cond-mat.stat-mech - 统计数学
    cs.AI - 人工智能
    cs.AR - 硬件体系结构
    cs.CL - 计算与语言
    cs.CR - 加密与安全
    cs.CV - 机器视觉与模式识别
    cs.CY - 计算与社会
    cs.DC - 分布式、并行与集群计算
    cs.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.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.NA - 数值分析
    math.ST - 统计理论
    physics.flu-dyn - 流体动力学
    physics.soc-ph - 物理学与社会
    stat.AP - 应用统计
    stat.ME - 统计方法论
    stat.ML - (统计)机器学习

    • [cond-mat.stat-mech]The typical set and entropy in stochastic systems with arbitrary phase space growth
    • [cs.AI]A brief history of AI: how to prevent another winter (a critical review)
    • [cs.AI]An Oracle and Observations for the OpenAI Gym / ALE Freeway Environment
    • [cs.AI]CX-ToM: Counterfactual Explanations with Theory-of-Mind for Enhancing Human Trust in Image Recognition Models
    • [cs.AI]Efficient Communication in Multi-Agent Distributed Reinforcement Learning
    • [cs.AI]Integration of Data and Theory for Accelerated Derivable Symbolic Discovery
    • [cs.AI]Multi-Agent Inverse Reinforcement Learning: Suboptimal Demonstrations and Alternative Solution Concepts
    • [cs.AI]Situated Conditional Reasoning
    • [cs.AI]Symbol Emergence and The Solutions to Any Task
    • [cs.AR]On the Accuracy of Analog Neural Network Inference Accelerators
    • [cs.CL]A Context-Aware Hierarchical BERT Fusion Network for Multi-turn Dialog Act Detection
    • [cs.CL]A Longitudinal Multi-modal Dataset for Dementia Monitoring and Diagnosis
    • [cs.CL]An Empirical Study on Leveraging Position Embeddings for Target-oriented Opinion Words Extraction
    • [cs.CL]An Exploratory Study on Utilising the Web of Linked Data for Product Data Mining
    • [cs.CL]An Open-Source Dataset and A Multi-Task Model for Malay Named Entity Recognition
    • [cs.CL]CREAK: A Dataset for Commonsense Reasoning over Entity Knowledge
    • [cs.CL]Challenges in Generalization in Open Domain Question Answering
    • [cs.CL]Contextualized Embeddings based Convolutional Neural Networks for Duplicate Question Identification
    • [cs.CL]Contrastive Representation Learning for Exemplar-Guided Paraphrase Generation
    • [cs.CL]Cross-Lingual Training with Dense Retrieval for Document Retrieval
    • [cs.CL]Detecting Speaker Personas from Conversational Texts
    • [cs.CL]Do Prompt-Based Models Really Understand the Meaning of their Prompts?
    • [cs.CL]Empirical Study of Named Entity Recognition Performance Using Distribution-aware Word Embedding
    • [cs.CL]Entity Linking and Discovery via Arborescence-based Supervised Clustering
    • [cs.CL]Establishing Interlingua in Multilingual Language Models
    • [cs.CL]Finetuned Language Models Are Zero-Shot Learners
    • [cs.CL]Indexing Context-Sensitive Reachability
    • [cs.CL]Language Modeling, Lexical Translation, Reordering: The Training Process of NMT through the Lens of Classical SMT
    • [cs.CL]Learning Neural Models for Natural Language Processing in the Face of Distributional Shift
    • [cs.CL]Learning from Multiple Noisy Augmented Data Sets for Better Cross-Lingual Spoken Language Understanding
    • [cs.CL]Multimodal Conditionality for Natural Language Generation
    • [cs.CL]Quantifying Reproducibility in NLP and ML
    • [cs.CL]Ranking Scientific Papers Using Preference Learning
    • [cs.CL]So Cloze yet so Far: N400 Amplitude is Better Predicted by Distributional Information than Human Predictability Judgements
    • [cs.CR]A Synergetic Attack against Neural Network Classifiers combining Backdoor and Adversarial Examples
    • [cs.CR]Ontology-driven Knowledge Graph for Android Malware
    • [cs.CV]3D Human Shape Style Transfer
    • [cs.CV]Access Control Using Spatially Invariant Permutation of Feature Maps for Semantic Segmentation Models
    • [cs.CV]CAP-Net: Correspondence-Aware Point-view Fusion Network for 3D Shape Analysis
    • [cs.CV]Deep Learning for Fitness
    • [cs.CV]Deep Metric Learning for Ground Images
    • [cs.CV]Dual-Camera Super-Resolution with Aligned Attention Modules
    • [cs.CV]Ghost Loss to Question the Reliability of Training Data
    • [cs.CV]Information Symmetry Matters: A Modal-Alternating Propagation Network for Few-Shot Learning
    • [cs.CV]MitoVis: A Visually-guided Interactive Intelligent System for Neuronal Mitochondria Analysis
    • [cs.CV]Model-Based Parameter Optimization for Ground Texture Based Localization Methods
    • [cs.CV]Neural Human Deformation Transfer
    • [cs.CV]Occlusion-Invariant Rotation-Equivariant Semi-Supervised Depth Based Cross-View Gait Pose Estimation
    • [cs.CV]Optimal Target Shape for LiDAR Pose Estimation
    • [cs.CV]Ordinal Pooling
    • [cs.CV]Representing Shape Collections with Alignment-Aware Linear Models
    • [cs.CV]Safety-aware Motion Prediction with Unseen Vehicles for Autonomous Driving
    • [cs.CV]Segmentation of turbulent computational fluid dynamics simulations with unsupervised ensemble learning
    • [cs.CV]Self-Taught Cross-Domain Few-Shot Learning with Weakly Supervised Object Localization and Task-Decomposition
    • [cs.CV]Semantic Segmentation on VSPW Dataset through Aggregation of Transformer Models
    • [cs.CV]Spatially varying white balancing for mixed and non-uniform illuminants
    • [cs.CV]Towards Learning Spatially Discriminative Feature Representations
    • [cs.CV]UnDeepLIO: Unsupervised Deep Lidar-Inertial Odometry
    • [cs.CV]Using Topological Framework for the Design of Activation Function and Model Pruning in Deep Neural Networks
    • [cs.CV]Video Pose Distillation for Few-Shot, Fine-Grained Sports Action Recognition
    • [cs.CV]Wildfire smoke plume segmentation using geostationary satellite imagery
    • [cs.CY]Hide and seek in Slovakia: utilizing tracking code data to uncover untrustworthy website networks
    • [cs.CY]Proceedings of KDD 2021 Workshop on Data-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resilience Planning
    • [cs.DC]A Reliable, Self-Adaptive Face Identification Framework via Lyapunov Optimization
    • [cs.DC]A Study of Mixed Precision Strategies for GMRES on GPUs
    • [cs.DC]Achieving near native runtime performance and cross-platform performance portability for random number generation through SYCL interoperability
    • [cs.DC]Byzantine Consensus in Directed Hypergraphs
    • [cs.DC]Characterization and Prediction of Deep Learning Workloads in Large-Scale GPU Datacenters
    • [cs.DC]Continuous Tasks and the Chromatic Simplicial Approximation Theorem
    • [cs.DC]ECO: Edge-Cloud Optimization of 5G applications
    • [cs.DC]Enabling Reproducible Analysis of Complex Workflows on the Edge-to-Cloud Continuum
    • [cs.DC]Fast Abstracts and Student Forum Proceedings, 17th European Dependable Computing Conference — EDCC 2021
    • [cs.DC]FedApp: a Research Sandbox for Application Orchestration in Federated Clouds using OpenStack
    • [cs.HC]A Multi-Sensor Interface to Improve the Teaching and Learning Experience in Arc Welding Training Tasks
    • [cs.HC]The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies
    • [cs.IR]UserBERT: Contrastive User Model Pre-training
    • [cs.IT]A Max-Min Task Offloading Algorithm for Mobile Edge Computing Using Non-Orthogonal Multiple Access
    • [cs.IT]Low-Latency and Secure Computation Offloading Assisted by Hybrid Relay-Reflecting Intelligent Surface
    • [cs.IT]Optimizing the Energy Efficiency of Unreliable Memories for Quantized Kalman Filtering
    • [cs.IT]Scalar Gaussian Wiretap Channel: Properties of the Support Size of the Secrecy-Capacity-Achieving Distribution
    • [cs.IT]Secrecy Performance of α-κ-μ Shadowed Fading Channel
    • [cs.IT]Secure Source Coding with Side-information at Decoder and Shared Key at Encoder and Decoder
    • [cs.LG]A Bayesian Approach to (Online) Transfer Learning: Theory and Algorithms
    • [cs.LG]A New Approach to Multilabel Stratified Cross Validation with Application to Large and Sparse Gene Ontology Datasets
    • [cs.LG]Biomedical Data-to-Text Generation via Fine-Tuning Transformers
    • [cs.LG]Building Interpretable Models for Business Process Prediction using Shared and Specialised Attention Mechanisms
    • [cs.LG]Dive into Layers: Neural Network Capacity Bounding using Algebraic Geometry
    • [cs.LG]Edge-featured Graph Neural Architecture Search
    • [cs.LG]Estimating Demand Flexibility Using Siamese LSTM Neural Networks
    • [cs.LG]How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data
    • [cs.LG]Impact of GPU uncertainty on the training of predictive deep neural networks
    • [cs.LG]Instance-wise or Class-wise? A Tale of Neighbor Shapley for Concept-based Explanation
    • [cs.LG]Investigate the Correlation of Breast Cancer Dataset using Different Clustering Technique
    • [cs.LG]J-Score: A Robust Measure of Clustering Accuracy
    • [cs.LG]LG4AV: Combining Language Models and Graph Neural Networks for Author Verification
    • [cs.LG]Large-Scale Learning with Fourier Features and Tensor Decompositions
    • [cs.LG]LightAutoML: AutoML Solution for a Large Financial Services Ecosystem
    • [cs.LG]Multi-agent Natural Actor-critic Reinforcement Learning Algorithms
    • [cs.LG]Pareto-Optimal Learning-Augmented Algorithms for Online Conversion Problems
    • [cs.LG]Provably Safe Model-Based Meta Reinforcement Learning: An Abstraction-Based Approach
    • [cs.LG]Stochastic Physics-Informed Neural Networks (SPINN): A Moment-Matching Framework for Learning Hidden Physics within Stochastic Differential Equations
    • [cs.LG]Topographic VAEs learn Equivariant Capsules
    • [cs.NI]Is Machine Learning Ready for Traffic Engineering Optimization?
    • [cs.RO]A Comparative Study of Nonlinear MPC and Differential-Flatness-Based Control for Quadrotor Agile Flight
    • [cs.RO]Invariant Filtering for Bipedal Walking on Dynamic Rigid Surfaces with Orientation-based Measurement Model
    • [cs.RO]Iterative Imitation Policy Improvement for Interactive Autonomous Driving
    • [cs.RO]Mechanical Chameleons: Evaluating the effects of a social robot’s non-verbal behavior on social influence
    • [cs.RO]On the similarities between Control Barrier Functions (CBFs) and Behavior Control Lyapunov Functions (BCLFs)
    • [cs.RO]Real-Time Volumetric-Semantic Exploration and Mapping: An Uncertainty-Aware Approach
    • [cs.RO]Theory of Mind Based Assistive Communication in Complex Human Robot Cooperation
    • [cs.SI]Neural PathSim for Inductive Similarity Search in Heterogeneous Information Networks
    • [eess.IV]Automatic Foot Ulcer segmentation Using an Ensemble of Convolutional Neural Networks
    • [eess.IV]Deep Learning Approach for Hyperspectral Image Demosaicking, Spectral Correction and High-resolution RGB Reconstruction
    • [eess.IV]Multi-centred Strong Augmentation via Contrastive Learning for Unsupervised Lesion Detection and Segmentation
    • [eess.IV]Unsupervised multi-latent space reinforcement learning framework for video summarization in ultrasound imaging
    • [eess.SP]Ground-Assisted Federated Learning in LEO Satellite Constellations
    • [eess.SY]Continuous-Time Behavior Trees as Discontinuous Dynamical Systems
    • [math.NA]Semi-Implicit Neural Solver for Time-dependent Partial Differential Equations
    • [math.ST]Is the mode elicitable relative to unimodal distributions?
    • [physics.flu-dyn]Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows
    • [physics.soc-ph]COVID-19 Vaccine Hesitancy and Information Diffusion: An Agent-based Modeling Approach
    • [physics.soc-ph]Universality, criticality and complexity of information propagation in social media
    • [stat.AP]Epidemic Models for COVID-19 during the First Wave from February to May 2020: a Methodological Review
    • [stat.AP]Evaluating the Use of Generalized Dynamic Weighted Ordinary Least Squares for Individualized HIV Treatment Strategies
    • [stat.AP]Frequency-Severity Experience Rating based on Latent Markovian Risk Profiles
    • [stat.AP]Simultaneous quantification and changepoint detection of point source gas emissions using recursive Bayesian inference
    • [stat.AP]Teacher Mental Health During the COVID-19 Pandemic: Informing Policies to Support Teacher Well-being and Effective Teaching Practices
    • [stat.AP]Two Shifts for Crop Mapping: Leveraging Aggregate Crop Statistics to Improve Satellite-based Maps in New Regions
    • [stat.ME]Regularized tapered sample covariance matrix
    • [stat.ME]Robust confidence distributions from proper scoring rules
    • [stat.ME]Variational Bayes algorithm and posterior consistency of Ising model parameter estimation
    • [stat.ML]Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process
    • [stat.ML]Sample Noise Impact on Active Learning
    • [stat.ML]Statistical Estimation and Inference via Local SGD in Federated Learning

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

    • [cond-mat.stat-mech]The typical set and entropy in stochastic systems with arbitrary phase space growth
    Rudolf Hanel, Bernat Corominas-Murtra
    http://arxiv.org/abs/2109.01475v1

    • [cs.AI]A brief history of AI: how to prevent another winter (a critical review)
    Amirhosein Toosi, Andrea Bottino, Babak Saboury, Eliot Siegel, Arman Rahmim
    http://arxiv.org/abs/2109.01517v1

    • [cs.AI]An Oracle and Observations for the OpenAI Gym / ALE Freeway Environment
    James S. Plank, Catherine D. Schuman, Robert M. Patton
    http://arxiv.org/abs/2109.01220v1

    • [cs.AI]CX-ToM: Counterfactual Explanations with Theory-of-Mind for Enhancing Human Trust in Image Recognition Models
    Arjun R. Akula, Keze Wang, Changsong Liu, Sari Saba-Sadiya, Hongjing Lu, Sinisa Todorovic, Joyce Chai, Song-Chun Zhu
    http://arxiv.org/abs/2109.01401v1

    • [cs.AI]Efficient Communication in Multi-Agent Distributed Reinforcement Learning
    Daniel Jarne Ornia, Manuel Mazo Jr
    http://arxiv.org/abs/2109.01417v1

    • [cs.AI]Integration of Data and Theory for Accelerated Derivable Symbolic Discovery
    Cristina Cornelio, Sanjeeb Dash, Vernon Austel, Tyler Josephson, Joao Goncalves, Kenneth Clarkson, Nimrod Megiddo, Bachir El Khadir, Lior Horesh
    http://arxiv.org/abs/2109.01634v1

    • [cs.AI]Multi-Agent Inverse Reinforcement Learning: Suboptimal Demonstrations and Alternative Solution Concepts
    Sage Bergerson
    http://arxiv.org/abs/2109.01178v1

    • [cs.AI]Situated Conditional Reasoning
    Giovanni Casini, Thomas Meyer, Ivan Varzinczak
    http://arxiv.org/abs/2109.0
    5e91
    1552v1
    5e91
    1552v1)

    • [cs.AI]Symbol Emergence and The Solutions to Any Task
    Michael Timothy Bennett
    http://arxiv.org/abs/2109.01281v1

    • [cs.AR]On the Accuracy of Analog Neural Network Inference Accelerators
    T. Patrick Xiao, Ben Feinberg, Christopher H. Bennett, Venkatraman Prabhakar, Prashant Saxena, Vineet Agrawal, Sapan Agarwal, Matthew J. Marinella
    http://arxiv.org/abs/2109.01262v1

    • [cs.CL]A Context-Aware Hierarchical BERT Fusion Network for Multi-turn Dialog Act Detection
    Ting-Wei Wu, Ruolin Su, Biing-Hwang Juang
    http://arxiv.org/abs/2109.01267v1

    • [cs.CL]A Longitudinal Multi-modal Dataset for Dementia Monitoring and Diagnosis
    Dimitris Gkoumas, Bo Wang, Adam Tsakalidis, Maria Wolters, Arkaitz Zubiaga, Matthew Purver, Maria Liakata
    http://arxiv.org/abs/2109.01537v1

    • [cs.CL]An Empirical Study on Leveraging Position Embeddings for Target-oriented Opinion Words Extraction
    Samuel Mensah, Kai Sun, Nikolaos Aletras
    http://arxiv.org/abs/2109.01238v1

    • [cs.CL]An Exploratory Study on Utilising the Web of Linked Data for Product Data Mining
    Ziqi Zhang, Xingyi Song
    http://arxiv.org/abs/2109.01411v1

    • [cs.CL]An Open-Source Dataset and A Multi-Task Model for Malay Named Entity Recognition
    Yingwen Fu, Nankai Lin, Zhihe Yang, Shengyi Jiang
    http://arxiv.org/abs/2109.01293v1

    • [cs.CL]CREAK: A Dataset for Commonsense Reasoning over Entity Knowledge
    Yasumasa Onoe, Michael J. Q. Zhang, Eunsol Choi, Greg Durrett
    http://arxiv.org/abs/2109.01653v1

    • [cs.CL]Challenges in Generalization in Open Domain Question Answering
    Linqing Liu, Patrick Lewis, Sebastian Riedel, Pontus Stenetorp
    http://arxiv.org/abs/2109.01156v1

    • [cs.CL]Contextualized Embeddings based Convolutional Neural Networks for Duplicate Question Identification
    Harsh Sakhrani, Saloni Parekh, Pratik Ratadiya
    http://arxiv.org/abs/2109.01560v1

    • [cs.CL]Contrastive Representation Learning for Exemplar-Guided Paraphrase Generation
    Haoran Yang, Wai Lam, Piji Li
    http://arxiv.org/abs/2109.01484v1

    • [cs.CL]Cross-Lingual Training with Dense Retrieval for Document Retrieval
    Peng Shi, Rui Zhang, He Bai, Jimmy Lin
    http://arxiv.org/abs/2109.01628v1

    • [cs.CL]Detecting Speaker Personas from Conversational Texts
    Jia-Chen Gu, Zhen-Hua Ling, Yu Wu, Quan Liu, Zhigang Chen, Xiaodan Zhu
    http://arxiv.org/abs/2109.01330v1

    • [cs.CL]Do Prompt-Based Models Really Understand the Meaning of their Prompts?
    Albert Webson, Ellie Pavlick
    http://arxiv.org/abs/2109.01247v1

    • [cs.CL]Empirical Study of Named Entity Recognition Performance Using Distribution-aware Word Embedding
    Xin Chen, Qi Zhao, Xinyang Liu
    http://arxiv.org/abs/2109.01636v1

    • [cs.CL]Entity Linking and Discovery via Arborescence-based Supervised Clustering
    Dhruv Agarwal, Rico Angell, Nicholas Monath, Andrew McCallum
    http://arxiv.org/abs/2109.01242v1

    • [cs.CL]Establishing Interlingua in Multilingual Language Models
    Maksym Del, Mark Fishel
    http://arxiv.org/abs/2109.01207v1

    • [cs.CL]Finetuned Language Models Are Zero-Shot Learners
    Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, Quoc V. Le
    http://arxiv.org/abs/2109.01652v1

    • [cs.CL]Indexing Context-Sensitive Reachability
    Qingkai Shi, Yongchao Wang, Charles Zhang
    http://arxiv.org/abs/2109.01321v1

    • [cs.CL]Language Modeling, Lexical Translation, Reordering: The Training Process of NMT through the Lens of Classical SMT
    Elena Voita, Rico Sennrich, Ivan Titov
    http://arxiv.org/abs/2109.01396v1

    • [cs.CL]Learning Neural Models for Natural Language Processing in the Face of Distributional Shift
    Paul Michel
    http://arxiv.org/abs/2109.01558v1

    • [cs.CL]Learning from Multiple Noisy Augmented Data Sets for Better Cross-Lingual Spoken Language Understanding
    Yingmei Guo, Linjun Shou, Jian Pei, Ming Gong, Mingxing Xu, Zhiyong Wu, Daxin Jiang
    http://arxiv.org/abs/2109.01583v1

    • [cs.CL]Multimodal Conditionality for Natural Language Generation
    Michael Sollami, Aashish Jain
    http://arxiv.org/abs/2109.01229v1

    • [cs.CL]Quantifying Reproducibility in NLP and ML
    Anya Belz
    http://arxiv.org/abs/2109.01211v1

    • [cs.CL]Ranking Scientific Papers Using Preference Learning
    Nils Dycke, Edwin Simpson, Ilia Kuznetsov, Iryna Gurevych
    http://arxiv.org/abs/2109.01190v1

    • [cs.CL]So Cloze yet so Far: N400 Amplitude is Better Predicted by Distributional Information than Human Predictability Judgements
    James A. Michaelov, Seana Coulson, Benjamin K. Bergen
    http://arxiv.org/abs/2109.01226v1

    • [cs.CR]A Synergetic Attack against Neural Network Classifiers combining Backdoor and Adversarial Examples
    Guanxiong Liu, Issa Khalil, Abdallah Khreishah, NhatHai Phan
    http://arxiv.org/abs/2109.01275v1

    • [cs.CR]Ontology-driven Knowledge Graph for Android Malware
    Ryan Christian, Sharmishtha Dutta, Youngja Park, Nidhi Rastogi
    http://arxiv.org/abs/2109.01544v1

    • [cs.CV]3D Human Shape Style Transfer
    Joao Regateiro, Edmond Boyer
    http://arxiv.org/abs/2109.01587v1

    • [cs.CV]Access Control Using Spatially Invariant Permutation of Feature Maps for Semantic Segmentation Models
    Hiroki Ito, MaungMaung AprilPyone, Hitoshi Kiya
    http://arxiv.org/abs/2109.01332v1

    • [cs.CV]CAP-Net: Correspondence-Aware Point-view Fusion Network for 3D Shape Analysis
    Xinwei He, Silin Cheng, Song Bai, Xiang Bai
    http://arxiv.org/abs/2109.01291v1

    • [cs.CV]Deep Learning for Fitness
    Mahendran N
    http://arxiv.org/abs/2109.01376v1

    • [cs.CV]Deep Metric Learning for Ground Images
    Raaghav Radhakrishnan, Jan Fabian Schmid, Randolf Scholz, Lars Schmidt-Thieme
    http://arxiv.org/abs/2109.01569v1

    • [cs.CV]Dual-Camera Super-Resolution with Aligned Attention Modules
    Tengfei Wang, Jiaxin Xie, Wenxiu Sun, Qiong Yan, Qifeng Chen
    http://arxiv.org/abs/2109.01349v1

    • [cs.CV]Ghost Loss to Question the Reliability of Training Data
    Adrien Deliège, Anthony Cioppa, Marc Van Droogenbroeck
    http://arxiv.org/abs/2109.01504v1

    • [cs.CV]Information Symmetry Matters: A Modal-Alternating Propagation Network for Few-Shot Learning
    Zhong Ji, Zhishen Hou, Xiyao Liu, Yanwei Pang, Jungong Han
    http://arxiv.org/abs/2109.01295v1

    • [cs.CV]MitoVis: A Visually-guided Interactive Intelligent System for Neuronal Mitochondria Analysis
    JunYoung Choi, Hakjun Lee, Suyeon Kim, Seok-Kyu Kwon, Won-Ki Jeong
    http://arxiv.org/abs/2109.01351v1

    • [cs.CV]Model-Based Parameter Optimization for Ground Texture Based Localization Methods
    Jan Fabian Schmid, Stephan F. Simon, Rudolf Mester
    http://arxiv.org/abs/2109.01559v1

    • [cs.CV]Neural Human Deformation Transfer
    Jean Basset, Adnane Boukhayma, Stefanie Wuhrer, Franck Multon, Edmond Boyer
    http://arxiv.org/abs/2109.01588v1

    • [cs.CV]Occlusion-Invariant Rotation-Equivariant Semi-Supervised Depth Based Cross-View Gait Pose Estimation
    Xiao Gu, Jianxin Yang, Hanxiao Zhang, Jianing Qiu, Frank Po Wen Lo, Yao Guo, Guang-Zhong Yang, Benny Lo
    http://arxiv.org/abs/2109.01397v1

    • [cs.CV]Optimal Target Shape for LiDAR Pose Estimation
    Jiunn-Kai Huang, William Clark, Jessy W. Grizzle
    http://arxiv.org/abs/2109.01181v1

    • [cs.CV]Ordinal Pooling
    Adrien Deliège, Maxime Istasse, Ashwani Kumar, Christophe De Vleeschouwer, Marc Van Droogenbroeck
    http://arxiv.org/abs/2109.01561v1

    • [cs.CV]Representing Shape Collections with Alignment-Aware Linear Models
    Romain Loiseau, Tom Monnier, Loïc Landrieu, Mathieu Aubry
    http://arxiv.org/abs/2109.01605v1

    • [cs.CV]Safety-aware Motion Prediction with Unseen Vehicles for Autonomous Driving
    Xuanchi Ren, Tao Yang, Li Erran Li, Alexandre Alahi, Qifeng Chen
    http://arxiv.org/abs/2109.01510v1

    • [cs.CV]Segmentation of turbulent computational fluid dynamics simulations with unsupervised ensemble learning
    Maarja Bussov, Joonas Nättilä
    http://arxiv.org/abs/2109.01381v1

    • [cs.CV]Self-Taught Cross-Domain Few-Shot Learning with Weakly Supervised Object Localization and Task-Decomposition
    Xiyao Liu, Zhong Ji, Yanwei Pang, Zhongfei Zhang
    http://arxiv.org/abs/2109.01302v1

    • [cs.CV]Semantic Segmentation on VSPW Dataset through Aggregation of Transformer Models
    Zixuan Chen, Junhong Zou, Xiaotao Wang
    http://arxiv.org/abs/2109.01316v1

    • [cs.CV]Spatially varying white balancing for mixed and non-uniform illuminants
    Teruaki Akazawa, Yuma Kinoshita, Hitoshi Kiya
    http://arxiv.org/abs/2109.01350v1

    • [cs.CV]Towards Learning Spatially Discriminative Feature Representations
    Chaofei Wang, Jiayu Xiao, Yizeng Han, Qisen Yang, Shiji Song, Gao Huang
    http://arxiv.org/abs/2109.01359v1

    • [cs.CV]UnDeepLIO: Unsupervised Deep Lidar-Inertial Odometry
    Yiming Tu, Jin Xie
    http://arxiv.org/abs/2109.01533v1

    • [cs.CV]Using Topological Framework for the Design of Activation Function and Model Pruning in Deep Neural Networks
    Yogesh Kochar, Sunil Kumar Vengalil, Neelam Sinha
    http://arxiv.org/abs/2109.01572v1

    • [cs.CV]Video Pose Distillation for Few-Shot, Fine-Grained Sports Action Recognition
    James Hong, Matthew Fisher, Michaël Gharbi, Kayvon Fatahalian
    http://arxiv.org/abs/2109.01305v1

    • [cs.CV]Wildfire smoke plume segmentation using geostationary satellite imagery
    Jeff Wen, Marshall Burke
    http://arxiv.org/abs/2109.01637v1

    • [cs.CY]Hide and seek in Slovakia: utilizing tracking code data to uncover untrustworthy website networks
    Jozef Michal Mintal, Michal Kalman, Karol Fabián
    http://arxiv.org/abs/2109.01527v1

    • [cs.CY]Proceedings of KDD 2021 Workshop on Data-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resilience Planning
    Snehalkumar, S. Gaikwad, Shankar Iyer, Dalton Lunga, Elizabeth Bondi
    http://arxiv.org/abs/2109.00100v3

    • [cs.DC]A Reliable, Self-Adaptive Face Identification Framework via Lyapunov Optimization
    Dohyeon Kim, Joongheon Kim, Jae young Bang
    http://arxiv.org/abs/2109.01212v1

    • [cs.DC]A Study of Mixed Precision Strategies for GMRES on GPUs
    Jennifer A. Loe, Christian A. Glusa, Ichitaro Yamazaki, Erik G. Boman, Sivasankaran Rajamanickam
    http://arxiv.org/abs/2109.01232v1

    • [cs.DC]Achieving near native runtime performance and cross-platform performance portability for random number generation through SYCL interoperability
    Vincent R. Pascuzzi, Mehdi Goli
    http://arxiv.org/abs/2109.01329v1

    • [cs.DC]Byzantine Consensus in Directed Hypergraphs
    Muhammad Samir Khan, Nitin H. Vaidya
    http://arxiv.org/abs/2109.01205v1

    • [cs.DC]Characterization and Prediction of Deep Learning Workloads in Large-Scale GPU Datacenters
    Hu, Qinghao, Sun, Peng, Yan, Shengen, Wen, Yonggang, Zhang, Tianwei
    http://arxiv.org/abs/2109.01313v1

    • [cs.DC]Continuous Tasks and the Chromatic Simplicial Approximation Theorem
    Hugo Rincon Galeana, Sergio Rajsbaum, Ulrich Schmid
    http://arxiv.org/abs/2109.01439v1

    • [cs.DC]ECO: Edge-Cloud Optimization of 5G applications
    Kunal Rao, Giuseppe Coviello, Wang-Pin Hsiung, Srimat Chakradhar
    http://arxiv.org/abs/2109.01201v1

    • [cs.DC]Enabling Reproducible Analysis of Complex Workflows on the Edge-to-Cloud Continuum
    Daniel Rosendo, Alexandru Costan, Gabriel Antoniu, Patrick Valduriez
    http://arxiv.org/abs/2109.01379v1

    • [cs.DC]Fast Abstracts and Student Forum Proceedings, 17th European Dependable Computing Conference — EDCC 2021
    Marcello Cinque, Barbara Gallina
    http://arxiv.org/abs/2109.00465v2

    • [cs.DC]FedApp: a Research Sandbox for Application Orchestration in Federated Clouds using OpenStack
    Johan Ruuskanen, Haorui Peng, Alfred Åkesson, Lars Larsson, Maria Kihl
    http://arxiv.org/abs/2109.01480v1

    • [cs.HC]A Multi-Sensor Interface to Improve the Teaching and Learning Experience in Arc Welding Training Tasks
    Hoi-Yin Lee, Peng Zhou, Victor Wu, David Navarro-Alarcon
    http://arxiv.org/abs/2109.01383v1

    • [cs.HC]The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies
    Riccardo Fogliato, Alexandra Chouldechova, Zachary Lipton
    http://arxiv.org/abs/2109.01443v1

    • [cs.IR]UserBERT: Contrastive User Model Pre-training
    Chuhan Wu, Fangzhao Wu, Yang Yu, Tao Qi, Yongfeng Huang, Xing Xie
    http://arxiv.org/abs/2109.01274v1

    • [cs.IT]A Max-Min Task Offloading Algorithm for Mobile Edge Computing Using Non-Orthogonal Multiple Access
    Vaibhav Kumar, Muhammad Fainan Hanif, Markku Juntti, Le-Nam Tran
    http://arxiv.org/abs/2109.01239v1

    • [cs.IT]Low-Latency and Secure Computation Offloading Assisted by Hybrid Relay-Reflecting Intelligent Surface
    Khac-Hoang Ngo, Nhan Thanh Nguyen, Thinh Quang Dinh, Trong-Minh Hoang, Markku Juntti
    http://arxiv.org/abs/2109.01335v1

    • [cs.IT]Optimizing the Energy Efficiency of Unreliable Memories for Quantized Kalman Filtering
    Jonathan Kern, Elsa Dupraz, Abdeldjalil Aïssa-El-Bey, Lav R. Varshney, François Leduc-Primeau
    http://arxiv.org/abs/2109.01520v1

    • [cs.IT]Scalar Gaussian Wiretap Channel: Properties of the Support Size of the Secrecy-Capacity-Achieving Distribution
    Luca Barletta, Alex Dytso
    http://arxiv.org/abs/2109.01566v1

    • [cs.IT]Secrecy Performance of α-κ-μ Shadowed Fading Channel
    A. S. M. Badrudduza, S. H. Islam, M. K. Kundu, I. S. Ansari
    http://arxiv.org/abs/2109.01407v1

    • [cs.IT]Secure Source Coding with Side-information at Decoder and Shared Key at Encoder and Decoder
    Hamid Ghourchian, Photios A. Stavrou, Tobias J. Oechtering, Mikael Skoglund
    http://arxiv.org/abs/2109.01613v1

    • [cs.LG]A Bayesian Approach to (Online) Transfer Learning: Theory and Algorithms
    Xuetong Wu, Jonathan H. Manton, Uwe Aickelin, Jingge Zhu
    http://arxiv.org/abs/2109.01377v1

    • [cs.LG]A New Approach to Multilabel Stratified Cross Validation with Application to Large and Sparse Gene Ontology Datasets
    Henri Tiittanen, Liisa Holm, Petri Törönen
    http://arxiv.org/abs/2109.01425v1

    • [cs.LG]Biomedical Data-to-Text Generation via Fine-Tuning Transformers
    Ruslan Yermakov, Nicholas Drago, Angelo Ziletti
    http://arxiv.org/abs/2109.01518v1

    • [cs.LG]Building Interpretable Models for Business Process Prediction using Shared and Specialised Attention Mechanisms
    Bemali Wickramanayake, Zhipeng He, Chun Ouyang, Catarina Moreira, Yue Xu, Renuka Sindhgatta
    http://arxiv.org/abs/2109.01419v1

    • [cs.LG]Dive into Layers: Neural Network Capacity Bounding using Algebraic Geometry
    Ji Yang, Lu Sang, Daniel Cremers
    http://arxiv.org/abs/2109.01461v1

    • [cs.LG]Edge-featured Graph Neural Architecture Search
    Shaofei Cai, Liang Li, Xinzhe Han, Zheng-jun Zha, Qingming Huang
    http://arxiv.org/abs/2109.01356v1

    • [cs.LG]Estimating Demand Flexibility Using Siamese LSTM Neural Networks
    Guangchun Ruan, Daniel S. Kirschen, Haiwang Zhong, Qing Xia, Chongqing Kang
    http://arxiv.org/abs/2109.01258v1

    • [cs.LG]How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data
    Zhiyuan Zhang, Lingjuan Lyu, Weiqiang Wang, Lichao Sun, Xu Sun
    http://arxiv.org/abs/2109.01300v1

    • [cs.LG]Impact of GPU uncertainty on the training of predictive deep neural networks
    Maciej Pietrowski, Andrzej Gajda, Takuto Yamamoto, Taisuke Kobayashi, Lana Sinapayen, Eiji Watanabe
    http://arxiv.org/abs/2109.01451v1

    • [cs.LG]Instance-wise or Class-wise? A Tale of Neighbor Shapley for Concept-based Explanation
    Jiahui Li, Kun Kuang, Lin Li, Long Chen, Songyang Zhang, Jian Shao, Jun Xiao
    http://arxiv.org/abs/2109.01369v1

    • [cs.LG]Investigate the Correlation of Breast Cancer Dataset using Different Clustering Technique
    Somenath Chakraborty, Beddhu Murali
    http://arxiv.org/abs/2109.01538v1

    • [cs.LG]J-Score: A Robust Measure of Clustering Accuracy
    Navid Ahmadinejad, Li Liu
    http://arxiv.org/abs/2109.01306v1

    • [cs.LG]LG4AV: Combining Language Models and Graph Neural Networks for Author Verification
    Maximilian Stubbemann, Gerd Stumme
    http://arxiv.org/abs/2109.01479v1

    • [cs.LG]Large-Scale Learning with Fourier Features and Tensor Decompositions
    Frederiek Wesel, Kim Batselier
    http://arxiv.org/abs/2109.01545v1

    • [cs.LG]LightAutoML: AutoML Solution for a Large Financial Services Ecosystem
    Anton Vakhrushev, Alexander Ryzhkov, Maxim Savchenko, Dmitry Simakov, Rinchin Damdinov, Alexander Tuzhilin
    http://arxiv.org/abs/2109.01528v1

    • [cs.LG]Multi-agent Natural Actor-critic Reinforcement Learning Algorithms
    Prashant Trivedi, Nandyala Hemachandra
    http://arxiv.org/abs/2109.01654v1

    • [cs.LG]Pareto-Optimal Learning-Augmented Algorithms for Online Conversion Problems
    Bo Sun, Russell Lee, Mohammad Hajiesmaili, Adam Wierman, Danny H. K. Tsang
    http://arxiv.org/abs/2109.01556v1

    • [cs.LG]Provably Safe Model-Based Meta Reinforcement Learning: An Abstraction-Based Approach
    Xiaowu Sun, Wael Fatnassi, Ulices Santa Cruz, Yasser Shoukry
    http://arxiv.org/abs/2109.01255v1

    • [cs.LG]Stochastic Physics-Informed Neural Networks (SPINN): A Moment-Matching Framework for Learning Hidden Physics within Stochastic Differential Equations
    Jared O’Leary, Joel A. Paulson, Ali Mesbah
    http://arxiv.org/abs/2109.01621v1

    • [cs.LG]Topographic VAEs learn Equivariant Capsules
    T. Anderson Keller, Max Welling
    http://arxiv.org/abs/2109.01394v1

    • [cs.NI]Is Machine Learning Ready for Traffic Engineering Optimization?
    Guillermo Bernárdez, José Suárez-Varela, Albert López, Bo Wu, Shihan Xiao, Xiangle Cheng, Pere Barlet-Ros, Albert Cabellos-Aparicio
    http://arxiv.org/abs/2109.01445v1

    • [cs.RO]A Comparative Study of Nonlinear MPC and Differential-Flatness-Based Control for Quadrotor Agile Flight
    Sihao Sun, Angel Romero, Philipp Foehn, Elia Kaufmann, Davide Scaramuzza
    http://arxiv.org/abs/2109.01365v1

    • [cs.RO]Invariant Filtering for Bipedal Walking on Dynamic Rigid Surfaces with Orientation-based Measurement Model
    Yuan Gao, Yan Gu
    http://arxiv.org/abs/2109.01241v1

    • [cs.RO]Iterative Imitation Policy Improvement for Interactive Autonomous Driving
    Zhao-Heng Yin, Chenran Li, Liting Sun, Masayoshi Tomizuka, Wei Zhan
    http://arxiv.org/abs/2109.01288v1

    • [cs.RO]Mechanical Chameleons: Evaluating the effects of a social robot’s non-verbal behavior on social influence
    Patrik Jonell, Anna Deichler, Ilaria Torre, Iolanda Leite, Jonas Beskow
    http://arxiv.org/abs/2109.01206v1

    • [cs.RO]On the similarities between Control Barrier Functions (CBFs) and Behavior Control Lyapunov Functions (BCLFs)
    Petter Ögren
    http://arxiv.org/abs/2109.01343v1

    • [cs.RO]Real-Time Volumetric-Semantic Exploration and Mapping: An Uncertainty-Aware Approach
    Rui Pimentel de Figueiredo, Jonas le Fevre Sejersen, Jakob Grimm Hansen, Martim Brandão, Erdal Kayacan
    http://arxiv.org/abs/2109.01474v1

    • [cs.RO]Theory of Mind Based Assistive Communication in Complex Human Robot Cooperation
    Moritz C. Buehler, Jürgen Adamy, Thomas H. Weisswange
    http://arxiv.org/abs/2109.01355v1

    • [cs.SI]Neural PathSim for Inductive Similarity Search in Heterogeneous Information Networks
    Wenyi Xiao, Huan Zhao, Vincent W. Zheng, Yangqiu Song
    http://arxiv.org/abs/2109.01549v1

    • [eess.IV]Automatic Foot Ulcer segmentation Using an Ensemble of Convolutional Neural Networks
    Amirreza Mahbod, Rupert Ecker, Isabella Ellinger
    http://arxiv.org/abs/2109.01408v1

    • [eess.IV]Deep Learning Approach for Hyperspectral Image Demosaicking, Spectral Correction and High-resolution RGB Reconstruction
    Peichao Li, Michael Ebner, Philip Noonan, Conor Horgan, Anisha Bahl, Sebastien Ourselin, Jonathan Shapey, Tom Vercauteren
    http://arxiv.org/abs/2109.01403v1

    • [eess.IV]Multi-centred Strong Augmentation via Contrastive Learning for Unsupervised Lesion Detection and Segmentation
    Yu Tian, Fengbei Liu, Guansong Pang, Yuanhong Chen, Yuyuan Liu, Johan W. Verjans, Rajvinder Singh, Gustavo Carneiro
    http://arxiv.org/abs/2109.01303v1

    • [eess.IV]Unsupervised multi-latent space reinforcement learning framework for video summarization in ultrasound imaging
    Roshan P Mathews, Mahesh Raveendranatha Panicker, Abhilash R Hareendranathan, Yale Tung Chen, Jacob L Jaremko, Brian Buchanan, Kiran Vishnu Narayan, Kesavadas C, Greeta Mathews
    http://arxiv.org/abs/2109.01309v1

    • [eess.SP]Ground-Assisted Federated Learning in LEO Satellite Constellations
    Nasrin Razmi, Bho Matthiesen, Armin Dekorsy, Petar Popovski
    http://arxiv.org/abs/2109.01348v1

    • [eess.SY]Continuous-Time Behavior Trees as Discontinuous Dynamical Systems
    Christopher Iliffe Sprague, Petter Ögren
    http://arxiv.org/abs/2109.01575v1

    • [math.NA]Semi-Implicit Neural Solver for Time-dependent Partial Differential Equations
    Suprosanna Shit, Ivan Ezhov, Leon Mächler, Abinav R., Jana Lipkova, Johannes C. Paetzold, Florian Kofler, Marie Piraud, Bjoern H. Menze
    http://arxiv.org/abs/2109.01467v1

    • [math.ST]Is the mode elicitable relative to unimodal distributions?
    Claudio Heinrich-Mertsching, Tobias Fissler
    http://arxiv.org/abs/2109.00464v2

    • [physics.flu-dyn]Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows
    Hamidreza Eivazi, Soledad Le Clainche, Sergio Hoyas, Ricardo Vinuesa
    http://arxiv.org/abs/2109.01514v1

    • [physics.soc-ph]COVID-19 Vaccine Hesitancy and Information Diffusion: An Agent-based Modeling Approach
    Pooria Taghizadeh Naderi, Ali Asgary, Jude Kong, Jianhong Wu, Fattaneh Taghiyareh
    http://arxiv.org/abs/2109.01182v1

    • [physics.soc-ph]Universality, criticality and complexity of information propagation in social media
    Daniele Notarmuzi, Claudio Castellano, Alessandro Flammini, Dario Mazzilli, Filippo Radicchi
    http://arxiv.org/abs/2109.00116v1

    • [stat.AP]Epidemic Models for COVID-19 during the First Wave from February to May 2020: a Methodological Review
    Marie Garin, Myrto Limnios, Alice Nicolaï, Ioannis Bargiotas, Olivier Boulant, Stephen Chick, Amir Dib, Theodoros Evgeniou, Mathilde Fekom, Argyris Kalogeratos, Christophe Labourdette, Anton Ovchinnikov, Raphaël Porcher, Camille Pouchol, Nicolas Vayatis
    http://arxiv.org/abs/2109.01450v1

    • [stat.AP]Evaluating the Use of Generalized Dynamic Weighted Ordinary Least Squares for Individualized HIV Treatment Strategies
    Larry Dong, Erica E. M. Moodie, Laura Villain, Rodolphe Thiébaut
    http://arxiv.org/abs/2109.01218v1

    • [stat.AP]Frequency-Severity Experience Rating based on Latent Markovian Risk Profiles
    Robert Matthijs Verschuren
    http://arxiv.org/abs/2109.01413v1

    • [stat.AP]Simultaneous quantification and changepoint detection of point source gas emissions using recursive Bayesian inference
    Amir Montazeri, Xiaochi Zhou, John D. Albertson
    http://arxiv.org/abs/2109.01603v1

    • [stat.AP]Teacher Mental Health During the COVID-19 Pandemic: Informing Policies to Support Teacher Well-being and Effective Teaching Practices
    Joseph M. Kush, Elena Badillo-Goicoechea, Rashelle J. Musci, Elizabeth A. Stuart
    http://arxiv.org/abs/2109.01547v1

    • [stat.AP]Two Shifts for Crop Mapping: Leveraging Aggregate Crop Statistics to Improve Satellite-based Maps in New Regions
    Dan M. Kluger, Sherrie Wang, David B. Lobell
    http://arxiv.org/abs/2109.01246v1

    • [stat.ME]Regularized tapered sample covariance matrix
    Esa Ollila, Arnaud Breloy
    http://arxiv.org/abs/2109.01353v1

    • [stat.ME]Robust confidence distributions from proper scoring rules
    Erlis Ruli, Laura Ventura, Monica Musio
    http://arxiv.org/abs/2109.01219v1

    • [stat.ME]Variational Bayes algorithm and posterior consistency of Ising model parameter estimation
    Minwoo Kim, Shrijita Bhattacharya, Tapabrata Maiti
    http://arxiv.org/abs/2109.01548v1

    • [stat.ML]Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process
    Christoph Molnar, Timo Freiesleben, Gunnar König, Giuseppe Casalicchio, Marvin N. Wright, Bernd Bischl
    http://arxiv.org/abs/2109.01433v1

    • [stat.ML]Sample Noise Impact on Active Learning
    Alexandre Abraham, Léo Dreyfus-Schmidt
    http://arxiv.org/abs/2109.01372v1

    • [stat.ML]Statistical Estimation and Inference via Local SGD in Federated Learning
    Xiang Li, Jiadong Liang, Xiangyu Chang, Zhihua Zhang
    http://arxiv.org/abs/2109.01326v1