistical inference for function-on-function linear regression
• [physics.data-an]Grassmannian diffusion maps based surrogate modeling via geometric harmonics
• [physics.geo-ph]1D Stochastic Inversion of Airborne Time-domain Electromag-netic Data with Realistic Prior and Accounting for the Forward Modeling Error
• [physics.soc-ph]UEFA could have easily improved the fairness of the European Qualifiers to the 2022 FIFA World Cup
• [q-bio.NC]Text2Brain: Synthesis of Brain Activation Maps from Free-form Text Query
• [q-bio.NC]Towards a Governance Framework for Brain Data
• [q-fin.ST]Intra-Day Price Simulation with Generative Adversarial Modelling of the Order Flow
• [quant-ph]Design of quantum optical experiments with logic artificial intelligence
• [quant-ph]Optimal Simulation of Quantum Measurements via the Likelihood POVMs
• [stat.AP]Disentangling positive and negative partisanship in affective polarization using a coevolving latent space network with attractors model
• [stat.ME]ALL-IN meta-analysis: breathing life into living systematic reviews
• [stat.ME]An Automated Approach to Causal Inference in Discrete Settings
• [stat.ME]Analysis and Methods to Mitigate Effects of Under-reporting in Count Data
• [stat.ME]Assessing Outcome-to-Outcome Interference in Sibling Fixed Effects Models
• [stat.ME]Conditional Cross-Design Synthesis Estimators for Generalizability in Medicaid
• [stat.ME]Heterogeneous Distributed Lag Models to Estimate Personalized Effects of Maternal Exposures to Air Pollution
• [stat.ME]Identification of the Heterogeneous Survivor Average Causal Effect in Observational Studies
• [stat.ME]Interoperability of statistical models in pandemic preparedness: principles and reality
• [stat.ME]Joint marginal structural models to estimate the causal effects of multiple longitudinal treatments in continuous time with application to COVID-19
• [stat.ME]Variance partitioning in spatio-temporal disease mapping models
• [stat.ML]Contributions to Large Scale Bayesian Inference and Adversarial Machine Learning
• [stat.ML]Gaussian Processes to speed up MCMC with automatic exploratory-exploitation effect
• [stat.ML]Improved prediction rule ensembling through model-based data generation

·····································

• [astro-ph.IM]Graph Neural Network-based Resource AllocationStrategies for Multi-Object Spectroscopy
Tianshu Wang, Peter Melchior
http://arxiv.org/abs/2109.13361v1

• [cs.AI]A taxonomy of strategic human interactions in traffic conflicts
Atrisha Sarkar, Kate Larson, Krzysztof Czarnecki
http://arxiv.org/abs/2109.13367v1

• [cs.AI]Explainable Machine Larning for liver transplantation
Pedro Cabalar, Brais Muñiz, Gilberto Pérez, Francisco Suárez
http://arxiv.org/abs/2109.13893v1

• [cs.AI]The Tensor Brain: A Unified Theory of Perception, Memory and Semantic Decoding
Volker Tresp, Sahand Sharifzadeh, Hang Li, Dario Konopatzki, Yunpu Ma
http://arxiv.org/abs/2109.13392v1

• [cs.CL]“How Robust r u?”: Evaluating Task-Oriented Dialogue Systems on Spoken Conversations
Seokhwan Kim, Yang Liu, Di Jin, Alexandros Papangelis, Karthik Gopalakrishnan, Behnam Hedayatnia, Dilek Hakkani-Tur
http://arxiv.org/abs/2109.13489v1

• [cs.CL]Active Learning for Argument Mining: A Practical Approach
Nikolai Solmsdorf, Dietrich Trautmann, Hinrich Schütze
http://arxiv.org/abs/2109.13611v1

• [cs.CL]Agreeing to Disagree: Annotating Offensive Language Datasets with Annotators’ Disagreement
Elisa Leonardelli, Stefano Menini, Alessio Palmero Aprosio, Marco Guerini, Sara Tonelli
http://arxiv.org/abs/2109.13563v1

• [cs.CL]Analyzing the Use of Character-Level Translation with Sparse and Noisy Datasets
Jörg Tiedemann, Preslav Nakov
http://arxiv.org/abs/2109.13723v1

• [cs.CL]Automatic Generation of Word Problems for Academic Education via Natural Language Processing (NLP)
Stanley Uros Keller
http://arxiv.org/abs/2109.13123v2

• [cs.CL]Chekhov’s Gun Recognition
Alexey Tikhonov, Ivan P. Yamshchikov
http://arxiv.org/abs/2109.13855v1

• [cs.CL]Cross-lingual Intermediate Fine-tuning improves Dialogue State Tracking
Nikita Moghe, Mark Steedman, Alexandra Birch
http://arxiv.org/abs/2109.13620v1

• [cs.CL]Expectation-based Minimalist Grammars
Cristiano Chesi
http://arxiv.org/abs/2109.13871v1

• [cs.CL]Exploring Teacher-Student Learning Approach for Multi-lingual Speech-to-Intent Classification
Bidisha Sharma, Maulik Madhavi, Xuehao Zhou, Haizhou Li
http://arxiv.org/abs/2109.13486v1

• [cs.CL]Generating texts under constraint through discriminator-guided MCTS
Antoine Chaffin, Vincent Claveau, Ewa Kijak
http://arxiv.org/abs/2109.13582v1

• [cs.CL]How Different Text-preprocessing Techniques Using The BERT Model Affect The Gender Profiling of Authors
Esam Alzahrani, Leon Jololian
http://arxiv.org/abs/2109.13890v1

• [cs.CL]Identifying and Mitigating Gender Bias in Hyperbolic Word Embeddings
Vaibhav Kumar, Tenzin Singhay Bhotia, Vaibhav Kumar, Tanmoy Chakraborty
http://arxiv.org/abs/2109.13767v1

• [cs.CL]Instance-Based Neural Dependency Parsing
Hiroki Ouchi, Jun Suzuki, Sosuke Kobayashi, Sho Yokoi, Tatsuki Kuribayashi, Masashi Yoshikawa, Kentaro Inui
http://arxiv.org/abs/2109.13497v1

• [cs.CL]Micromodels for Efficient, Explainable, and Reusable Systems: A Case Study on Mental Health
Andrew Lee, Jonathan K. Kummerfeld, Lawrence C. An, Rada Mihalcea
http://arxiv.org/abs/2109.13770v1

• [cs.CL]Multilingual Counter Narrative Type Classification
Yi-Ling Chung, Marco Guerini, Rodrigo Agerri
http://arxiv.org/abs/2109.13664v1

• [cs.CL]Nana-HDR: A Non-attentive Non-autoregressive Hybrid Model for TTS
Shilun Lin, Wenchao Su, Li Meng, Fenglong Xie, Xinhui Li, Li Lu
http://arxiv.org/abs/2109.13673v1

• [cs.CL]On Homophony and Rényi Entropy
Tiago Pimentel, Clara Meister, Simone Teufel, Ryan Cotterell
http://arxiv.org/abs/2109.13766v1

• [cs.CL]On Isotropy Calibration of Transformers
Yue Ding, Karolis Martinkus, Damian Pascual, Simon Clematide, Roger Wattenhofer
http://arxiv.org/abs/2109.13304v1

• [cs.CL]One to rule them all: Towards Joint Indic Language Hate Speech Detection
Mehar Bhatia, Tenzin Singhay Bhotia, Akshat Agarwal, Prakash Ramesh, Shubham Gupta, Kumar Shridhar, Felix Laumann, Ayushman Dash
http://arxiv.org/abs/2109.13711v1

• [cs.CL]SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases
Sumit Neelam, Udit Sharma, Hima Karanam, Shajith Ikbal, Pavan Kapanipathi, Ibrahim Abdelaziz, Nandana Mihindukulasooriya, Young-Suk Lee, Santosh Srivastava, Cezar Pendus, Saswati Dana, Dinesh Garg, Achille Fokoue, G P Shrivatsa Bhargav, Dinesh Khandelwal, Srinivas Ravishankar, Sairam Gurajada, Maria Chang, Rosario Uceda-Sosa, Salim Roukos, Alexander Gray, Guilherme LimaRyan Riegel, Francois Luus, L Venkata Subramaniam
http://arxiv.org/abs/2109.13430v1

• [cs.CL]Sentiment Analysis in Twitter for Macedonian
Dame Jovanoski, Veno Pachovski, Preslav Nakov
http://arxiv.org/abs/2109.13725v1

• [cs.CL]Single-dataset Experts for Multi-dataset Question Answering
Dan Friedman, Ben Dodge, Danqi Chen
http://arxiv.org/abs/2109.13880v1

• [cs.CL]TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation
Adaku Uchendu, Zeyu Ma, Thai Le, Rui Zhang, Dongwon Lee
http://arxiv.org/abs/2109.13296v1

• [cs.CL]Template-free Prompt Tuning for Few-shot NER
Ruotian Ma, Xin Zhou, Tao Gui, Yiding Tan, Qi Zhang, Xuanjing Huang
http://arxiv.org/abs/2109.13532v1

• [cs.CL]Temporal Information and Event Markup Language: TIE-ML Markup Process and Schema Version 1.0
Damir Cavar, Billy Dickson, Ali Aljubailan, Soyoung Kim
http://arxiv.org/abs/2109.13892v1

• [cs.CL]Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
Fangyu Liu, Yunlong Jiao, Jordan Massiah, Emine Yilmaz, Serhii Havrylov
http://arxiv.org/abs/2109.13059v2

• [cs.CL]Translating from Morphologically Complex Languages: A Paraphrase-Based Approach
Preslav Nakov, Hwee Tou Ng
http://arxiv.org/abs/2109.13724v1

• [cs.CL]Visually Grounded Reasoning across Languages and Cultures
Fangyu Liu, Emanuele Bugliarello, Edoardo Maria Ponti, Siva Reddy, Nigel Collier, Desmond Elliott
http://arxiv.org/abs/2109.13238v1

• [cs.CR]Are iPhones Really Better for Privacy? Comparative Study of iOS and Android Apps
Konrad Kollnig, Anastasia Shuba, Reuben Binns, Max Van Kleek, Nigel Shadbolt
http://arxiv.org/abs/2109.13722v1

• [cs.CR]GANG-MAM: GAN based enGine for Modifying Android Malware
Renjith G, Sonia Laudanna, Aji S, Corrado Aaron Visaggio, Vinod P
http://arxiv.org/abs/2109.13297v1

• [cs.CV] $今日学术视野(2021.9.30) - 图4$ -Cal: Calibrated aleatoric uncertainty estimation from neural networks for robot perception
Dhaivat Bhatt, Kaustubh Mani, Dishank Bansal, Krishna Murthy, Hanju Lee, Liam Paull
http://arxiv.org/abs/2109.13913v1

• [cs.CV]3D Hand Pose and Shape Estimation from RGB Images for Improved Keypoint-Based Hand-Gesture Recognition
Danilo Avola, Luigi Cinque, Alessio Fagioli, Gian Luca Foresti, Adriano Fragomeni, Daniele Pannone
http://arxiv.org/abs/2109.13879v1

• [cs.CV]A Contrastive Learning Approach to Auroral Identification and Classification
Jeremiah W. Johnson, Swathi Hari, Donald Hampton, Hyunju K. Connor
http://arxiv.org/abs/2109.13899v1

• [cs.CV]A Strong Baseline for the VIPriors Data-Efficient Image Classification Challenge
Björn Barz, Lorenzo Brigato, Luca Iocchi, Joachim Denzler
http://arxiv.org/abs/2109.13561v1

• [cs.CV]A hierarchical residual network with compact triplet-center loss for sketch recognition
Lei Wang, Shihui Zhang, Huan He, Xiaoxiao Zhang, Yu Sang
http://arxiv.org/abs/2109.13536v1

• [cs.CV]Adaptive Attribute and Structure Subspace Clustering Network
Zhihao Peng, Hui Liu, Yuheng Jia, Junhui Hou
http://arxiv.org/abs/2109.13742v1

• [cs.CV]An Efficient Network Design for Face Video Super-resolution
Feng Yu, He Li, Sige Bian, Yongming Tang
http://arxiv.org/abs/2109.13626v1

• [cs.CV]CIDEr-R: Robust Consensus-based Image Description Evaluation
Gabriel Oliveira dos Santos, Esther Luna Colombini, Sandra Avila
http://arxiv.org/abs/2109.13701v1

• [cs.CV]Compound eye inspired flat lensless imaging with spatially-coded Voronoi-Fresnel phase
Qiang Fu, Dong-Ming Yan, Wolfgang Heidrich
http://arxiv.org/abs/2109.13703v1

• [cs.CV]Convolutional Shapelet Transform: A new approach for time series shapelets
Antoine Guillaume, Christel Vrain, Elloumi Wael
http://arxiv.org/abs/2109.13514v1

• [cs.CV]Efficient Computer Vision on Edge Devices with Pipeline-Parallel Hierarchical Neural Networks
Abhinav Goel, Caleb Tung, Xiao Hu, George K. Thiruvathukal, James C. Davis, Yung-Hsiang Lu
http://arxiv.org/abs/2109.13356v1

• [cs.CV]Efficient Global-Local Memory for Real-time Instrument Segmentation of Robotic Surgical Video
Jiacheng Wang, Yueming Jin, Liansheng Wang, Shuntian Cai, Pheng-Ann Heng, Jing Qin
http://arxiv.org/abs/2109.13593v1

• [cs.CV]Evaluation of Deep Neural Network Domain Adaptation Techniques for Image Recognition
Alan Preciado-Grijalva, Venkata Santosh Sai Ramireddy Muthireddy
http://arxiv.org/abs/2109.13420v1

• [cs.CV]Fail-Safe Human Detection for Drones Using a Multi-Modal Curriculum Learning Approach
Ali Safa, Tim Verbelen, Ilja Ocket, André Bourdoux, Francky Catthoor, Georges G. E. Gielen
http://arxiv.org/abs/2109.13666v1

• [cs.CV]Image scaling by de la Vallée-Poussin filtered interpolation
Donatella Occorsio, Giuliana Ramella, Woula Themistoclakis
http://arxiv.org/abs/2109.13897v1

• [cs.CV]Information Elevation Network for Fast Online Action Detection
Sunah Min, Jinyoung Moon
http://arxiv.org/abs/2109.13572v1

• [cs.CV]KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D
Yiyi Liao, Jun Xie, Andreas Geiger
http://arxiv.org/abs/2109.13410v1

• [cs.CV]Modelling Neighbor Relation in Joint Space-Time Graph for Video Correspondence Learning
Zixu Zhao, Yueming Jin, Pheng-Ann Heng
http://arxiv.org/abs/2109.13499v1

• [cs.CV]Motion Deblurring with Real Events
Fang Xu, Lei Yu, Bishan Wang, Wen Yang, Gui-Song Xia, Xu Jia, Zhendong Qiao, Jianzhuang Liu
http://arxiv.org/abs/2109.13695v1

• [cs.CV]Multi-Semantic Image Recognition Model and Evaluating Index for explaining the deep learning models
Qianmengke Zhao, Ye Wang, Qun Liu
http://arxiv.org/abs/2109.13531v1

• [cs.CV]Not Color Blind: AI Predicts Racial Identity from Black and White Retinal Vessel Segmentations
Aaron S. Coyner, Praveer Singh, James M. Brown, Susan Ostmo, R. V. Paul Chan, Michael F. Chiang, Jayashree Kalpathy-Cramer, J. Peter Campbell
http://arxiv.org/abs/2109.13845v1

• [cs.CV]PDC-Net+: Enhanced Probabilistic Dense Correspondence Network
Prune Truong, Martin Danelljan, Fisher Yu, Luc Van Gool
http://arxiv.org/abs/2109.13912v1

• [cs.CV]PFENet++: Boosting Few-shot Semantic Segmentation with the Noise-filtered Context-aware Prior Mask
Xiaoliu Luo, Zhuotao Tian, Taiping Zhang, Bei Yu, Yuan Yan Tang, Jiaya Jia
http://arxiv.org/abs/2109.13788v1

• [cs.CV]SiamEvent: Event-based Object Tracking via Edge-aware Similarity Learning with Siamese Networks
Yujeong Chae, Lin Wang, Kuk-Jin Yoon
http://arxiv.org/abs/2109.13456v1

• [cs.CV]Stable training of autoencoders for hyperspectral unmixing
Kamil Książek, Przemysław Głomb, Michał Romaszewski, Michał Cholewa, Bartosz Grabowski
http://arxiv.org/abs/2109.13748v1

• [cs.CV]StereoSpike: Depth Learning with a Spiking Neural Network
Ulysse Rançon, Javier Cuadrado-Anibarro, Benoit R. Cottereau, Timothée Masquelier
http://arxiv.org/abs/2109.13751v1

• [cs.CV]The VVAD-LRS3 Dataset for Visual Voice Activity Detection
Adrian Lubitz, Matias Valdenegro-Toro, Frank Kirchner
http://arxiv.org/abs/2109.13789v1

• [cs.CV]To Which Out-Of-Distribution Object Orientations Are DNNs Capable of Generalizing?
Avi Cooper, Xavier Boix, Daniel Harari, Spandan Madan, Hanspeter Pfister, Tomotake Sasaki, Pawan Sinha
http://arxiv.org/abs/2109.13445v1

• [cs.CV]Towards Rotation Invariance in Object Detection
Agastya Kalra, Guy Stoppi, Bradley Brown, Rishav Agarwal, Achuta Kadambi
http://arxiv.org/abs/2109.13488v1

• [cs.CV]Turning old models fashion again: Recycling classical CNN networks using the Lattice Transformation
Ana Paula G. S. de Almeida, Flavio de Barros Vidal
http://arxiv.org/abs/2109.13885v1

• [cs.CV]ViT Cane: Visual Assistant for the Visually Impaired
Bhavesh Kumar
http://arxiv.org/abs/2109.13857v1

• [cs.CV]Warp-Refine Propagation: Semi-Supervised Auto-labeling via Cycle-consistency
Aditya Ganeshan, Alexis Vallet, Yasunori Kudo, Shin-ichi Maeda, Tommi Kerola, Rares Ambrus, Dennis Park, Adrien Gaidon
http://arxiv.org/abs/2109.13432v1

• [cs.CV]WarpedGANSpace: Finding non-linear RBF paths in GAN latent space
Christos Tzelepis, Georgios Tzimiropoulos, Ioannis Patras
http://arxiv.org/abs/2109.13357v1

• [cs.CV]Weakly Supervised Keypoint Discovery
Serim Ryou, Pietro Perona
http://arxiv.org/abs/2109.13423v1

• [cs.CY]A deep dive into the accuracy of IP Geolocation Databases and its impact on online advertising
Patricia Callejo, Marco Gramaglia, Rubén Cuevas, Ángel Cuevas
http://arxiv.org/abs/2109.13665v1

• [cs.CY]CS Education for the Socially-Just Worlds We Need: The Case for Justice-Centered Approaches to CS in Higher Education
Kevin Lin
http://arxiv.org/abs/2109.13283v1

• [cs.CY]Fighting the Fog: Evaluating the Clarity of Privacy Disclosures in the Age of CCPA
Rex Chen, Fei Fang, Thomas Norton, Aleecia M. McDonald, Norman Sadeh
http://arxiv.org/abs/2109.13816v1

• [cs.CY]The Role of Communication Technology Across the Life Course: A Field Guide to Social Support in East York
Anabel Quan-Haase, Molly-Gloria Harper, Barry Wellmnan
http://arxiv.org/abs/2109.13907v1

• [cs.CY]Using Comics to Introduce and Reinforce Programming Concepts in CS1
Sangho Suh, Celine Latulipe, Ken Jen Lee, Bernadette Cheng, Edith Law
http://arxiv.org/abs/2109.13197v2

• [cs.DB]CateCom: a practical data-centric approach to categorization of computational models
Alexander Zech, Timur Bazhirov
http://arxiv.org/abs/2109.13452v1

• [cs.DC]Dynamics in Coded Edge Computing for IoT: A Fractional Evolutionary Game Approach
Yue Han, Dusit Niyato, Cyril Leung, Chunyan Miao, Dong In Kim
http://arxiv.org/abs/2109.13586v1

• [cs.DC]EdgePier: P2P-based Container Image Distribution in Edge Computing Environments
Soeren Becker, Florian Schmidt, Odej Kao
http://arxiv.org/abs/2109.12983v1

• [cs.DC]How Low Can You Go? Practical cold-start performance limits in FaaS
Yue Tan, David Liu, Nanqinqin Li, Amit Levy
http://arxiv.org/abs/2109.13319v1

• [cs.DC]Restructuring Serverless Computing with Data-Centric Function Orchestration
Minchen Yu, Tingjia Cao, Wei Wang, Ruichuan Chen
http://arxiv.org/abs/2109.13492v1

• [cs.DC]The Megopolis Resampler: Memory Coalesced Resampling on GPUs
Joshua A. Chesser, Hoa Van Nguyen, Damith C. Ranasinghe
http://arxiv.org/abs/2109.13504v1

• [cs.DL]Modeling Ephraim Chambers’ Knowledge Structure from a Naive Standpoint
Scott McClellan, Mat Kelly, Jane Greenberg
http://arxiv.org/abs/2109.13915v1

• [cs.DM]Compact Redistricting Plans Have Many Spanning Trees
Ariel D. Procaccia, Jamie Tucker-Foltz
http://arxiv.org/abs/2109.13394v1

• [cs.GT]Equilibria and learning dynamics in mixed network coordination/anti-coordination games
Laura Arditti, Giacomo Como, Fabio Fagnani, Martina Vanelli
http://arxiv.org/abs/2109.12692v2

• [cs.GT]Learning Attacker’s Bounded Rationality Model in Security Games
Adam Żychowski, Jacek Mańdziuk
http://arxiv.org/abs/2109.13036v1

• [cs.HC]Intelligent Decision Assistance Versus Automated Decision-Making: Enhancing Knowledge Work Through Explainable Artificial Intelligence
Max Schemmer, Niklas Kühl, Gerhard Satzger
http://arxiv.org/abs/2109.13827v1

• [cs.HC]Opportunistic Implicit User Authentication for Health-Tracking IoT Wearables
Alexa Muratyan, William Cheung, Sayanton V. Dibbo, Sudip Vhaduri
http://arxiv.org/abs/2109.13705v1

• [cs.HC]Trustworthy AI and Robotics and the Implications for the AEC Industry: A Systematic Literature Review and Future Potentials
Newsha Emaminejad, Reza Akhavian
http://arxiv.org/abs/2109.13373v1

• [cs.IR]Concept-Aware Denoising Graph Neural Network for Micro-Video Recommendation
Yiyu Liu, Qian Liu, Yu Tian, Changping Wang, Yanan Niu, Yang Song, Chenliang Li
http://arxiv.org/abs/2109.13527v1

• [cs.IR]Exploring The Role of Local and Global Explanations in Recommender Systems
Marissa Radensky, Doug Downey, Kyle Lo, Zoran Popović, Daniel S. Weld
http://arxiv.org/abs/2109.13301v1

• [cs.IR]Synerise at RecSys 2021: Twitter user engagement prediction with a fast neural model
Michał Daniluk, Jacek Dąbrowski, Barbara Rychalska, Konrad Gołuchowski
http://arxiv.org/abs/2109.12985v2

• [cs.IR]The eDiscovery Medicine Show
Maura R. Grossman, Gordon V. Cormack
http://arxiv.org/abs/2109.13908v1

• [cs.IT]An Open Problem on the Bentness of Mesnager’s Functions
Chunming Tang, Peng Han, Qi Wang, Jun Zhang, Yanfeng Qi
http://arxiv.org/abs/2109.13421v1

• [cs.IT]An extended Krylov subspace method for decoding edge-based compressed images by homogeneous diffusion
Volker Grimm, Kevin Liang
http://arxiv.org/abs/2109.13607v1

• [cs.IT]Extended Irreducible Binary Sextic Goppa codes
Daitao Huang, Qin Yue
http://arxiv.org/abs/2109.13413v1

• [cs.IT]Intelligent Reflecting Surface Aided Wireless Networks: From Single-Reflection to Multi-Reflection Design and Optimization
Weidong Mei, Beixiong Zheng, Changsheng You, Rui Zhang
http://arxiv.org/abs/2109.13641v1

• [cs.IT]Millimeter Wave and Terahertz Urban Microcell Propagation Measurements and Models
Yunchou Xing, Theodore S. Rappaport
http://arxiv.org/abs/2109.13404v1

• [cs.IT]New Interleaving Constructions of Asymptotically Optimal Periodic Quasi-Complementary Sequence Sets
Gaojun Luo, Martianus Frederic Ezerman, San Ling
http://arxiv.org/abs/2109.13697v1

• [cs.IT]On Joint Detection and Decoding in Short-Packet Communications
Alejandro Lancho, Johan Östman, Giuseppe Durisi
http://arxiv.org/abs/2109.13669v1

• [cs.IT]The $今日学术视野(2021.9.30) - 图5$ -ary antiprimitive BCH codes
Hongwei Zhu, Minjia Shi, Xiaoqiang Wang, Tor Helleseth
http://arxiv.org/abs/2109.13803v1

• [cs.IT]Three New Infinite Families of Optimal Locally Repairable Codes from Matrix-Product Codes
Gaojun Luo, Martianus Frederic Ezerman, San Ling
http://arxiv.org/abs/2109.13692v1

• [cs.IT]Two-Stage Channel Estimation Approach for Cell-Free IoT With Massive Random Access
Xinhua Wang, Alexei Ashikhmin, Zhicheng Dong, Chao Zhai
http://arxiv.org/abs/2109.13450v1

• [cs.IT]Weighted Secrecy Coverage Analysis and the Impact of Friendly Jamming over UAV-Enabled Networks
X. A. Flores Cabezas, D. P. Moya Osorio, M. Latva-aho
http://arxiv.org/abs/2109.13629v1

• [cs.LG]A First-Occupancy Representation for Reinforcement Learning
Ted Moskovitz, Spencer R. Wilson, Maneesh Sahani
http://arxiv.org/abs/2109.13863v1

• [cs.LG]A PAC-Bayesian Analysis of Distance-Based Classifiers: Why Nearest-Neighbour works!
Thore Graepel, Ralf Herbrich
http://arxiv.org/abs/2109.13889v1

• [cs.LG]A multi-stage semi-supervised improved deep embedded clustering (MS-SSIDEC) method for bearing fault diagnosis under the situation of insufficient labeled samples
Tongda Sun, Gang Yu
http://arxiv.org/abs/2109.13521v1

• [cs.LG]An Adaptive Deep Learning Framework for Day-ahead Forecasting of Photovoltaic Power Generation
Xing Luo, Dongxiao Zhang
http://arxiv.org/abs/2109.13442v1

• [cs.LG]An Automated Data Engineering Pipeline for Anomaly Detection of IoT Sensor Data
Xinze Li, Baixi Zou
http://arxiv.org/abs/2109.13828v1

• [cs.LG]Anomaly Detection for High-Dimensional Data Using Large Deviations Principle
Sreelekha Guggilam, Varun Chandola, Abani Patra
http://arxiv.org/abs/2109.13698v1

• [cs.LG]Automated Estimation of Construction Equipment Emission using Inertial Sensors and Machine Learning Models
Farid Shahnavaz, Reza Akhavian
http://arxiv.org/abs/2109.13375v1

• [cs.LG]Bayesian Transfer Learning: An Overview of Probabilistic Graphical Models for Transfer Learning
Junyu Xuan, Jie Lu, Guangquan Zhang
http://arxiv.org/abs/2109.13233v1

• [cs.LG]Cluster Analysis of a Symbolic Regression Search Space
Gabriel Kronberger, Lukas Kammerer, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller
http://arxiv.org/abs/2109.13898v1

• [cs.LG]Clustering to the Fewest Clusters Under Intra-Cluster Dissimilarity Constraints
Jennie Andersen, Brice Chardin, Mohamed Tribak
http://arxiv.org/abs/2109.13644v1

• [cs.LG]Confusion-based rank similarity filters for computationally-efficient machine learning on high dimensional data
Katharine A. Shapcott, Alex D. Bird
http://arxiv.org/abs/2109.13610v1

• [cs.LG]Convergence of Deep Convolutional Neural Networks
Yuesheng Xu, Haizhang Zhang
http://arxiv.org/abs/2109.13542v1

• [cs.LG]DEBOSH: Deep Bayesian Shape Optimization
Nikita Durasov, Artem Lukoyanov, Jonathan Donier, Pascal Fua
http://arxiv.org/abs/2109.13337v1

• [cs.LG]DOODLER: Determining Out-Of-Distribution Likelihood from Encoder Reconstructions
Jonathan S. Kent, Bo Li
http://arxiv.org/abs/2109.13237v1

• [cs.LG]Deep Reinforcement Learning with Adjustments
Hamed Khorasgani, Haiyan Wang, Chetan Gupta, Susumu Serita
http://arxiv.org/abs/2109.13463v1

• [cs.LG]Delve into the Performance Degradation of Differentiable Architecture Search
Jiuling Zhang, Zhiming Ding
http://arxiv.org/abs/2109.13466v1

• [cs.LG]Discriminative Attribution from Counterfactuals
Nils Eckstein, Alexander S. Bates, Gregory S. X. E. Jefferis, Jan Funke
http://arxiv.org/abs/2109.13412v1

• [cs.LG]DynG2G: An Efficient Stochastic Graph Embedding Method for Temporal Graphs
Mengjia Xu, Apoorva Vikram Singh, George Em Karniadakis
http://arxiv.org/abs/2109.13441v1

• [cs.LG]Exploratory State Representation Learning
Astrid Merckling, Nicolas Perrin-Gilbert, Alexandre Coninx, Stéphane Doncieux
http://arxiv.org/abs/2109.13596v1

• [cs.LG]Exploring More When It Needs in Deep Reinforcement Learning
Youtian Guo, Qi Gao
http://arxiv.org/abs/2109.13477v1

• [cs.LG]Exposing Paid Opinion Manipulation Trolls
Todor Mihaylov, Ivan Koychev, Georgi Georgiev, Preslav Nakov
http://arxiv.org/abs/2109.13726v1

• [cs.LG]FedIPR: Ownership Verification for Federated Deep Neural Network Models
Lixin Fan, Bowen Li, Hanlin Gu, Jie Li, Qiang Yang
http://arxiv.org/abs/2109.13236v1

• [cs.LG]IGAN: Inferent and Generative Adversarial Networks
Dr. Luc Vignaud
http://arxiv.org/abs/2109.13360v1

• [cs.LG]Improving Time Series Classification Algorithms Using Octave-Convolutional Layers
Samuel Harford, Fazle Karim, Houshang Darabi
http://arxiv.org/abs/2109.13696v1

• [cs.LG]Introducing the viewpoint in the resource description using machine learning
Ouahiba Djama
http://arxiv.org/abs/2109.13306v1

• [cs.LG]Learning from Small Samples: Transformation-Invariant SVMs with Composition and Locality at Multiple Scales
Tao Liu, P. R. Kumar, Xi Liu
http://arxiv.org/abs/2109.12784v2

• [cs.LG]Learning to Superoptimize Real-world Programs
Alex Shypula, Pengcheng Yin, Jeremy Lacomis, Claire Le Goues, Edward Schwartz, Graham Neubig
http://arxiv.org/abs/2109.13498v1

• [cs.LG]Lithium-ion Battery State of Health Estimation based on Cycle Synchronization using Dynamic Time Warping
Kate Qi Zhou, Yan Qin, Billy Pik Lik Lau, Chau Yuen, Stefan Adams
http://arxiv.org/abs/2109.13448v1

• [cs.LG]Lyapunov-Net: A Deep Neural Network Architecture for Lyapunov Function Approximation
Nathan Gaby, Fumin Zhang, Xiaojing Ye
http://arxiv.org/abs/2109.13359v1

• [cs.LG]Machine learning methods for prediction of cancer driver genes: a survey paper
Renan Andrades, Mariana Recamonde-Mendoza
http://arxiv.org/abs/2109.13685v1

• [cs.LG]Making Curiosity Explicit in Vision-based RL
Elie Aljalbout, Maximilian Ulmer, Rudolph Triebel
http://arxiv.org/abs/2109.13588v1

• [cs.LG]Multimodality in Meta-Learning: A Comprehensive Survey
Yao Ma, Shilin Zhao, Weixiao Wang, Yaoman Li, Irwin King
http://arxiv.org/abs/2109.13576v1

• [cs.LG]Multiwavelet-based Operator Learning for Differential Equations
Gaurav Gupta, Xiongye Xiao, Paul Bogdan
http://arxiv.org/abs/2109.13459v1

• [cs.LG]Near-Linear Time Algorithm with Near-Logarithmic Regret Per Switch for Mixable/Exp-Concave Losses
Kaan Gokcesu, Hakan Gokcesu
http://arxiv.org/abs/2109.13786v1

• [cs.LG]Physics-Augmented Learning: A New Paradigm Beyond Physics-Informed Learning
Ziming Liu, Yunyue Chen, Yuanqi Du, Max Tegmark
http://arxiv.org/abs/2109.13901v1

• [cs.LG]Probabilistic modeling of lake surface water temperature using a Bayesian spatio-temporal graph convolutional neural network
Michael Stalder, Firat Ozdemir, Artur Safin, Jonas Sukys, Damien Bouffard, Fernando Perez-Cruz
http://arxiv.org/abs/2109.13235v1

• [cs.LG]Reinforcement Learning for Quantitative Trading
Shuo Sun, Rundong Wang, Bo An
http://arxiv.org/abs/2109.13851v1

• [cs.LG]ST-MAML: A Stochastic-Task based Method for Task-Heterogeneous Meta-Learning
Zhe Wang, Jake Grigsby, Arshdeep Sekhon, Yanjun Qi
http://arxiv.org/abs/2109.13305v1

• [cs.LG]Symbolic Regression by Exhaustive Search: Reducing the Search Space Using Syntactical Constraints and Efficient Semantic Structure Deduplication
Lukas Kammerer, Gabriel Kronberger, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller
http://arxiv.org/abs/2109.13895v1

• [cs.LG]The Fragility of Optimized Bandit Algorithms
Lin Fan, Peter W. Glynn
http://arxiv.org/abs/2109.13595v1

• [cs.LG]The Role of Lookahead and Approximate Policy Evaluation in Policy Iteration with Linear Value Function Approximation
Anna Winnicki, Joseph Lubars, Michael Livesay, R. Srikant
http://arxiv.org/abs/2109.13419v1

• [cs.LG]Unrolling SGD: Understanding Factors Influencing Machine Unlearning
Anvith Thudi, Gabriel Deza, Varun Chandrasekaran, Nicolas Papernot
http://arxiv.org/abs/2109.13398v1

• [cs.LG]Unsolved Problems in ML Safety
Dan Hendrycks, Nicholas Carlini, John Schulman, Jacob Steinhardt
http://arxiv.org/abs/2109.13916v1

• [cs.LG]VoxCeleb Enrichment for Age and Gender Recognition
Khaled Hechmi, Trung Ngo Trong, Ville Hautamaki, Tomi Kinnunen
http://arxiv.org/abs/2109.13510v1

• [cs.LG]What to Prioritize? Natural Language Processing for the Development of a Modern Bug Tracking Solution in Hardware Development
Thi Thu Hang Do, Markus Dobler, Niklas Kühl
http://arxiv.org/abs/2109.13825v1

• [cs.LG]When in Doubt: Improving Classification Performance with Alternating Normalization
Menglin Jia, Austin Reiter, Ser-Nam Lim, Yoav Artzi, Claire Cardie
http://arxiv.org/abs/2109.13449v1

• [cs.MM]Audio-to-Image Cross-Modal Generation
Maciej Żelaszczyk, Jacek Mańdziuk
http://arxiv.org/abs/2109.13354v1

• [cs.NE]Extensible Logging and Empirical Attainment Function for IOHexperimenter
Johann Dreo, Manuel Lopez-Ibanez
http://arxiv.org/abs/2109.13773v1

• [cs.NE]Faster Improvement Rate Population Based Training
Valentin Dalibard, Max Jaderberg
http://arxiv.org/abs/2109.13800v1

• [cs.NE]Half a Dozen Real-World Applications of Evolutionary Multitasking and More
Abhishek Gupta, Lei Zhou, Yew-Soon Ong, Zefeng Chen, Yaqing Hou
http://arxiv.org/abs/2109.13101v2

• [cs.RO]Adaptive Informative Path Planning Using Deep Reinforcement Learning for UAV-based Active Sensing
Julius Rückin, Liren Jin, Marija Popović
http://arxiv.org/abs/2109.13570v1

• [cs.RO]Affordance Template Registration via Human-in-the-loop Corrections
Michael Hagenow, Michael Zinn, Terrence Fong, Evan Laske, Kimberly Hambuchen
http://arxiv.org/abs/2109.13649v1

• [cs.RO]Bimanual Telemanipulation with Force and Haptic Feedback and Predictive Limit Avoidance
Christian Lenz, Sven Behnke
http://arxiv.org/abs/2109.13382v1

• [cs.RO]Bottom-Up Skill Discovery from Unsegmented Demonstrations for Long-Horizon Robot Manipulation
Yifeng Zhu, Peter Stone, Yuke Zhu
http://arxiv.org/abs/2109.13841v1

• [cs.RO]Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets
Frederik Ebert, Yanlai Yang, Karl Schmeckpeper, Bernadette Bucher, Georgios Georgakis, Kostas Daniilidis, Chelsea Finn, Sergey Levine
http://arxiv.org/abs/2109.13396v1

• [cs.RO]CRANE: a 10 Degree-of-Freedom, Tele-surgical System for Dexterous Manipulation within Imaging Bores
Dimitri A. Schreiber, Zhaowei Yu, Hanpeng Jiang, Alexander M. Norbash, Michael C. Yip
http://arxiv.org/abs/2109.13407v1

• [cs.RO]Control Barrier Functions for Singularity Avoidance in Passivity-Based Manipulator Control
Vince Kurtz, Patrick M. Wensing, Hai Lin
http://arxiv.org/abs/2109.13349v1

• [cs.RO]Cooperative Object Transportation using Gibbs Random Fields
Paulo Rezeck, Renato M. Assunção, Luiz Chaimowicz
http://arxiv.org/abs/2109.13734v1

• [cs.RO]Designed to Cooperate: A Kant-Inspired Ethic of Machine-to-Machine Cooperation
Seng W. Loke
http://arxiv.org/abs/2109.13493v1

• [cs.RO]Interactive Dynamic Walking: Learning Gait Switching Policies with Generalization Guarantees
Prem Chand, Sushant Veer, Ioannis Poulakakis
http://arxiv.org/abs/2109.13417v1

• [cs.RO]Literature Review on Endoscopic Robotic Systems in Ear and Sinus Surgery
Guillaume Michel, Durgesh Haribhau Salunkhe, Philippe Bordure, Damien Chablat
http://arxiv.org/abs/2109.13661v1

• [cs.RO]Meta Reinforcement Learning Based Sensor Scanning in 3D Uncertain Environments for Heterogeneous Multi-Robot Systems
Junfeng Chen, Yuan Gao, Junjie Hu, Fuqin Deng, Tin Lun Lam
http://arxiv.org/abs/2109.13617v1

• [cs.RO]Model-based Motion Imitation for Agile, Diverse and Generalizable Quadupedal Locomotion
Tianyu Li, Jungdam Won, Sehoon Ha, Akshara Rai
http://arxiv.org/abs/2109.13362v1

• [cs.RO]Multiple-Pilot Collaboration for Advanced Remote Intervention using Reinforcement Learning
Ziwei Wang, Weibang Bai, Zhang Chen, Bo Xiao, Bin Liang, Eric M. Yeatman
http://arxiv.org/abs/2109.13324v1

• [cs.RO]NimbRo Avatar: Interactive Immersive Telepresence with Force-Feedback Telemanipulation
Max Schwarz, Christian Lenz, Andre Rochow, Michael Schreiber, Sven Behnke
http://arxiv.org/abs/2109.13772v1

• [cs.RO]Not Only Domain Randomization: Universal Policy with Embedding System Identification
Zihan Ding
http://arxiv.org/abs/2109.13438v1

• [cs.RO]On the Empirical Evaluation of Information Gain Criteria for Active Action Selection
Prajval Kumar Murali, Mohsen Kaboli
http://arxiv.org/abs/2109.13540v1

• [cs.RO]Online Object Model Reconstruction and Reuse for Lifelong Improvement of Robot Manipulation
Shiyang Lu, Rui Wang, Yinglong Miao, Chaitanya Mitash, Kostas Bekris
http://arxiv.org/abs/2109.13910v1

• [cs.RO]Runtime Safety Assurance
1000
for Learning-enabled Control of Autonomous Driving Vehicles
Shengduo Chen, Yaowei Sun, Dachuan Li, Qiang Wang, Qi Hao, Joseph Sifakis
http://arxiv.org/abs/2109.13446v1

• [cs.RO]SafetyNet: Safe planning for real-world self-driving vehicles using machine-learned policies
Matt Vitelli, Yan Chang, Yawei Ye, Maciej Wołczyk, Błażej Osiński, Moritz Niendorf, Hugo Grimmett, Qiangui Huang, Ashesh Jain, Peter Ondruska
http://arxiv.org/abs/2109.13602v1

• [cs.RO]Scan Context++: Structural Place Recognition Robust to Rotation and Lateral Variations in Urban Environments
Giseop Kim, Sunwook Choi, Ayoung Kim
http://arxiv.org/abs/2109.13494v1

• [cs.RO]Solving Challenging Control Problems Using Two-Staged Deep Reinforcement Learning
Nitish Sontakke, Sehoon Ha
http://arxiv.org/abs/2109.13338v1

• [cs.RO]Targetless Extrinsic Calibration of Stereo Cameras, Thermal Cameras, and Laser Sensors in the Wild
Taimeng Fu, Huai Yu, Yaoyu Hu, Sebastian Scherer
http://arxiv.org/abs/2109.13414v1

• [cs.RO]Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradients
Oliver Scheel, Luca Bergamini, Maciej Wołczyk, Błażej Osiński, Peter Ondruska
http://arxiv.org/abs/2109.13333v1

• [cs.SD]Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme
Vadim Popov, Ivan Vovk, Vladimir Gogoryan, Tasnima Sadekova, Mikhail Kudinov, Jiansheng Wei
http://arxiv.org/abs/2109.13821v1

• [cs.SI]Exploring the spatiotemporal heterogeneity in the relationship between human mobility and COVID-19 prevalence using dynamic time warping
Hoeyun Kwon, Kaitlyn Hom, Mark Rifkin, Beichen Tian, Caglar Koylu
http://arxiv.org/abs/2109.13765v1

• [cs.SI]Extracting Attentive Social Temporal Excitation for Sequential Recommendation
Yunzhe Li, Yue Ding, Bo Chen, Xin Xin, Yule Wang, Yuxiang Shi, Ruiming Tang, Dong Wang
http://arxiv.org/abs/2109.13539v1

• [cs.SI]Fake News Detection using Semi-Supervised Graph Convolutional Network
Priyanka Meel, Dinesh Kumar Vishwakarma
http://arxiv.org/abs/2109.13476v1

• [cs.SI]Learning Ideological Embeddings from Information Cascades
Corrado Monti, Giuseppe Manco, Cigdem Aslay, Francesco Bonchi
http://arxiv.org/abs/2109.13589v1

• [cs.SI]Success at high peaks: a multiscale approach combining individual and expedition-wide factors
Sanjukta Krishnagopal
http://arxiv.org/abs/2109.13340v1

• [econ.EM]Gaussian and Student’s $今日学术视野(2021.9.30) - 图6$ mixture vector autoregressive model
Savi Virolainen
http://arxiv.org/abs/2109.13648v1

• [econ.EM]Macroeconomic forecasting with LSTM and mixed frequency time series data
Sarun Kamolthip
http://arxiv.org/abs/2109.13777v1

• [econ.EM]bqror: An R package for Bayesian Quantile Regression in Ordinal Models
Prajual Maheshwari, Mohammad Arshad Rahman
http://arxiv.org/abs/2109.13606v1

• [eess.AS]The JHU submission to VoxSRC-21: Track 3
Jejin Cho, Jesus Villalba, Najim Dehak
http://arxiv.org/abs/2109.13425v1

• [eess.IV]Metal Artifact Reduction in 2D CT Images with Self-supervised Cross-domain Learning
Lequan Yu, Zhicheng Zhang, Xiaomeng Li, Hongyi Ren, Wei Zhao, Lei Xing
http://arxiv.org/abs/2109.13483v1

• [eess.IV]Real-Time Glaucoma Detection from Digital Fundus Images using Self-ONNs
Ozer Can Devecioglu, Junaid Malik, Turker Ince, Serkan Kiranyaz, Eray Atalay, Moncef Gabbouj
http://arxiv.org/abs/2109.13604v1

• [eess.IV]Unsupervised Diffeomorphic Surface Registration and Non-Linear Modelling
Balder Croquet, Daan Christiaens, Seth M. Weinberg, Michael Bronstein, Dirk Vandermeulen, Peter Claes
http://arxiv.org/abs/2109.13630v1

• [eess.SP]Index Modulation with Circularly-Shifted Chirps for Dual-Function Radar and Communications
Alphan Sahin, Safi Shams Muhtasimul Hoque, Chao-Yu Chen
http://arxiv.org/abs/2109.13865v1

• [eess.SP]Transfer Learning based Evolutionary Deep Neural Network for Intelligent Fault Diagnosis
Arun K. Sharma, Nishchal K. Verma
http://arxiv.org/abs/2109.13479v1

• [eess.SY]DeepPSL: End-to-end perception and reasoning with applications to zero shot learning
Nigel Duffy, Sai Akhil Puranam, Sridhar Dasaratha, Karmvir Singh Phogat, Sunil Reddy Tiyyagura
http://arxiv.org/abs/2109.13662v1

• [eess.SY]Model-Free Reinforcement Learning for Optimal Control of MarkovDecision Processes Under Signal Temporal Logic Specifications
Krishna C. Kalagarla, Rahul Jain, Pierluigi Nuzzo
http://arxiv.org/abs/2109.13377v1

• [hep-th]The edge of chaos: quantum field theory and deep neural networks
Kevin T. Grosvenor, Ro Jefferson
http://arxiv.org/abs/2109.13247v1

• [math.CO]Multiple contractions of permutation arrays
Carmen Amarra, Dom Vito A. Briones, Manuel Joseph C. Loquias
http://arxiv.org/abs/2109.13585v1

• [math.PR]Perturbation theory for killed Markov processes and quasi-stationary distributions
Daniel Rudolf, Andi Q. Wang
http://arxiv.org/abs/2109.13819v1

• [math.ST]A functional central limit theorem for the empirical Ripley’s K-function
Christophe A. N. Biscio, Anne Marie Svane
http://arxiv.org/abs/2109.13741v1

• [math.ST]An exact test for significance of clusters in binary data
James Mathews, Cameron Crowe, Rami Vanguri, Margaret Callahan, Travis Hollmann, Saad Nadeem
http://arxiv.org/abs/2109.13876v1

• [math.ST]Dynamic Ranking with the BTL Model: A Nearest Neighbor based Rank Centrality Method
Eglantine Karlé, Hemant Tyagi
http://arxiv.org/abs/2109.13743v1

• [math.ST]Fairness guarantee in multi-class classification
Christophe Denis, Romuald Elie, Mohamed Hebiri, François Hu
http://arxiv.org/abs/2109.13642v1

• [math.ST]On eigenvalues of a high dimensional Kendall’s rank correlation matrix with dependences
Cheng Wang, Qinwen Wang, Zeng Li
http://arxiv.org/abs/2109.13624v1

• [math.ST]Optimal Orthogonal Group Synchronization and Rotation Group Synchronization
Chao Gao, Anderson Y. Zhang
http://arxiv.org/abs/2109.13491v1

• [math.ST]Sharp multiple testing boundary for sparse sequences
Kweku Abraham, Ismael Castillo, Etienne Roquain
http://arxiv.org/abs/2109.13601v1

• [math.ST]Simulation of non-stationary and non-Gaussian random processes by 3rd-order Spectral Representation Method: Theory and POD implementation
Lohit Vandanapu, Michael D. Shields
http://arxiv.org/abs/2109.13689v1

• [math.ST]Statistical inference for function-on-function linear regression
Holger Dette, Jiajun Tang
http://arxiv.org/abs/2109.13603v1

• [physics.data-an]Grassmannian diffusion maps based surrogate modeling via geometric harmonics
Ketson R. M. dos Santos, Dimitrios G. Giovanis, Katiana Kontolati, Dimitrios Loukrezis, Michael D. Shields
http://arxiv.org/abs/2109.13805v1

• [physics.geo-ph]1D Stochastic Inversion of Airborne Time-domain Electromag-netic Data with Realistic Prior and Accounting for the Forward Modeling Error
Peng Bai, Giulio Vignoli, Thomas Mejer Hansen
http://arxiv.org/abs/2109.13780v1

• [physics.soc-ph]UEFA could have easily improved the fairness of the European Qualifiers to the 2022 FIFA World Cup
László Csató, Dezső Bednay
http://arxiv.org/abs/2109.13785v1

• [q-bio.NC]Text2Brain: Synthesis of Brain Activation Maps from Free-form Text Query
Gia H. Ngo, Minh Nguyen, Nancy F. Chen, Mert R. Sabuncu
http://arxiv.org/abs/2109.13814v1

• [q-bio.NC]Towards a Governance Framework for Brain Data
Marcello Ienca, Joseph J. Fins, Ralf J. Jox, Fabrice Jotterand, Silja Voeneky, Roberto Andorno, Tonio Ball, Claude Castelluccia, Ricardo Chavarriaga, Hervé Chneiweiss, Agata Ferretti, Orsolya Friedrich, Samia Hurst, Grischa Merkel, Fruzsina Molnar-Gabor, Jean-Marc Rickli, James Scheibner, Effy Vayena, Rafael Yuste, Philipp Kellmeyer
http://arxiv.org/abs/2109.11960v2

• [q-fin.ST]Intra-Day Price Simulation with Generative Adversarial Modelling of the Order Flow
Ye-Sheen Lim, Denise Gorse
http://arxiv.org/abs/2109.13905v1

• [quant-ph]Design of quantum optical experiments with logic artificial intelligence
Alba Cervera-Lierta, Mario Krenn, Alán Aspuru-Guzik
http://arxiv.org/abs/2109.13273v1

• [quant-ph]Optimal Simulation of Quantum Measurements via the Likelihood POVMs
Arun Padakandla
http://arxiv.org/abs/2109.12586v2

• [stat.AP]Disentangling positive and negative partisanship in affective polarization using a coevolving latent space network with attractors model
Xiaojing Zhu, Cantay Caliskan, Dino P. Christenson, Konstantinos Spiliopoulos, Dylan Walker, Eric D. Kolaczyk
http://arxiv.org/abs/2109.13129v2

• [stat.ME]ALL-IN meta-analysis: breathing life into living systematic reviews
Judith ter Schure, Peter Grünwald
http://arxiv.org/abs/2109.12141v1

• [stat.ME]An Automated Approach to Causal Inference in Discrete Settings
Guilherme Duarte, Noam Finkelstein, Dean Knox, Jonathan Mummolo, Ilya Shpitser
http://arxiv.org/abs/2109.13471v1

• [stat.ME]Analysis and Methods to Mitigate Effects of Under-reporting in Count Data
Jennifer Brennan, Marlena Bannick, Nicholas Kassebaum, Lauren Wilner, Azalea Thomson, Aleksandr Aravkin, Peng Zheng
http://arxiv.org/abs/2109.12247v2

• [stat.ME]Assessing Outcome-to-Outcome Interference in Sibling Fixed Effects Models
David C. Mallinson
http://arxiv.org/abs/2109.13399v1

• [stat.ME]Conditional Cross-Design Synthesis Estimators for Generalizability in Medicaid
Irina Degtiar, Tim Layton, Jacob Wallace, Sherri Rose
http://arxiv.org/abs/2109.13288v1

• [stat.ME]Heterogeneous Distributed Lag Models to Estimate Personalized Effects of Maternal Exposures to Air Pollution
Daniel Mork, Marianthi-Anna Kioumourtzoglou, Marc Weisskopf, Brent A Coull, Ander Wilson
http://arxiv.org/abs/2109.13763v1

• [stat.ME]Identification of the Heterogeneous Survivor Average Causal Effect in Observational Studies
Yuhao Deng, Yuhang Guo, Yingjun Chang, Xiao-Hua Zhou
http://arxiv.org/abs/2109.13623v1

• [stat.ME]Interoperability of statistical models in pandemic preparedness: principles and reality
George Nicholson, Marta Blangiardo, Mark Briers, Peter J. Diggle, Tor Erlend Fjelde, Hong Ge, Robert J. B. Goudie, Radka Jersakova, Ruairidh E. King, Brieuc C. L. Lehmann, Ann-Marie Mallon, Tullia Padellini, Yee Whye Teh, Chris Holmes, Sylvia Richardson
http://arxiv.org/abs/2109.13730v1

• [stat.ME]Joint marginal structural models to estimate the causal effects of multiple longitudinal treatments in continuous time with application to COVID-19
Liangyuan Hu, Fan Li, Jiayi Ji, Himanshu Joshi, Erick Scott
http://arxiv.org/abs/2109.13368v1

• [stat.ME]Variance partitioning in spatio-temporal disease mapping models
M. Franco-Villoria, M. Ventrucci, H. Rue
http://arxiv.org/abs/2109.13374v1

• [stat.ML]Contributions to Large Scale Bayesian Inference and Adversarial Machine Learning
Víctor Gallego
http://arxiv.org/abs/2109.13232v1

• [stat.ML]Gaussian Processes to speed up MCMC with automatic exploratory-exploitation effect
Alessio Benavoli, Jason Wyse, Arthur White
http://arxiv.org/abs/2109.13891v1

• [stat.ML]Improved prediction rule ensembling through model-based data generation
Benny Markovitch, Marjolein Fokkema
http://arxiv.org/abs/2109.13672v1