cs.AI - 人工智能 cs.AR - 硬件体系结构 cs.CE - 计算工程、 金融和科学 cs.CL - 计算与语言 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DS - 数据结构与算法 cs.GR - 计算机图形学 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.MA - 多代理系统 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 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 hep-th - 高能物理理论 math.NA - 数值分析 math.OC - 优化与控制 math.ST - 统计理论 physics.bio-ph - 生物物理 physics.flu-dyn - 流体动力学 physics.soc-ph - 物理学与社会 q-bio.BM - 生物分子 quant-ph - 量子物理 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cs.AI]AI solutions for drafting in Magic: the Gathering
• [cs.AI]Action and Perception as Divergence Minimization
• [cs.AI]Derived metrics for the game of Go — intrinsic network strength assessment and cheat-detection
• [cs.AI]FairXGBoost: Fairness-aware Classification in XGBoost
• [cs.AI]Fairness in the Eyes of the Data: Certifying Machine-Learning Models
• [cs.AI]Grounded Language Learning Fast and Slow
• [cs.AI]Learning to Infer User Hidden States for Online Sequential Advertising
• [cs.AI]On Population-Based Algorithms for Distributed Constraint Optimization Problems
• [cs.AI]SEDRo: A Simulated Environment for Developmental Robotics
• [cs.AI]User Intention Recognition and Requirement Elicitation Method for Conversational AI Services
• [cs.AR]An Ensemble Learning Approach for In-situ Monitoring of FPGA Dynamic Power
• [cs.AR]Decision Tree Based Hardware Power Monitoring for Run Time Dynamic Power Management in FPGA
• [cs.CE]Accelerating engineering design by automatic selection of simulation cases through Pool-Based Active Learning
• [cs.CL]A Practical Chinese Dependency Parser Based on A Large-scale Dataset
• [cs.CL]A Python Library for Exploratory Data Analysis and Knowledge Discovery on Twitter Data
• [cs.CL]A Simple Global Neural Discourse Parser
• [cs.CL]Biomedical named entity recognition using BERT in the machine reading comprehension framework
• [cs.CL]Comparative Evaluation of Pretrained Transfer Learning Models on Automatic Short Answer Grading
• [cs.CL]Learning to summarize from human feedback
• [cs.CL]SRQA: Synthetic Reader for Factoid Question Answering
• [cs.CL]The ADAPT Enhanced Dependency Parser at the IWPT 2020 Shared Task
• [cs.CL]Too good to be true? Predicting author profiles from abusive language
• [cs.CL]orgFAQ: A New Dataset and Analysis on Organizational FAQs and User Questions
• [cs.CV]1st Place Solution of LVIS Challenge 2020: A Good Box is not a Guarantee of a Good Mask
• [cs.CV]A Comparison of Pre-trained Vision-and-Language Models for Multimodal Representation Learning across Medical Images and Reports
• [cs.CV]Adherent Mist and Raindrop Removal from a Single Image Using Attentive Convolutional Network
• [cs.CV]Auto-Classifier: A Robust Defect Detector Based on an AutoML Head
• [cs.CV]Computational Analysis of Deformable Manifolds: from Geometric Modelling to Deep Learning
• [cs.CV]DESC: Domain Adaptation for Depth Estimation via Semantic Consistency
• [cs.CV]Efficiency in Real-time Webcam Gaze Tracking
• [cs.CV]Few-shot Object Detection with Feature Attention Highlight Module in Remote Sensing Images
• [cs.CV]Flow-edge Guided Video Completion
• [cs.CV]Layer-specific Optimization for Mixed Data Flow with Mixed Precision in FPGA Design for CNN-based Object Detectors
• [cs.CV]MIPGAN — Generating Robust and High QualityMorph Attacks Using Identity Prior Driven GAN
• [cs.CV]Modeling Global Body Configurations in American Sign Language
• [cs.CV]Modification method for single-stage object detectors that allows to exploit the temporal behaviour of a scene to improve detection accuracy
• [cs.CV]Multi-Loss Weighting with Coefficient of Variations
• [cs.CV]NITES: A Non-Parametric Interpretable Texture Synthesis Method
• [cs.CV]Noise-Aware Texture-Preserving Low-Light Enhancement
• [cs.CV]Physics-based Shading Reconstruction for Intrinsic Image Decomposition
• [cs.CV]Ref-NMS: Breaking Proposal Bottlenecks in Two-Stage Referring Expression Grounding
• [cs.CV]Robust Object Classification Approach using Spherical Harmonics
• [cs.CV]SCG-Net: Self-Constructing Graph Neural Networks for Semantic Segmentation
• [cs.CV]Spatial Transformer Point Convolution
• [cs.CV]Synthetic-to-Real Unsupervised Domain Adaptation for Scene Text Detection in the Wild
• [cs.CV]TRACE: Transform Aggregate and Compose Visiolinguistic Representations for Image Search with Text Feedback
• [cs.CV]Tasks Integrated Networks: Joint Detection and Retrieval for Image Search
• [cs.CV]Towards Practical Implementations of Person Re-Identification from Full Video Frames
• [cs.CV]Unsupervised Feedforward Feature (UFF) Learning for Point Cloud Classification and Segmentation
• [cs.CV]Unsupervised Point Cloud Registration via Salient Points Analysis (SPA)
• [cs.CY]A Theoretical Approach for a Novel Model to Realizing Empathy
• [cs.CY]COVID-19: The Information Warfare Paradigm Shift
• [cs.CY]Deep Learning in Science
• [cs.CY]Gender Stereotype Reinforcement: Measuring the Gender Bias Conveyed by Ranking Algorithms
• [cs.CY]Indoor Localization Techniques Within a Home Monitoring Platform
• [cs.CY]Reading In-Between the Lines: An Analysis of Dissenter
• [cs.CY]Unique Exams: Designing assessments for integrity and fairness
• [cs.DB]HyperBench: A Benchmark and Tool for Hypergraphs and Empirical Findings
• [cs.DC]Fast Byzantine Gathering with Visibility in Graphs
• [cs.DC]Software-Distributed Shared Memory for Heterogeneous Machines: Design and Use Considerations
• [cs.DS]Physarum Multi-Commodity Flow Dynamics
• [cs.DS]Zuckerli: A New Compressed Representation for Graphs
• [cs.GR]TAP-Net: Transport-and-Pack using Reinforcement Learning
• [cs.GR]TopoMap: A 0-dimensional Homology Preserving Projection of High-Dimensional Data
• [cs.GT]Bid Shading in The Brave New World of First-Price Auctions
• [cs.HC]Micro-entries: Encouraging Deeper Evaluation of Mental Models Over Time for Interactive Data Systems
• [cs.IR]Comparing Fair Ranking Metrics
• [cs.IR]Exploring Artist Gender Bias in Music Recommendation
• [cs.IT]A Design Framework for Epsilon-Private Data Disclosure
• [cs.IT]Algebraic geometry codes and some applications
• [cs.IT]Embedded Blockchains: A Synthesis of Blockchains, Spread Spectrum Watermarking, Perceptual Hashing & Digital Signatures
• [cs.IT]On the Size of the Giant Component in Inhomogeneous Random K-out Graphs
• [cs.IT]Optimal Streaming of 360 VR Videos with Perfect, Imperfect and Unknown FoV Viewing Probabilities
• [cs.IT]Optimal Wireless Streaming of Multi-Quality 360 VR Video by Exploiting Natural, Relative Smoothness-enabled and Transcoding-enabled Multicast Opportunities
• [cs.IT]Private Weighted Random Walk Stochastic Gradient Descent
• [cs.IT]Remote Joint Strong Coordination and Reliable Communication
• [cs.IT]Secure Strong Coordination
• [cs.IT]Service Rate Region: A New Aspect of Coded Distributed System Design
• [cs.IT]Smart Meter Data Privacy
• [cs.LG]A Heaviside Function Approximation for Neural Network Binary Classification
• [cs.LG]A Partial Regularization Method for Network Compression
• [cs.LG]A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning
• [cs.LG]Algebraic Neural Networks: Stability Properties
• [cs.LG]All Data Inclusive, Deep Learning Models to Predict Critical Events in the Medical Information Mart for Intensive Care III Database (MIMIC III)
• [cs.LG]An Internal Cluster Validity Index Based on Distance-based Separability Measure
• [cs.LG]Bounded Risk-Sensitive Markov Game and Its Inverse Reward Learning Problem
• [cs.LG]CAGNN: Cluster-Aware Graph Neural Networks for Unsupervised Graph Representation Learning
• [cs.LG]Can AutoML outperform humans? An evaluation on popular OpenML datasets using AutoML Benchmark
• [cs.LG]Change Point Detection by Cross-Entropy Maximization
• [cs.LG]Data Programming by Demonstration: A Framework for Interactively Learning Labeling Functions
• [cs.LG]Error estimate for a universal function approximator of ReLU network with a local connection
• [cs.LG]Explainable Empirical Risk Minimization
• [cs.LG]FairGNN: Eliminating the Discrimination in Graph Neural Networks with Limited Sensitive Attribute Information
• [cs.LG]It’s Hard for Neural Networks To Learn the Game of Life
• [cs.LG]Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints
• [cs.LG]MixBoost: Synthetic Oversampling with Boosted Mixup for Handling Extreme Imbalance
• [cs.LG]Optimality-based Analysis of XCSF Compaction in Discrete Reinforcement Learning
• [cs.LG]Penalty and Augmented Lagrangian Methods for Layer-parallel Training of Residual Networks
• [cs.LG]Physics-Consistent Data-driven Waveform Inversion with Adaptive Data Augmentation
• [cs.LG]Process Mining Meets Causal Machine Learning: Discovering Causal Rules from Event Logs
• [cs.LG]Robust, Accurate Stochastic Optimization for Variational Inference
• [cs.LG]Sample-Efficient Automated Deep Reinforcement Learning
• [cs.LG]Select-ProtoNet: Learning to Select for Few-Shot Disease Subtype Prediction
• [cs.LG]Towards Efficient and Scalable Acceleration of Online Decision Tree Learning on FPGA
• [cs.LG]Understanding the wiring evolution in differentiable neural architecture search
• [cs.LG]Yet Meta Learning Can Adapt Fast, It Can Also Break Easily
• [cs.MA]DRLE: Decentralized Reinforcement Learning at the Edge for Traffic Light Control
• [cs.MA]Quasi-synchronization of bounded confidence opinion dynamics with stochastic asynchronous rule
• [cs.NE]End-to-End Learning of Neuromorphic Wireless Systems for Low-Power Edge Artificial Intelligence
• [cs.NE]Multidisciplinary Design Optimization of Reusable Launch Vehicles for Different Propellants and Objectives
• [cs.NE]Sparse Meta Networks for Sequential Adaptation and its Application to Adaptive Language Modelling
• [cs.NE]Tree Neural Networks in HOL4
• [cs.NI]Cost-aware Feature Selection for IoT Device Classification
• [cs.NI]Local Fast Rerouting with Low Congestion: A Randomized Approach
• [cs.RO]Detection-Aware Trajectory Generation for a Drone Cinematographer
• [cs.RO]Dexterous Robotic Grasping with Object-Centric Visual Affordances
• [cs.RO]Evaluation of a Skill-based Control Architecture for a Visual Inspection-oriented Aerial Platform
• [cs.RO]Proposed Efficient Design for Unmanned Surface Vehicles
• [cs.RO]Secure Encoded Instruction Graphs for End-to-End Data Validation in Autonomous Robots
• [cs.SE]Automated identification of metamorphic test scenarios for an ocean-modeling application
• [cs.SE]P6: A Declarative Language for Integrating Machine Learning in Visual Analytics
• [cs.SE]Smoke Testing for Machine Learning: Simple Tests to Discover Severe Defects
• [cs.SI]How Twitter affects the perception of public opinion: Two case studies
• [cs.SI]Internal migration and mobile communication patterns among pairs with strong ties
• [cs.SI]Online Community Detection for Event Streams on Networks
• [econ.EM]A Robust Score-Driven Filter for Multivariate Time Series
• [eess.AS]Convolutional Speech Recognition with Pitch and Voice Quality Features
• [eess.AS]Detecting Parkinson’s Disease from Speech-task in an accessible and interpretable manner
• [eess.AS]HiFiSinger: Towards High-Fidelity Neural Singing Voice Synthesis
• [eess.AS]Knowing What to Listen to: Early Attention for Deep Speech Representation Learning
• [eess.IV]CNN-Based Ultrasound Image Reconstruction for Ultrafast Displacement Tracking
• [eess.IV]Fundus Image Analysis for Age Related Macular Degeneration: ADAM-2020 Challenge Report
• [eess.IV]Heightmap Reconstruction of Macula on Color Fundus Images Using Conditional Generative Adversarial Networks
• [eess.IV]Limited View Tomographic Reconstruction Using a Deep Recurrent Framework with Residual Dense Spatial-Channel Attention Network and Sinogram Consistency
• [eess.IV]Multimodal brain tumor classification
• [eess.IV]Real Image Super Resolution Via Heterogeneous Model using GP-NAS
• [eess.IV]When Image Decomposition Meets Deep Learning: A Novel Infrared and Visible Image Fusion Method
• [eess.SP]Deep Learning Based Antenna Selection for Channel Extrapolation in FDD Massive MIMO
• [eess.SP]Deep Learning Optimized Sparse Antenna Activation for Reconfigurable Intelligent Surface Assisted Communication
• [hep-th]Quantum stabilizer codes, lattices, and CFTs
• [math.NA]Kernel Interpolation of High Dimensional Scattered Data
• [math.OC]Distributed Online Optimization via Gradient Tracking with Adaptive Momentum
• [math.OC]Heterogeneous Explore-Exploit Strategies on Multi-Star Networks
• [math.ST]Inaccuracy measures for concomitants of GOS in Morgenstern family
• [physics.bio-ph]Computational prediction of RNA tertiary structures using machine learning methods
• [physics.flu-dyn]Transfer learning for nonlinear dynamics and its application to fluid turbulence
• [physics.soc-ph]Adaptive Reinforcement Learning Model for Simulation of Urban Mobility during Crises
• [q-bio.BM]Learning from Protein Structure with Geometric Vector Perceptrons
• [quant-ph]Quantum Discriminator for Binary Classification
• [quant-ph]Quantum Long Short-Term Memory
• [stat.CO]Globally-centered autocovariances in MCMC
• [stat.ME]A Hierarchical Meta-Analysis for Settings Involving Multiple Outcomes across Multiple Cohorts
• [stat.ME]Adaptive Randomization in Network Data
• [stat.ME]Fisher transformation based Confidence Intervals of Correlations in Fixed- and Random-Effects Meta-Analysis
• [stat.ME]Probabilistic Forecasting for Daily Electricity Loads and Quantiles for Curve-to-Curve Regression
• [stat.ME]Spectral estimation for spatial point patterns
• [stat.ME]Statistical Inference for distributions with one Poisson conditional
• [stat.ME]Statistical characterization and time-series modeling of seismic noise
• [stat.ME]The sceptical Bayes factor for the assessment of replication success
• [stat.ME]Unfolding-Model-Based Visualization: Theory, Method and Applications
• [stat.ML]Bayesian Perceptron: Towards fully Bayesian Neural Networks
• [stat.ML]Clustering of Nonnegative Data and an Application to Matrix Completion
• [stat.ML]Large Dimensional Analysis and Improvement of Multi Task Learning
• [stat.ML]Non-parametric generalized linear model
• [stat.ML]On the study of the Beran estimator for generalized censoring indicators
• [stat.ML]Quasi-symplectic Langevin Variational Autoencoder
• [stat.ML]Ramifications of Approximate Posterior Inference for Bayesian Deep Learning in Adversarial and Out-of-Distribution Settings
• [stat.ML]Simulation of an Elevator Group Control Using Generative Adversarial Networks and Related AI Tools
·····································
• [cs.AI]AI solutions for drafting in Magic: the Gathering
Henry N. Ward, Daniel J. Brooks, Dan Troha, Bobby Mills, Arseny S. Khakhalin
http://arxiv.org/abs/2009.00655v2
• [cs.AI]Action and Perception as Divergence Minimization
Danijar Hafner, Pedro A. Ortega, Jimmy Ba, Thomas Parr, Karl Friston, Nicolas Heess
http://arxiv.org/abs/2009.01791v1
• [cs.AI]Derived metrics for the game of Go — intrinsic network strength assessment and cheat-detection
Attila Egri-Nagy, Antti Törmänen
http://arxiv.org/abs/2009.01606v1
• [cs.AI]FairXGBoost: Fairness-aware Classification in XGBoost
Srinivasan Ravichandran, Drona Khurana, Bharath Venkatesh, Narayanan Unny Edakunni
http://arxiv.org/abs/2009.01442v1
• [cs.AI]Fairness in the Eyes of the Data: Certifying Machine-Learning Models
Shahar Segal, Yossi Adi, Benny Pinkas, Carsten Baum, Chaya Ganesh, Joseph Keshet
http://arxiv.org/abs/2009.01534v1
• [cs.AI]Grounded Language Learning Fast and Slow
Felix Hill, Olivier Tieleman, Tamara von Glehn, Nathaniel Wong, Hamza Merzic, Stephen Clark
http://arxiv.org/abs/2009.01719v1
• [cs.AI]Learning to Infer User Hidden States for Online Sequential Advertising
Zhaoqing Peng, Junqi Jin, Lan Luo, Yaodong Yang, Rui Luo, Jun Wang, Weinan Zhang, Haiyang Xu, Miao Xu, Chuan Yu, Tiejian Luo, Han Li, Jian Xu, Kun Gai
http://arxiv.org/abs/2009.01453v1
• [cs.AI]On Population-Based Algorithms for Distributed Constraint Optimization Problems
Saaduddin Mahmud, Md. Mosaddek Khan, Nicholas R. Jennings
http://arxiv.org/abs/2009.01625v1
• [cs.AI]SEDRo: A Simulated Environment for Developmental Robotics
Aishwarya Pothula, Md Ashaduzzaman Rubel Mondol, Sanath Narasimhan, Sm Mazharul Islam, Deokgun Park
http://arxiv.org/abs/2009.01810v1
• [cs.AI]User Intention Recognition and Requirement Elicitation Method for Conversational AI Services
Junrui Tian, Zhiying Tu, Zhongjie Wang, Xiaofei Xu, Min Liu
http://arxiv.org/abs/2009.01509v1
• [cs.AR]An Ensemble Learning Approach for In-situ Monitoring of FPGA Dynamic Power
Zhe Lin, Sharad Sinha, Wei Zhang
http://arxiv.org/abs/2009.01432v1
• [cs.AR]Decision Tree Based Hardware Power Monitoring for Run Time Dynamic Power Management in FPGA
Zhe Lin, Wei Zhang, Sharad Sinha
http://arxiv.org/abs/2009.01434v1
• [cs.CE]Accelerating engineering design by automatic selection of simulation cases through Pool-Based Active Learning
José Hugo C. Gaspar Elsas, Nicholas A. G. Casaprima, Ivan F. M. Menezes
http://arxiv.org/abs/2009.01420v1
• [cs.CL]A Practical Chinese Dependency Parser Based on A Large-scale Dataset
Shuai Zhang, Lijie Wang, Ke Sun, Xinyan Xiao
http://arxiv.org/abs/2009.00901v2
• [cs.CL]A Python Library for Exploratory Data Analysis and Knowledge Discovery on Twitter Data
Mario Graff, Daniela Moctezuma, Sabino Miranda-Jiménez, Eric S. Tellez
http://arxiv.org/abs/2009.01826v1
• [cs.CL]A Simple Global Neural Discourse Parser
Yichu Zhou, Omri Koshorek, Vivek Srikumar, Jonathan Berant
http://arxiv.org/abs/2009.01312v1
• [cs.CL]Biomedical named entity recognition using BERT in the machine reading comprehension framework
Cong Sun, Zhihao Yang, Lei Wang, Yin Zhang, Hongfei Lin, Jian Wang
http://arxiv.org/abs/2009.01560v1
• [cs.CL]Comparative Evaluation of Pretrained Transfer Learning Models on Automatic Short Answer Grading
Sasi Kiran Gaddipati, Deebul Nair, Paul G. Plöger
http://arxiv.org/abs/2009.01303v1
• [cs.CL]Learning to summarize from human feedback
Nisan Stiennon, Long Ouyang, Jeff Wu, Daniel M. Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, Paul Christiano
http://arxiv.org/abs/2009.01325v1
• [cs.CL]SRQA: Synthetic Reader for Factoid Question Answering
Jiuniu Wang, Wenjia Xu, Xingyu Fu, Yang Wei, Li Jin, Ziyan Chen, Guangluan Xu, Yirong Wu
http://arxiv.org/abs/2009.01630v1
• [cs.CL]The ADAPT Enhanced Dependency Parser at the IWPT 2020 Shared Task
James Barry, Joachim Wagner, Jennifer Foster
http://arxiv.org/abs/2009.01712v1
• [cs.CL]Too good to be true? Predicting author profiles from abusive language
Isabelle van der Vegt, Bennett Kleinberg, Paul Gill
http://arxiv.org/abs/2009.01126v2
• [cs.CL]orgFAQ: A New Dataset and Analysis on Organizational FAQs and User Questions
Guy Lev, Michal Shmueli-Scheuer, Achiya Jerbi, David Konopnicki
http://arxiv.org/abs/2009.01460v1
• [cs.CV]1st Place Solution of LVIS Challenge 2020: A Good Box is not a Guarantee of a Good Mask
Jingru Tan, Gang Zhang, Hanming Deng, Changbao Wang, Lewei Lu, Quanquan Li, Jifeng Dai
http://arxiv.org/abs/2009.01559v1
• [cs.CV]A Comparison of Pre-trained Vision-and-Language Models for Multimodal Representation Learning across Medical Images and Reports
Yikuan Li, Hanyin Wang, Yuan Luo
http://arxiv.org/abs/2009.01523v1
• [cs.CV]Adherent Mist and Raindrop Removal from a Single Image Using Attentive Convolutional Network
Da He, Xiaoyu Shang, Jiajia Luo
http://arxiv.org/abs/2009.01466v1
• [cs.CV]Auto-Classifier: A Robust Defect Detector Based on an AutoML Head
Vasco Lopes, Luís A. Alexandre
http://arxiv.org/abs/2009.01573v1
• [cs.CV]Computational Analysis of Deformable Manifolds: from Geometric Modelling to Deep Learning
Stefan C Schonsheck
http://arxiv.org/abs/2009.01786v1
• [cs.CV]DESC: Domain Adaptation for Depth Estimation via Semantic Consistency
Adrian Lopez-Rodriguez, Krystian Mikolajczyk
http://arxiv.org/abs/2009.01579v1
• [cs.CV]Efficiency in Real-time Webcam Gaze Tracking
Amogh Gudi, Xin Li, Jan van Gemert
http://arxiv.org/abs/2009.01270v1
• [cs.CV]Few-shot Object Detection with Feature Attention Highlight Module in Remote Sensing Images
Zixuan Xiao, Ping Zhong, Yuan Quan, Xuping Yin, Wei Xue
http://arxiv.org/abs/2009.01616v1
• [cs.CV]Flow-edge Guided Video Completion
Chen Gao, Ayush Saraf, Jia-Bin Huang, Johannes Kopf
http://arxiv.org/abs/2009.01835v1
• [cs.CV]Layer-specific Optimization for Mixed Data Flow with Mixed Precision in FPGA Design for CNN-based Object Detectors
Duy Thanh Nguyen, Hyun Kim, Hyuk-Jae Lee
http://arxiv.org/abs/2009.01588v1
• [cs.CV]MIPGAN — Generating Robust and High QualityMorph Attacks Using Identity Prior Driven GAN
Haoyu Zhang, Sushma Venkatesh, Raghavendra Ramachandra, Kiran Raja, Naser Damer, Christoph Busch
http://arxiv.org/abs/2009.01729v1
• [cs.CV]Modeling Global Body Configurations in American Sign Language
Nicholas Wilkins, Beck Cordes Galbraith, Ifeoma Nwogu
http://arxiv.org/abs/2009.01468v1
• [cs.CV]Modification method for single-stage object detectors that allows to exploit the temporal behaviour of a scene to improve detection accuracy
Menua Gevorgyan
http://arxiv.org/abs/2009.01617v1
• [cs.CV]Multi-Loss Weighting with Coefficient of Variations
Rick Groenendijk, Sezer Karaoglu, Theo Gevers, Thomas Mensink
http://arxiv.org/abs/2009.01717v1
• [cs.CV]NITES: A Non-Parametric Interpretable Texture Synthesis Method
Xuejing Lei, Ganning Zhao, C. -C. Jay Kuo
http://arxiv.org/abs/2009.01376v1
• [cs.CV]Noise-Aware Texture-Preserving Low-Light Enhancement
Zohreh Azizi, Xuejing Lei, C. -C Jay Kuo
http://arxiv.org/abs/2009.01385v1
• [cs.CV]Physics-based Shading Reconstruction for Intrinsic Image Decomposition
Anil S. Baslamisli, Yang Liu, Sezer Karaoglu, Theo Gevers
http://arxiv.org/abs/2009.01540v1
• [cs.CV]Ref-NMS: Breaking Proposal Bottlenecks in Two-Stage Referring Expression Grounding
Long Chen, Wenbo Ma, Jun Xiao, Hanwang Zhang, Wei Liu, Shih-Fu Chang
http://arxiv.org/abs/2009.01449v1
• [cs.CV]Robust Object Classification Approach using Spherical Harmonics
Ayman Mukhaimar, Ruwan Tennakoon, Chow Yin Lai, Reza Hoseinnezhad, Alireza Bab-Hadiashar
http://arxiv.org/abs/2009.01369v1
• [cs.CV]SCG-Net: Self-Constructing Graph Neural Networks for Semantic Segmentation
Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg
http://arxiv.org/abs/2009.01599v1
• [cs.CV]Spatial Transformer Point Convolution
Yuan Fang, Chunyan Xu, Zhen Cui, Yuan Zong, Jian Yang
http://arxiv.org/abs/2009.01427v1
• [cs.CV]Synthetic-to-Real Unsupervised Domain Adaptation for Scene Text Detection in the Wild
Weijia Wu, Ning Lu, Enze Xie
http://arxiv.org/abs/2009.01766v1
• [cs.CV]TRACE: Transform Aggregate and Compose Visiolinguistic Representations for Image Search with Text Feedback
Surgan Jandial, Ayush Chopra, Pinkesh Badjatiya, Pranit Chawla, Mausoom Sarkar, Balaji Krishnamurthy
http://arxiv.org/abs/2009.01485v1
• [cs.CV]Tasks Integrated Networks: Joint Detection and Retrieval for Image Search
Lei Zhang, Zhenwei He, Yi Yang, Liang Wang, Xinbo Gao
http://arxiv.org/abs/2009.01438v1
• [cs.CV]Towards Practical Implementations of Person Re-Identification from Full Video Frames
Felix O. Sumari, Luigy Machaca, Jose Huaman, Esteban W. G. Clua, Joris Guérin
http://arxiv.org/abs/2009.01377v1
• [cs.CV]Unsupervised Feedforward Feature (UFF) Learning for Point Cloud Classification and Segmentation
Min Zhang, Pranav Kadam, Shan Liu, C. -C. Jay Kuo
http://arxiv.org/abs/2009.01280v1
• [cs.CV]Unsupervised Point Cloud Registration via Salient Points Analysis (SPA)
Pranav Kadam, Min Zhang, Shan Liu, C. -C. Jay Kuo
http://arxiv.org/abs/2009.01293v1
• [cs.CY]A Theoretical Approach for a Novel Model to Realizing Empathy
Marialejandra Garcia Corretjer, David Miralles, Raquel Ros
http://arxiv.org/abs/2009.01229v1
• [cs.CY]COVID-19: The Information Warfare Paradigm Shift
Jan Kallberg, Rosemary A. Burk, Bhavani Thuraisingham
http://arxiv.org/abs/2009.01267v1
• [cs.CY]Deep Learning in Science
Stefano Bianchini, Moritz Müller, Pierre Pelletier
http://arxiv.org/abs/2009.01575v1
• [cs.CY]Gender Stereotype Reinforcement: Measuring the Gender Bias Conveyed by Ranking Algorithms
Alessandro Fabris, Alberto Purpura, Gianmaria Silvello, Gian Antonio Susto
http://arxiv.org/abs/2009.01334v1
• [cs.CY]Indoor Localization Techniques Within a Home Monitoring Platform
Iuliana Marin, Maria-Iuliana Bocicor, Arthur-Jozsef Molnar
http://arxiv.org/abs/2009.01654v1
• [cs.CY]Reading In-Between the Lines: An Analysis of Dissenter
Erik Rye, Jeremy Blackburn, Robert Beverly
http://arxiv.org/abs/2009.01772v1
• [cs.CY]Unique Exams: Designing assessments for integrity and fairness
Gili Rusak, Lisa Yan
http://arxiv.org/abs/2009.01713v1
• [cs.DB]HyperBench: A Benchmark and Tool for Hypergraphs and Empirical Findings
Wolfgang Fischl, Georg Gottlob, Davide Mario Longo, Reinhard Pichler
http://arxiv.org/abs/2009.01769v1
• [cs.DC]Fast Byzantine Gathering with Visibility in Graphs
Avery Miller, Ullash Saha
http://arxiv.org/abs/2009.01544v1
• [cs.DC]Software-Distributed Shared Memory for Heterogeneous Machines: Design and Use Considerations
Loïc Cudennec
http://arxiv.org/abs/2009.01507v1
• [cs.DS]Physarum Multi-Commodity Flow Dynamics
Vincenzo Bonifaci, Enrico Facca, Frederic Folz, Andreas Karrenbauer, Pavel Kolev, Kurt Mehlhorn, Giovanna Morigi, Golnoosh Shahkarami, Quentin Vermande
http://arxiv.org/abs/2009.01498v1
• [cs.DS]Zuckerli: A New Compressed Representation for Graphs
Luca Versari, Iulia M. Comsa, Alessio Conte, Roberto Grossi
http://arxiv.org/abs/2009.01353v1
• [cs.GR]TAP-Net: Transport-and-Pack using Reinforcement Learning
Ruizhen Hu, Juzhan Xu, Bin Chen, Minglun Gong, Hao Zhang, Hui Huang
http://arxiv.org/abs/2009.01469v1
• [cs.GR]TopoMap: A 0-dimensional Homology Preserving Projection of High-Dimensional Data
Harish Doraiswamy, Julien Tierny, Paulo J. S. Silva, Luis Gustavo Nonato, Claudio Silva
http://arxiv.org/abs/2009.01512v1
• [cs.GT]Bid Shading in The Brave New World of First-Price Auctions
Djordje Gligorijevic, Tian Zhou, Bharatbhushan Shetty, Brendan Kitts, Shengjun Pan, Junwei Pan, Aaron Flores
http://arxiv.org/abs/2009.01360v1
• [cs.HC]Micro-entries: Encouraging Deeper Evaluation of Mental Models Over Time for Interactive Data Systems
Jeremy E. Block, Eric D. Ragan
http://arxiv.org/abs/2009.01282v1
• [cs.IR]Comparing Fair Ranking Metrics
Amifa Raj, Connor Wood, Ananda Montoly, Michael D. Ekstrand
http://arxiv.org/abs/2009.01311v1
• [cs.IR]Exploring Artist Gender Bias in Music Recommendation
Dougal Shakespeare, Lorenzo Porcaro, Emilia Gómez, Carlos Castillo
http://arxiv.org/abs/2009.01715v1
• [cs.IT]A Design Framework for Epsilon-Private Data Disclosure
Amirreza Zamani, Tobias J. Oechtering, Mikael Skoglund
http://arxiv.org/abs/2009.01704v1
• [cs.IT]Algebraic geometry codes and some applications
Alain Couvreur, Hugues Randriambololona
http://arxiv.org/abs/2009.01281v1
• [cs.IT]Embedded Blockchains: A Synthesis of Blockchains, Spread Spectrum Watermarking, Perceptual Hashing & Digital Signatures
Sam Blake
http://arxiv.org/abs/2009.00951v2
• [cs.IT]On the Size of the Giant Component in Inhomogeneous Random K-out Graphs
Mansi Sood, Osman Yagan
http://arxiv.org/abs/2009.01610v1
• [cs.IT]Optimal Streaming of 360 VR Videos with Perfect, Imperfect and Unknown FoV Viewing Probabilities
Lingzhi Zhao, Ying Cui, Chengjun Guo, Zhi Liu
http://arxiv.org/abs/2009.01753v1
• [cs.IT]Optimal Wireless Streaming of Multi-Quality 360 VR Video by Exploiting Natural, Relative Smoothness-enabled and Transcoding-enabled Multicast Opportunities
Kaixuan Long, Ying Cui, Chencheng Ye, Zhi Liu
http://arxiv.org/abs/2009.01632v1
• [cs.IT]Private Weighted Random Walk Stochastic Gradient Descent
Ghadir Ayache, Salim El Rouayheb
http://arxiv.org/abs/2009.01790v1
• [cs.IT]Remote Joint Strong Coordination and Reliable Communication
Giulia Cervia, Tobias J. Oechtering, Mikael Skoglund
http://arxiv.org/abs/2009.01569v1
• [cs.IT]Secure Strong Coordination
Giulia Cervia, German Bassi, Mikael Skoglund
http://arxiv.org/abs/2009.01572v1
• [cs.IT]Service Rate Region: A New Aspect of Coded Distributed System Design
Mehmet Aktas, Gauri Joshi, Swanand Kadhe, Fatemeh Kazemi, Emina Soljanin
http://arxiv.org/abs/2009.01598v1
• [cs.IT]Smart Meter Data Privacy
Giulio Giaconi, Deniz Gunduz, H. Vincent Poor
http://arxiv.org/abs/2009.01364v1
• [cs.LG]A Heaviside Function Approximation for Neural Network Binary Classification
Nathan Tsoi, Yofti Milkessa, Marynel Vázquez
http://arxiv.org/abs/2009.01367v1
• [cs.LG]A Partial Regularization Method for Network Compression
E Zhenqian, Gao Weiguo
http://arxiv.org/abs/2009.01395v1
• [cs.LG]A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning
Martin Mundt, Yong Won Hong, Iuliia Pliushch, Visvanathan Ramesh
http://arxiv.org/abs/2009.01797v1
• [cs.LG]Algebraic Neural Networks: Stability Properties
Alejandro Parada-Mayorga, Alejandro Ribeiro
http://arxiv.org/abs/2009.01433v1
• [cs.LG]All Data Inclusive, Deep Learning Models to Predict Critical Events in the Medical Information Mart for Intensive Care III Database (MIMIC III)
Anubhav Reddy Nallabasannagari, Madhu Reddiboina, Ryan Seltzer, Trevor Zeffiro, Ajay Sharma, Mahendra Bhandari
http://arxiv.org/abs/2009.01366v1
• [cs.LG]An Internal Cluster Validity Index Based on Distance-based Separability Measure
Shuyue Guan, Murray Loew
http://arxiv.org/abs/2009.01328v1
• [cs.LG]Bounded Risk-Sensitive Markov Game and Its Inverse Reward Learning Problem
Ran Tian, Liting Sun, Masayoshi Tomizuka
http://arxiv.org/abs/2009.01495v1
• [cs.LG]CAGNN: Cluster-Aware Graph Neural Networks for Unsupervised Graph Representation Learning
Yanqiao Zhu, Yichen Xu, Feng Yu, Shu Wu, Liang Wang
http://arxiv.org/abs/2009.01674v1
• [cs.LG]Can AutoML outperform humans? An evaluation on popular OpenML datasets using AutoML Benchmark
Marc Hanussek, Matthias Blohm, Maximilien Kintz
http://arxiv.org/abs/2009.01564v1
• [cs.LG]Change Point Detection by Cross-Entropy Maximization
Aurélien Serre, Didier Chételat, Andrea Lodi
http://arxiv.org/abs/2009.01358v1
• [cs.LG]Data Programming by Demonstration: A Framework for Interactively Learning Labeling Functions
Sara Evensen, Chang Ge, Dongjin Choi, Çağatay Demiralp
http://arxiv.org/abs/2009.01444v1
• [cs.LG]Error estimate for a universal function approximator of ReLU network with a local connection
Jae-Mo Kang, Sunghwan Moon
http://arxiv.org/abs/2009.01461v1
• [cs.LG]Explainable Empirical Risk Minimization
A. Jung
http://arxiv.org/abs/2009.01492v1
• [cs.LG]FairGNN: Eliminating the Discrimination in Graph Neural Networks with Limited Sensitive Attribute Information
Enyan Dai, Suhang Wang
http://arxiv.org/abs/2009.01454v1
• [cs.LG]It’s Hard for Neural Networks To Learn the Game of Life
Jacob M. Springer, Garrett T. Kenyon
http://arxiv.org/abs/2009.01398v1
• [cs.LG]Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints
Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa
http://arxiv.org/abs/2009.01721v1
• [cs.LG]MixBoost: Synthetic Oversampling with Boosted Mixup for Handling Extreme Imbalance
Anubha Kabra, Ayush Chopra, Nikaash Puri, Pinkesh Badjatiya, Sukriti Verma, Piyush Gupta, Balaji K
http://arxiv.org/abs/2009.01571v1
• [cs.LG]Optimality-based Analysis of XCSF Compaction in Discrete Reinforcement Learning
Jordan T. Bishop, Marcus Gallagher
http://arxiv.org/abs/2009.01476v1
• [cs.LG]Penalty and Augmented Lagrangian Methods for Layer-parallel Training of Residual Networks
Qi Sun, Hexing Dong, Zewei Chen, Weizhen Dian, Jiacheng Sun, Yitong Sun, Zhenguo Li, Bin Dong
http://arxiv.org/abs/2009.01462v1
• [cs.LG]Physics-Consistent Data-driven Waveform Inversion with Adaptive Data Augmentation
Renán Rojas-Gómez, Jihyun Yang, Youzuo Lin, James Theiler, Brendt Wohlberg
http://arxiv.org/abs/2009.01807v1
• [cs.LG]Process Mining Meets Causal Machine Learning: Discovering Causal Rules from Event Logs
Zahra Dasht Bozorgi, Irene Teinemaa, Marlon Dumas, Marcello La Rosa, Artem Polyvyanyy
http://arxiv.org/abs/2009.01561v1
• [cs.LG]Robust, Accurate Stochastic Optimization for Variational Inference
Akash Kumar Dhaka, Alejandro Catalina, Michael Riis Andersen, Måns Magnusson, Jonathan H. Huggins, Aki Vehtari
http://arxiv.org/abs/2009.00666v2
• [cs.LG]Sample-Efficient Automated Deep Reinforcement Learning
Jörg K. H. Franke, Gregor Köhler, André Biedenkapp, Frank Hutter
http://arxiv.org/abs/2009.01555v1
• [cs.LG]Select-ProtoNet: Learning to Select for Few-Shot Disease Subtype Prediction
Ziyi Yang, Jun Shu, Yong Liang, Deyu Meng, Zongben Xu
http://arxiv.org/abs/2009.00792v2
• [cs.LG]Towards Efficient and Scalable Acceleration of Online Decision Tree Learning on FPGA
Zhe Lin, Sharad Sinha, Wei Zhang
http://arxiv.org/abs/2009.01431v1
• [cs.LG]Understanding the wiring evolution in differentiable neural architecture search
Sirui Xie, Shoukang Hu, Xinjiang Wang, Chunxiao Liu, Jianping Shi, Xunying Liu, Dahua Lin
http://arxiv.org/abs/2009.01272v1
• [cs.LG]Yet Meta Learning Can Adapt Fast, It Can Also Break Easily
Han Xu, Yaxin Li, Xiaorui Liu, Hui Liu, Jiliang Tang
http://arxiv.org/abs/2009.01672v1
• [cs.MA]DRLE: Decentralized Reinforcement Learning at the Edge for Traffic Light Control
Pengyuan Zhou, Xianfu Chen, Zhi Liu, Tristan Braud, Pan Hui, Jussi Kangasharju
http://arxiv.org/abs/2009.01502v1
• [cs.MA]Quasi-synchronization of bounded confidence opinion dynamics with stochastic asynchronous rule
Wei Su, Xueqiao Wang, Ge Chen, Kai Shen
http://arxiv.org/abs/2009.01455v1
• [cs.NE]End-to-End Learning of Neuromorphic Wireless Systems for Low-Power Edge Artificial Intelligence
Nicolas Skatchkovsky, Hyeryung Jang, Osvaldo Simeone
http://arxiv.org/abs/2009.01527v1
• [cs.NE]Multidisciplinary Design Optimization of Reusable Launch Vehicles for Different Propellants and Objectives
Kai Dresia, Simon Jentzsch, Günther Waxenegger-Wilfing, Robson Hahn, Jan Deeken, Michael Oschwald, Fabio Mota
http://arxiv.org/abs/2009.01664v1
• [cs.NE]Sparse Meta Networks for Sequential Adaptation and its Application to Adaptive Language Modelling
Tsendsuren Munkhdalai
http://arxiv.org/abs/2009.01803v1
• [cs.NE]Tree Neural Networks in HOL4
Thibault Gauthier
http://arxiv.org/abs/2009.01827v1
• [cs.NI]Cost-aware Feature Selection for IoT Device Classification
Biswadeep Chakraborty, Dinil Mon Divakaran, Ido Nevat, Gareth W. Peters, Mohan Gurusamy
http://arxiv.org/abs/2009.01368v1
• [cs.NI]Local Fast Rerouting with Low Congestion: A Randomized Approach
Gregor Bankhamer, Robert Elsässer, Stefan Schmid
http://arxiv.org/abs/2009.01497v1
• [cs.RO]Detection-Aware Trajectory Generation for a Drone Cinematographer
Boseong Felipe Jeon, Dongseok Shim, H. Jin Kim
http://arxiv.org/abs/2009.01565v1
• [cs.RO]Dexterous Robotic Grasping with Object-Centric Visual Affordances
Priyanka Mandikal, Kristen Grauman
http://arxiv.org/abs/2009.01439v1
• [cs.RO]Evaluation of a Skill-based Control Architecture for a Visual Inspection-oriented Aerial Platform
Emilio Garcia-Fidalgo, Francisco Bonnin-Pascual, Joan P. Company-Corcoles, Alberto Ortiz
http://arxiv.org/abs/2009.01612v1
• [cs.RO]Proposed Efficient Design for Unmanned Surface Vehicles
Pouyan Asgharian, Zati Hakim Azizul
http://arxiv.org/abs/2009.01284v1
• [cs.RO]Secure Encoded Instruction Graphs for End-to-End Data Validation in Autonomous Robots
Jorge Peña Queralta, Li Qingqing, Eduardo Castelló Ferrer, Tomi Westerlund
http://arxiv.org/abs/2009.01341v1
• [cs.SE]Automated identification of metamorphic test scenarios for an ocean-modeling application
Dilip J. Hiremath, Martin Claus, Wilhelm Hasselbring, Willi Rath
http://arxiv.org/abs/2009.01554v1
• [cs.SE]P6: A Declarative Language for Integrating Machine Learning in Visual Analytics
Jianping Kelvin Li, Kwan-Liu Ma
http://arxiv.org/abs/2009.01399v1
• [cs.SE]Smoke Testing for Machine Learning: Simple Tests to Discover Severe Defects
Steffen Herbold, Tobias Haar
http://arxiv.org/abs/2009.01521v1
• [cs.SI]How Twitter affects the perception of public opinion: Two case studies
Felix Gaisbauer, Armin Pournaki, Sven Banisch, Eckehard Olbrich
http://arxiv.org/abs/2009.01666v1
• [cs.SI]Internal migration and mobile communication patterns among pairs with strong ties
Mikaela Irene D. Fudolig, Daniel Monsivais, Kunal Bhattacharya, Hang-Hyun Jo, Kimmo Kaski
http://arxiv.org/abs/2009.00252v2
• [cs.SI]Online Community Detection for Event Streams on Networks
Guanhua Fang, Owen G. Ward, Tian Zheng
http://arxiv.org/abs/2009.01742v1
• [econ.EM]A Robust Score-Driven Filter for Multivariate Time Series
Enzo D’Innocenzo, Alessandra Luati, Mario Mazzocchi
http://arxiv.org/abs/2009.01517v1
• [eess.AS]Convolutional Speech Recognition with Pitch and Voice Quality Features
Guillermo Cámbara, Jordi Luque, Mireia Farrús
http://arxiv.org/abs/2009.01309v1
• [eess.AS]Detecting Parkinson’s Disease from Speech-task in an accessible and interpretable manner
Wasifur Rahman, Sangwu Lee, Md. Saiful Islam, Abdullah Al Mamun, Victor Antony, Harshil Ratnu, Mohammad Rafayet Ali, Ehsan Hoque
http://arxiv.org/abs/2009.01231v1
• [eess.AS]HiFiSinger: Towards High-Fidelity Neural Singing Voice Synthesis
Jiawei Chen, Xu Tan, Jian Luan, Tao Qin, Tie-Yan Liu
http://arxiv.org/abs/2009.01776v1
• [eess.AS]Knowing What to Listen to: Early Attention for Deep Speech Representation Learning
Amirhossein Hajavi, Ali Etemad
http://arxiv.org/abs/2009.01822v1
• [eess.IV]CNN-Based Ultrasound Image Reconstruction for Ultrafast Displacement Tracking
Dimitris Perdios, Manuel Vonlanthen, Florian Martinez, Marcel Arditi, Jean-Philippe Thiran
http://arxiv.org/abs/2009.01816v1
• [eess.IV]Fundus Image Analysis for Age Related Macular Degeneration: ADAM-2020 Challenge Report
Sharath M Shankaranarayana
http://arxiv.org/abs/2009.01548v1
• [eess.IV]Heightmap Reconstruction of Macula on Color Fundus Images Using Conditional Generative Adversarial Networks
Peyman Tahghighi, Reza A. Zoroofi, Sareh Saffi, Alireza Ramezani
http://arxiv.org/abs/2009.01601v1
• [eess.IV]Limited View Tomographic Reconstruction Using a Deep Recurrent Framework with Residual Dense Spatial-Channel Attention Network and Sinogram Consistency
Bo Zhou, S. Kevin Zhou, James S. Duncan, Chi Liu
http://arxiv.org/abs/2009.01782v1
• [eess.IV]Multimodal brain tumor classification
Marvin Lerousseau, Eric Deutsh, Nikos Paragios
http://arxiv.org/abs/2009.01592v1
• [eess.IV]Real Image Super Resolution Via Heterogeneous Model using GP-NAS
Zhihong Pan, Baopu Li, Teng Xi, Yanwen Fan, Gang Zhang, Jingtuo Liu, Junyu Han, Errui Ding
http://arxiv.org/abs/2009.01371v1
• [eess.IV]When Image Decomposition Meets Deep Learning: A Novel Infrared and Visible Image Fusion Method
Zixiang Zhao, Shuang Xu, Rui Feng, Chunxia Zhang, Junmin Liu, Jiangshe Zhang
http://arxiv.org/abs/2009.01315v1
• [eess.SP]Deep Learning Based Antenna Selection for Channel Extrapolation in FDD Massive MIMO
Yindi Yang, Shun Zhang, Feifei Gao, Chao Xu, Jianpeng Ma, Octavia A. Dobre
http://arxiv.org/abs/2009.01653v1
• [eess.SP]Deep Learning Optimized Sparse Antenna Activation for Reconfigurable Intelligent Surface Assisted Communication
Shunbo Zhang, Shun Zhang, Feifei Gao, Jianpeng Ma, Octavia A. Dobre
http://arxiv.org/abs/2009.01607v1
• [hep-th]Quantum stabilizer codes, lattices, and CFTs
Anatoly Dymarsky, Alfred Shapere
http://arxiv.org/abs/2009.01244v1
• [math.NA]Kernel Interpolation of High Dimensional Scattered Data
Shao-Bo Lin, Xiangyu Chang, Xingping Sun
http://arxiv.org/abs/2009.01514v1
• [math.OC]Distributed Online Optimization via Gradient Tracking with Adaptive Momentum
Guido Carnevale, Francesco Farina, Ivano Notarnicola, Giuseppe Notarstefano
http://arxiv.org/abs/2009.01745v1
• [math.OC]Heterogeneous Explore-Exploit Strategies on Multi-Star Networks
Udari Madhushani, Naomi Leonard
http://arxiv.org/abs/2009.01339v1
• [math.ST]Inaccuracy measures for concomitants of GOS in Morgenstern family
S. Daneshi, A. Nezakati, S. Tahmasebi, M. Longobardi
http://arxiv.org/abs/2009.01800v1
• [physics.bio-ph]Computational prediction of RNA tertiary structures using machine learning methods
Bin Huang, Yuanyang Du, Shuai Zhang, Wenfei Li, Jun Wang, Jian Zhang
http://arxiv.org/abs/2009.01440v1
• [physics.flu-dyn]Transfer learning for nonlinear dynamics and its application to fluid turbulence
Masanobu Inubushi, Susumu Goto
http://arxiv.org/abs/2009.01407v1
• [physics.soc-ph]Adaptive Reinforcement Learning Model for Simulation of Urban Mobility during Crises
Chao Fan, Xiangqi Jiang, Ali Mostafavi
http://arxiv.org/abs/2009.01359v1
• [q-bio.BM]Learning from Protein Structure with Geometric Vector Perceptrons
Bowen Jing, Stephan Eismann, Patricia Suriana, Raphael J. L. Townshend, Ron Dror
http://arxiv.org/abs/2009.01411v1
• [quant-ph]Quantum Discriminator for Binary Classification
Prasanna Date
http://arxiv.org/abs/2009.01235v1
• [quant-ph]Quantum Long Short-Term Memory
Samuel Yen-Chi Chen, Shinjae Yoo, Yao-Lung L. Fang
http://arxiv.org/abs/2009.01783v1
• [stat.CO]Globally-centered autocovariances in MCMC
Medha Agarwal, Dootika Vats
http://arxiv.org/abs/2009.01799v1
• [stat.ME]A Hierarchical Meta-Analysis for Settings Involving Multiple Outcomes across Multiple Cohorts
Tugba Akkaya Hocagil, Louise M. Ryan, Richard J. Cook, Gale A. Richardson, Nancy L. Day, Claire D. Coles, Heather Carmichael Olson, Sandra W. Jacobson, Joseph L. Jacobson
http://arxiv.org/abs/2009.01323v1
• [stat.ME]Adaptive Randomization in Network Data
Zhixin Zhou, Ping Li, Feifang Hu
http://arxiv.org/abs/2009.01273v1
• [stat.ME]Fisher transformation based Confidence Intervals of Correlations in Fixed- and Random-Effects Meta-Analysis
Thilo Welz, Philipp Doebler, Markus Pauly
http://arxiv.org/abs/2009.01522v1
• [stat.ME]Probabilistic Forecasting for Daily Electricity Loads and Quantiles for Curve-to-Curve Regression
Xiuqin Xu, Ying Chen, Yannig Goude, Qiwei Yao
http://arxiv.org/abs/2009.01595v1
• [stat.ME]Spectral estimation for spatial point patterns
Tuomas A. Rajala, Sofia C. Olhede, David J. Murrell
http://arxiv.org/abs/2009.01474v1
• [stat.ME]Statistical Inference for distributions with one Poisson conditional
Barry C. Arnold, B. G. Manjunath
http://arxiv.org/abs/2009.01296v1
• [stat.ME]Statistical characterization and time-series modeling of seismic noise
Kanchan Aggarwal, Siddhartha Mukhopadhyay, Arun K Tangirala
http://arxiv.org/abs/2009.01549v1
• [stat.ME]The sceptical Bayes factor for the assessment of replication success
Samuel Pawel, Leonhard Held
http://arxiv.org/abs/2009.01520v1
• [stat.ME]Unfolding-Model-Based Visualization: Theory, Method and Applications
Yunxiao Chen, Zhiliang Ying, Haoran Zhang
http://arxiv.org/abs/2009.01551v1
• [stat.ML]Bayesian Perceptron: Towards fully Bayesian Neural Networks
Marco F. Huber
http://arxiv.org/abs/2009.01730v1
• [stat.ML]Clustering of Nonnegative Data and an Application to Matrix Completion
C. Strohmeier, D. Needell
http://arxiv.org/abs/2009.01279v1
• [stat.ML]Large Dimensional Analysis and Improvement of Multi Task Learning
Malik Tiomoko, Romain Couillet, Hafiz Tiomoko
http://arxiv.org/abs/2009.01591v1
• [stat.ML]Non-parametric generalized linear model
Matthew Dowling, Yuan Zhao, Il Memming Park
http://arxiv.org/abs/2009.01362v1
• [stat.ML]On the study of the Beran estimator for generalized censoring indicators
Mikael Escobar-Bach, Olivier Goudet
http://arxiv.org/abs/2009.01726v1
• [stat.ML]Quasi-symplectic Langevin Variational Autoencoder
Zihao Wang, Hervé Delingette
http://arxiv.org/abs/2009.01675v1
• [stat.ML]Ramifications of Approximate Posterior Inference for Bayesian Deep Learning in Adversarial and Out-of-Distribution Settings
John Mitros, Arjun Pakrashi, Brian Mac Namee
http://arxiv.org/abs/2009.01798v1
• [stat.ML]Simulation of an Elevator Group Control Using Generative Adversarial Networks and Related AI Tools
Tom Peetz, Sebastian Vogt, Martin Zaefferer, Thomas Bartz-Beielstein