astro-ph.CO - 宇宙学和天体物理学

    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.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.RO - 机器人学 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 hep-lat - 高能物理晶格 math.OC - 优化与控制 math.ST - 统计理论 physics.soc-ph - 物理学与社会 q-fin.PM - 投资组合管理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [astro-ph.CO]Mass Estimation of Galaxy Clusters with Deep Learning I: Sunyaev-Zel’dovich Effect
    • [astro-ph.IM]Agile Earth observation satellite scheduling over 20 years: formulations, methods and future directions
    • [cs.AI]A Survey of End-to-End Driving: Architectures and Training Methods
    • [cs.AI]Accelerating and Improving AlphaZero Using Population Based Training
    • [cs.AI]Efficient Rule Learning with Template Saturation for Knowledge Graph Completion
    • [cs.AI]Online Guest Detection in a Smart Home using Pervasive Sensors and Probabilistic Reasoning
    • [cs.CL]Know thy corpus! Robust methods for digital curation of Web corpora
    • [cs.CL]Local Contextual Attention with Hierarchical Structure for Dialogue Act Recognition
    • [cs.CL]MixPoet: Diverse Poetry Generation via Learning Controllable Mixed Latent Space
    • [cs.CL]Review-guided Helpful Answer Identification in E-commerce
    • [cs.CL]Sentence Level Human Translation Quality Estimation with Attention-based Neural Networks
    • [cs.CL]Using word embeddings to improve the discriminability of co-occurrence text networks
    • [cs.CL]WAC: A Corpus of Wikipedia Conversations for Online Abuse Detection
    • [cs.CR]Automating Botnet Detection with Graph Neural Networks
    • [cs.CV]A Spatial-Temporal Attentive Network with Spatial Continuity for Trajectory Prediction
    • [cs.CV]Adaptive Graph Convolutional Network with Attention Graph Clustering for Co-saliency Detection
    • [cs.CV]Analyzing Visual Representations in Embodied Navigation Tasks
    • [cs.CV]Automatic Lesion Detection System (ALDS) for Skin Cancer Classification Using SVM and Neural Classifiers
    • [cs.CV]BIHL:A Fast and High Performance Object Proposals based on Binarized HL Frequency
    • [cs.CV]Belief Propagation Reloaded: Learning BP-Layers for Labeling Problems
    • [cs.CV]BigGAN-based Bayesian reconstruction of natural images from human brain activity
    • [cs.CV]Deep Domain-Adversarial Image Generation for Domain Generalisation
    • [cs.CV]Dual Temporal Memory Network for Efficient Video Object Segmentation
    • [cs.CV]Extending Maps with Semantic and Contextual Object Information for Robot Navigation: a Learning-Based Framework using Visual and Depth Cues
    • [cs.CV]Gimme Signals: Discriminative signal encoding for multimodal activity recognition
    • [cs.CV]Harmonizing Transferability and Discriminability for Adapting Object Detectors
    • [cs.CV]Interaction Graphs for Object Importance Estimation in On-road Driving Videos
    • [cs.CV]Is There Tradeoff between Spatial and Temporal in Video Super-Resolution?
    • [cs.CV]LaserFlow: Efficient and Probabilistic Object Detection and Motion Forecasting
    • [cs.CV]Partial Weight Adaptation for Robust DNN Inference
    • [cs.CV]PointINS: Point-based Instance Segmentation
    • [cs.CV]Probabilistic Future Prediction for Video Scene Understanding
    • [cs.CV]Pyramidal Edge-maps based Guided Thermal Super-resolution
    • [cs.CV]Semantic Pyramid for Image Generation
    • [cs.CY]Large-Scale Educational Question Analysis with Partial Variational Auto-encoders
    • [cs.DC]A Fault-Tolerance Shim for Serverless Computing
    • [cs.DC]Characterizing Optimizations to Memory Access Patterns using Architecture-Independent Program Features
    • [cs.DC]On Exploiting Transaction Concurrency To Speed Up Blockchains
    • [cs.HC]CRWIZ: A Framework for Crowdsourcing Real-Time Wizard-of-Oz Dialogues
    • [cs.IR]Tracing patients’ PLOD with mobile phones: Mitigation of epidemic risks through patients’ locational open data
    • [cs.IT]Non Orthogonal Multiple Access with Orthogonal Time Frequency Space Signal Transmission
    • [cs.LG]A General Framework for Learning Mean-Field Games
    • [cs.LG]Analysis of Hyper-Parameters for Small Games: Iterations or Epochs in Self-Play?
    • [cs.LG]Autoencoders
    • [cs.LG]Balancedness and Alignment are Unlikely in Linear Neural Networks
    • [cs.LG]Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case Study
    • [cs.LG]Coronary Artery Segmentation from Intravascular Optical Coherence Tomography Using Deep Capsules
    • [cs.LG]Dynamic transformation of prior knowledge intoBayesian models for data streams
    • [cs.LG]Graph Convolutional Topic Model for Data Streams
    • [cs.LG]Heterogeneous Relational Reasoning in Knowledge Graphs with Reinforcement Learning
    • [cs.LG]Interference and Generalization in Temporal Difference Learning
    • [cs.LG]Invariant Causal Prediction for Block MDPs
    • [cs.LG]Learning Graph Embedding with Limited Labeled Data: An Efficient Sampling Approach
    • [cs.LG]Learning and Fairness in Energy Harvesting: A Maximin Multi-Armed Bandits Approach
    • [cs.LG]Minor Constraint Disturbances for Deep Semi-supervised Learning
    • [cs.LG]Model Agnostic Multilevel Explanations
    • [cs.LG]On the effectiveness of convolutional autoencoders on image-based personalized recommender systems
    • [cs.LG]Sample Efficient Reinforcement Learning through Learning from Demonstrations in Minecraft
    • [cs.LG]Sparse Graphical Memory for Robust Planning
    • [cs.LG]Taylor Expansion Policy Optimization
    • [cs.LG]Ultra Efficient Transfer Learning with Meta Update for Cross Subject EEG Classification
    • [cs.LG]Wasserstein-based Graph Alignment
    • [cs.LG]What Information Does a ResNet Compress?
    • [cs.LG]When are Non-Parametric Methods Robust?
    • [cs.LG]Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling
    • [cs.RO]Action for Better Prediction
    • [cs.RO]Computationally Efficient Obstacle Avoidance Trajectory Planner for UAVs Based on Heuristic Angular Search Method
    • [cs.RO]Geometry-aware Dynamic Movement Primitives
    • [cs.RO]Human Grasp Classification for Reactive Human-to-Robot Handovers
    • [cs.RO]LIBRE: The Multiple 3D LiDAR Dataset
    • [cs.RO]Learning to Generalize Across Long-Horizon Tasks from Human Demonstrations
    • [cs.RO]Long-term Prediction of Vehicle Behavior using Short-term Uncertainty-aware Trajectories and High-definition Maps
    • [cs.RO]Towards a Framework for Visual Intelligence in Service Robotics: Epistemic Requirements and Gap Analysis
    • [cs.SI]NesTPP: Modeling Thread Dynamics in Online Discussion Forums
    • [cs.SI]Snapshot Samplings of the Bitcoin Transaction Network and Analysis of Cryptocurrency Growth
    • [econ.EM]Targeting Customers under Response-Dependent Costs
    • [eess.IV]Advanced Deep Learning Methodologies for Skin Cancer Classification in Prodromal Stages
    • [eess.IV]Estimation of Rate Control Parameters for Video Coding Using CNN
    • [eess.IV]Random smooth gray value transformations for cross modality learning with gray value invariant networks
    • [eess.SP]A Power-Efficient Binary-Weight Spiking Neural Network Architecture for Real-Time Object Classification
    • [eess.SP]RSSI-Based Hybrid Beamforming Design with Deep Learning
    • [eess.SY]Data Set Description: Identifying the Physics Behind an Electric Motor — Data-Driven Learning of the Electrical Behavior (Part II)
    • [eess.SY]Identification of AC Networks via Online Learning
    • [eess.SY]Robust tracking of an unknown trajectory with a multi-rotor UAV: A high-gain observer approach
    • [eess.SY]SIS Epidemic Model under Mobility on Multi-layer Networks
    • [hep-lat]Equivariant flow-based sampling for lattice gauge theory
    • [math.OC]Boosting Frank-Wolfe by Chasing Gradients
    • [math.OC]Communication Efficient Sparsification for Large Scale Machine Learning
    • [math.ST]Existence and Uniqueness of the Kronecker Covariance MLE
    • [math.ST]SVM Learning Rates for Data with Low Intrinsic Dimension
    • [math.ST]Statistical Inference for High Dimensional Panel Functional Time Series
    • [physics.soc-ph]The impact of incorrect social information on collective wisdom in human groups
    • [q-fin.PM]Application of Deep Q-Network in Portfolio Management
    • [stat.AP]A Note on Early Epidemiological Analysis of Coronavirus Disease 2019 Outbreak using Crowdsourced Data
    • [stat.AP]Bayesian Posterior Interval Calibration to Improve the Interpretability of Observational Studies
    • [stat.AP]Power and Sample Size for Marginal Structural Models
    • [stat.AP]Spatial multiresolution analysis approach to identify crash hotspots and estimate crash risk
    • [stat.CO]Extending the MaCSim approach using similarity weight matrix to assess the accuracy of record linkage
    • [stat.ME]A comparison of parameter estimation in function-on-function regression
    • [stat.ME]A spatial causal analysis of wildland fire-contributed PM2.5 using numerical model output
    • [stat.ME]Default Bayes Factors for Testing the (In)equality of Several Population Variances
    • [stat.ME]Estimating Basis Functions in Massive Fields under the Spatial Mixed Effects Model
    • [stat.ME]Spatial Tweedie exponential dispersion models
    • [stat.ME]Use of Cross-validation Bayes Factors to Test Equality of Two Densities
    • [stat.ME]VC-BART: Bayesian trees for varying coefficients
    • [stat.ML]An Evaluation of Change Point Detection Algorithms
    • [stat.ML]B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data
    • [stat.ML]BayesFlow: Learning complex stochastic models with invertible neural networks

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

    • [astro-ph.CO]Mass Estimation of Galaxy Clusters with Deep Learning I: Sunyaev-Zel’dovich Effect
    Nikhel Gupta, Christian L. Reichardt
    http://arxiv.org/abs/2003.06135v1

    • [astro-ph.IM]Agile Earth observation satellite scheduling over 20 years: formulations, methods and future directions
    Xinwei Wang, Guohua Wu, Lining Xing, Witold Pedrycz
    http://arxiv.org/abs/2003.06169v1

    • [cs.AI]A Survey of End-to-End Driving: Architectures and Training Methods
    Ardi Tampuu, Maksym Semikin, Naveed Muhammad, Dmytro Fishman, Tambet Matiisen
    http://arxiv.org/abs/2003.06404v1

    • [cs.AI]Accelerating and Improving AlphaZero Using Population Based Training
    Ti-Rong Wu, Ting-Han Wei, I-Chen Wu
    http://arxiv.org/abs/2003.06212v1

    • [cs.AI]Efficient Rule Learning with Template Saturation for Knowledge Graph Completion
    Yulong Gu, Yu Guan, Paolo Missier
    http://arxiv.org/abs/2003.06071v1

    • [cs.AI]Online Guest Detection in a Smart Home using Pervasive Sensors and Probabilistic Reasoning
    Jennifer Renoux, Uwe Köckemann, Amy Loutfi
    http://arxiv.org/abs/2003.06347v1

    • [cs.CL]Know thy corpus! Robust methods for digital curation of Web corpora
    Serge Sharoff
    http://arxiv.org/abs/2003.06389v1

    • [cs.CL]Local Contextual Attention with Hierarchical Structure for Dialogue Act Recognition
    Zhigang Dai, Jinhua Fu, Qile Zhu, Hengbin Cui, Xiaolong li, Yuan Qi
    http://arxiv.org/abs/2003.06044v1

    • [cs.CL]MixPoet: Diverse Poetry Generation via Learning Controllable Mixed Latent Space
    Xiaoyuan Yi, Ruoyu Li, Cheng Yang, Wenhao Li, Maosong Sun
    http://arxiv.org/abs/2003.06094v1

    • [cs.CL]Review-guided Helpful Answer Identification in E-commerce
    Wenxuan Zhang, Wai Lam, Yang Deng, Jing Ma
    http://arxiv.org/abs/2003.06209v1

    • [cs.CL]Sentence Level Human Translation Quality Estimation with Attention-based Neural Networks
    Yu Yuan, Serge Sharoff
    http://arxiv.org/abs/2003.06381v1

    • [cs.CL]Using word embeddings to improve the discriminability of co-occurrence text networks
    Laura V. C. Quispe, Jorge A. V. Tohalino, Diego R. Amancio
    http://arxiv.org/abs/2003.06279v1

    • [cs.CL]WAC: A Corpus of Wikipedia Conversations for Online Abuse Detection
    Noé Cecillon, Vincent Labatut, Richard Dufour, Georges Linares
    http://arxiv.org/abs/2003.06190v1

    • [cs.CR]Automating Botnet Detection with Graph Neural Networks
    Jiawei Zhou, Zhiying Xu, Alexander M. Rush, Minlan Yu
    http://arxiv.org/abs/2003.06344v1

    • [cs.CV]A Spatial-Temporal Attentive Network with Spatial Continuity for Trajectory Prediction
    Beihao Xia, Conghao Wang, Qinmu Peng, Xinge You, Dacheng Tao
    http://arxiv.org/abs/2003.06107v1

    • [cs.CV]Adaptive Graph Convolutional Network with Attention Graph Clustering for Co-saliency Detection
    Kaihua Zhang, Tengpeng Li, Shiwen Shen, Bo Liu, Jin Chen, Qingshan Liu
    http://arxiv.org/abs/2003.06167v1

    • [cs.CV]Analyzing Visual Representations in Embodied Navigation Tasks
    Erik Wijmans, Julian Straub, Dhruv Batra, Irfan Essa, Judy Hoffman, Ari Morcos
    http://arxiv.org/abs/2003.05993v1

    • [cs.CV]Automatic Lesion Detection System (ALDS) for Skin Cancer Classification Using SVM and Neural Classifiers
    Muhammad Ali Farooq, Muhammad Aatif Mobeen Azhar, Rana Hammad Raza
    http://arxiv.org/abs/2003.06276v1

    • [cs.CV]BIHL:A Fast and High Performance Object Proposals based on Binarized HL Frequency
    Jiang Chao, Liang Huawei, Wang Zhiling
    http://arxiv.org/abs/2003.06124v1

    • [cs.CV]Belief Propagation Reloaded: Learning BP-Layers for Labeling Problems
    Patrick Knöbelreiter, Christian Sormann, Alexander Shekhovtsov, Friedrich Fraundorfer, Thomas Pock
    http://arxiv.org/abs/2003.06258v1

    • [cs.CV]BigGAN-based Bayesian reconstruction of natural images from human brain activity
    Kai Qiao, Jian Chen, Linyuan Wang, Chi Zhang, Li Tong, Bin Yan
    http://arxiv.org/abs/2003.06105v1

    • [cs.CV]Deep Domain-Adversarial Image Generation for Domain Generalisation
    Kaiyang Zhou, Yongxin Yang, Timothy Hospedales, Tao Xiang
    http://arxiv.org/abs/2003.06054v1

    • [cs.CV]Dual Temporal Memory Network for Efficient Video Object Segmentation
    Kaihua Zhang, Long Wang, Dong Liu, Bo Liu, Qingshan Liu, Zhu Li
    http://arxiv.org/abs/2003.06125v1

    • [cs.CV]Extending Maps with Semantic and Contextual Object Information for Robot Navigation: a Learning-Based Framework using Visual and Depth Cues
    Renato Martins, Dhiego Bersan, Mario F. M. Campos, Erickson R. Nascimento
    http://arxiv.org/abs/2003.06336v1

    • [cs.CV]Gimme Signals: Discriminative signal encoding for multimodal activity recognition
    Raphael Memmesheimer, Nick Theisen, Dietrich Paulus
    http://arxiv.org/abs/2003.06156v1

    • [cs.CV]Harmonizing Transferability and Discriminability for Adapting Object Detectors
    Chaoqi Chen, Zebiao Zheng, Xinghao Ding, Yue Huang, Qi Dou
    http://arxiv.org/abs/2003.06297v1

    • [cs.CV]Interaction Graphs for Object Importance Estimation in On-road Driving Videos
    Zehua Zhang, Ashish Tawari, Sujitha Martin, David Crandall
    http://arxiv.org/abs/2003.06045v1

    • [cs.CV]Is There Tradeoff between Spatial and Temporal in Video Super-Resolution?
    Haochen Zhang, Dong Liu, Zhiwei Xiong
    http://arxiv.org/abs/2003.06141v1

    • [cs.CV]LaserFlow: Efficient and Probabilistic Object Detection and Motion Forecasting
    Gregory P. Meyer, Jake Charland, Shreyash Pandey, Ankit Laddha, Carlos Vallespi-Gonzalez, Carl K. Wellington
    http://arxiv.org/abs/2003.05982v1

    • [cs.CV]Partial Weight Adaptation for Robust DNN Inference
    Xiufeng Xie, Kyu-Han Kim
    http://arxiv.org/abs/2003.06131v1

    • [cs.CV]PointINS: Point-based Instance Segmentation
    Lu Qi, Xiangyu Zhang, Yingcong Chen, Yukang Chen, Jian Sun, Jiaya Jia
    http://arxiv.org/abs/2003.06148v1

    • [cs.CV]Probabilistic Future Prediction for Video Scene Understanding
    Anthony Hu, Fergal Cotter, Nikhil Mohan, Corina Gurau, Alex Kendall
    http://arxiv.org/abs/2003.06409v1

    • [cs.CV]Pyramidal Edge-maps based Guided Thermal Super-resolution
    Honey Gupta, Kaushik Mitra
    http://arxiv.org/abs/2003.06216v1

    • [cs.CV]Semantic Pyramid for Image Generation
    Assaf Shocher, Yossi Gandelsmam, Inbar Mosseri, Michal Yarom, Michal Irani, William T. Freeman, Tali Dekel
    http://arxiv.org/abs/2003.06221v1

    • [cs.CY]Large-Scale Educational Question Analysis with Partial Variational Auto-encoders
    Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, Jose Miguel Hernandez-Lobato, Simon Peyton Jones, Cheng Zhang
    http://arxiv.org/abs/2003.05980v1

    • [cs.DC]A Fault-Tolerance Shim for Serverless Computing
    Vikram Sreekanti, Chenggang Wu, Saurav Chhatrapati, Joseph E. Gonzalez, Joseph M. Hellerstein, Jose M. Faleiro
    http://arxiv.org/abs/2003.06007v1

    • [cs.DC]Characterizing Optimizations to Memory Access Patterns using Architecture-Independent Program Features
    Aditya Chilukuri, Josh Milthorpe, Beau Johnston
    http://arxiv.org/abs/2003.06064v1

    • [cs.DC]On Exploiting Transaction Concurrency To Speed Up Blockchains
    Daniël Reijsbergen, Tien Tuan Anh Dinh
    http://arxiv.org/abs/2003.06128v1

    • [cs.HC]CRWIZ: A Framework for Crowdsourcing Real-Time Wizard-of-Oz Dialogues
    Francisco J. Chiyah Garcia, José Lopes, Xingkun Liu, Helen Hastie
    http://arxiv.org/abs/2003.05995v1

    • [cs.IR]Tracing patients’ PLOD with mobile phones: Mitigation of epidemic risks through patients’ locational open data
    Ikki Ohmukai, Yasunori Yamamoto, Maori Ito, Takashi Okumura
    http://arxiv.org/abs/2003.06199v1

    • [cs.IT]Non Orthogonal Multiple Access with Orthogonal Time Frequency Space Signal Transmission
    Aritra Chatterjee, Vivek Rangamgari, Shashank Tiwari, Suvra Sekhar Das
    http://arxiv.org/abs/2003.06387v1

    • [cs.LG]A General Framework for Learning Mean-Field Games
    Xin Guo, Anran Hu, Renyuan Xu, Junzi Zhang
    http://arxiv.org/abs/2003.06069v1

    • [cs.LG]Analysis of Hyper-Parameters for Small Games: Iterations or Epochs in Self-Play?
    Hui Wang, Michael Emmerich, Mike Preuss, Aske Plaat
    http://arxiv.org/abs/2003.05988v1

    • [cs.LG]Autoencoders
    Dor Bank, Noam Koenigstein, Raja Giryes
    http://arxiv.org/abs/2003.05991v1

    • [cs.LG]Balancedness and Alignment are Unlikely in Linear Neural Networks
    Adityanarayanan Radhakrishnan, Eshaan Nichani, Daniel Bernstein, Caroline Uhler
    http://arxiv.org/abs/2003.06340v1

    • [cs.LG]Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case Study
    Assaf Dauber, Meir Feder, Tomer Koren, Roi Livni
    http://arxiv.org/abs/2003.06152v1

    • [cs.LG]Coronary Artery Segmentation from Intravascular Optical Coherence Tomography Using Deep Capsules
    Arjun Balaji, Lachlan Kelsey, Kamran Majeed, Carl Schultz, Barry Doyle
    http://arxiv.org/abs/2003.06080v1

    • [cs.LG]Dynamic transformation of prior knowledge intoBayesian models for data streams
    Tran Xuan Bach, Nguyen Duc Anh, Linh Ngo Van, Khoat Than
    http://arxiv.org/abs/2003.06123v1

    • [cs.LG]Graph Convolutional Topic Model for Data Streams
    Linh Ngo Van, Bach Tran, Khoat Than
    http://arxiv.org/abs/2003.06112v1

    • [cs.LG]Heterogeneous Relational Reasoning in Knowledge Graphs with Reinforcement Learning
    Mandana Saebi, Steven Krieg, Chuxu Zhang, Meng Jiang, Nitesh Chawla
    http://arxiv.org/abs/2003.06050v1

    • [cs.LG]Interference and Generalization in Temporal Difference Learning
    Emmanuel Bengio, Joelle Pineau, Doina Precup
    http://arxiv.org/abs/2003.06350v1

    • [cs.LG]Invariant Causal Prediction for Block MDPs
    Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup
    http://arxiv.org/abs/2003.06016v1

    • [cs.LG]Learning Graph Embedding with Limited Labeled Data: An Efficient Sampling Approach
    Qirui Li, Xiaoming Liu, Chao Shen, Xi Peng, Yadong Zhou, Xiaohong Guan
    http://arxiv.org/abs/2003.06100v1

    • [cs.LG]Learning and Fairness in Energy Harvesting: A Maximin Multi-Armed Bandits Approach
    Debamita Ghosh, Arun Verma, Manjesh K. Hanawal
    http://arxiv.org/abs/2003.06213v1

    • [cs.LG]Minor Constraint Disturbances for Deep Semi-supervised Learning
    Jielei Chu, Jing Liu, Hongjun Wang, Zhiguo Gong, Tianrui Li
    http://arxiv.org/abs/2003.06321v1

    • [cs.LG]Model Agnostic Multilevel Explanations
    Karthikeyan Natesan Ramamurthy, Bhanukiran Vinzamuri, Yunfeng Zhang, Amit Dhurandhar
    http://arxiv.org/abs/2003.06005v1

    • [cs.LG]On the effectiveness of convolutional autoencoders on image-based personalized recommender systems
    E. Blanco-Mallo, B. Remeseiro, V. Bolón-Canedo, A. Alonso-Betanzos
    http://arxiv.org/abs/2003.06205v1

    • [cs.LG]Sample Efficient Reinforcement Learning through Learning from Demonstrations in Minecraft
    Christian Scheller, Yanick Schraner, Manfred Vogel
    http://arxiv.org/abs/2003.06066v1

    • [cs.LG]Sparse Graphical Memory for Robust Planning
    Michael Laskin, Scott Emmons, Ajay Jain, Thanard Kurutach, Pieter Abbeel, Deepak Pathak
    http://arxiv.org/abs/2003.06417v1

    • [cs.LG]Taylor Expansion Policy Optimization
    Yunhao Tang, Michal Valko, Rémi Munos
    http://arxiv.org/abs/2003.06259v1

    • [cs.LG]Ultra Efficient Transfer Learning with Meta Update for Cross Subject EEG Classification
    Tiehang Duan, Mihir Chauhan, Mohammad Abuzar Shaikh, Sargur Srihari
    http://arxiv.org/abs/2003.06113v1

    • [cs.LG]Wasserstein-based Graph Alignment
    Hermina Petric Maretic, Mireille El Gheche, Matthias Minder, Giovanni Chierchia, Pascal Frossard
    http://arxiv.org/abs/2003.06048v1

    • [cs.LG]What Information Does a ResNet Compress?
    Luke Nicholas Darlow, Amos Storkey
    http://arxiv.org/abs/2003.06254v1

    • [cs.LG]When are Non-Parametric Methods Robust?
    Robi Bhattacharjee, Kamalika Chaudhuri
    http://arxiv.org/abs/2003.06121v1

    • [cs.LG]Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling
    Tong Che, Ruixiang Zhang, Jascha Sohl-Dickstein, Hugo Larochelle, Liam Paull, Yuan Cao, Yoshua Bengio
    http://arxiv.org/abs/2003.06060v1

    • [cs.RO]Action for Better Prediction
    Bernadette Bucher, Karl Schmeckpeper, Nikolai Matni, Kostas Daniilidis
    http://arxiv.org/abs/2003.06082v1

    • [cs.RO]Computationally Efficient Obstacle Avoidance Trajectory Planner for UAVs Based on Heuristic Angular Search Method
    Han Chen, Peng Lu
    http://arxiv.org/abs/2003.06136v1

    • [cs.RO]Geometry-aware Dynamic Movement Primitives
    Fares J. Abu-Dakka, Ville Kyrki
    http://arxiv.org/abs/2003.06061v1

    • [cs.RO]Human Grasp Classification for Reactive Human-to-Robot Handovers
    Wei Yang, Chris Paxton, Maya Cakmak, Dieter Fox
    http://arxiv.org/abs/2003.06000v1

    • [cs.RO]LIBRE: The Multiple 3D LiDAR Dataset
    Alexander Carballo, Jacob Lambert, Abraham Monrroy, David Wong, Patiphon Narksri, Yuki Kitsukawa, Eijiro Takeuchi, Shinpei Kato, Kazuya Takeda
    http://arxiv.org/abs/2003.06129v1

    • [cs.RO]Learning to Generalize Across Long-Horizon Tasks from Human Demonstrations
    Ajay Mandlekar, Danfei Xu, Roberto Martín-Martín, Silvio Savarese, Li Fei-Fei
    http://arxiv.org/abs/2003.06085v1

    • [cs.RO]Long-term Prediction of Vehicle Behavior using Short-term Uncertainty-aware Trajectories and High-definition Maps
    Sai Yalamanchi, Tzu-Kuo Huang, Galen Clark Haynes, Nemanja Djuric
    http://arxiv.org/abs/2003.06143v1

    • [cs.RO]Towards a Framework for Visual Intelligence in Service Robotics: Epistemic Requirements and Gap Analysis
    Agnese Chiatti, Enrico Motta, Enrico Daga
    http://arxiv.org/abs/2003.06171v1

    • [cs.SI]NesTPP: Modeling Thread Dynamics in Online Discussion Forums
    Chen Ling, Guangmo Tong, Mozi Chen
    http://arxiv.org/abs/2003.06051v1

    • [cs.SI]Snapshot Samplings of the Bitcoin Transaction Network and Analysis of Cryptocurrency Growth
    Lambert T. Leong
    http://arxiv.org/abs/2003.06068v1

    • [econ.EM]Targeting Customers under Response-Dependent Costs
    Johannes Haupt, Stefan Lessmann
    http://arxiv.org/abs/2003.06271v1

    • [eess.IV]Advanced Deep Learning Methodologies for Skin Cancer Classification in Prodromal Stages
    Muhammad Ali Farooq, Asma Khatoon, Viktor Varkarakis, Peter Corcoran
    http://arxiv.org/abs/2003.06356v1

    • [eess.IV]Estimation of Rate Control Parameters for Video Coding Using CNN
    Maria Santamaria, Ebroul Izquierdo, Saverio Blasi, Marta Mrak
    http://arxiv.org/abs/2003.06315v1

    • [eess.IV]Random smooth gray value transformations for cross modality learning with gray value invariant networks
    Nikolas Lessmann, Bram van Ginneken
    http://arxiv.org/abs/2003.06158v1

    • [eess.SP]A Power-Efficient Binary-Weight Spiking Neural Network Architecture for Real-Time Object Classification
    Pai-Yu Tan, Po-Yao Chuang, Yen-Ting Lin, Cheng-Wen Wu, Juin-Ming Lu
    http://arxiv.org/abs/2003.06310v1

    • [eess.SP]RSSI-Based Hybrid Beamforming Design with Deep Learning
    Hamed Hojatian, Vu Nguyen Ha, Jérémy Nadal, Jean-François Frigon, François Leduc-Primeau
    http://arxiv.org/abs/2003.06042v1

    • [eess.SY]Data Set Description: Identifying the Physics Behind an Electric Motor — Data-Driven Learning of the Electrical Behavior (Part II)
    Sören Hanke, Oliver Wallscheid, Joachim Böcker
    http://arxiv.org/abs/2003.06268v1

    • [eess.SY]Identification of AC Networks via Online Learning
    Emanuele Fabbiani, Pulkit Nahata, Giuseppe De Nicolao, Giancarlo Ferrari-Trecate
    http://arxiv.org/abs/2003.06210v1

    • [eess.SY]Robust tracking of an unknown trajectory with a multi-rotor UAV: A high-gain observer approach
    C. J. Boss, V. Srivastava, H. K. Khalil
    http://arxiv.org/abs/2003.06390v1

    • [eess.SY]SIS Epidemic Model under Mobility on Multi-layer Networks
    Vishal Abhishek, Vaibhav Srivastava
    http://arxiv.org/abs/2003.06341v1

    • [hep-lat]Equivariant flow-based sampling for lattice gauge theory
    Gurtej Kanwar, Michael S. Albergo, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Sébastien Racanière, Danilo Jimenez Rezende, Phiala E. Shanahan
    http://arxiv.org/abs/2003.06413v1

    • [math.OC]Boosting Frank-Wolfe by Chasing Gradients
    Cyrille W. Combettes, Sebastian Pokutta
    http://arxiv.org/abs/2003.06369v1

    • [math.OC]Communication Efficient Sparsification for Large Scale Machine Learning
    Sarit Khirirat, Sindri Magnússon, Arda Aytekin, Mikael Johansson
    http://arxiv.org/abs/2003.06377v1

    • [math.ST]Existence and Uniqueness of the Kronecker Covariance MLE
    Mathias Drton, Satoshi Kuriki, Peter Hoff
    http://arxiv.org/abs/2003.06024v1

    • [math.ST]SVM Learning Rates for Data with Low Intrinsic Dimension
    Thomas Hamm, Ingo Steinwart
    http://arxiv.org/abs/2003.06202v1

    • [math.ST]Statistical Inference for High Dimensional Panel Functional Time Series
    Zhou Zhou, Holger Dette
    http://arxiv.org/abs/2003.05968v1

    • [physics.soc-ph]The impact of incorrect social information on collective wisdom in human groups
    Bertrand Jayles, Ramón Escobedo, Stéphane Cezera, Adrien Blanchet, Tatsuya Kameda, Clément Sire, Guy Theraulaz
    http://arxiv.org/abs/2003.06160v1

    • [q-fin.PM]Application of Deep Q-Network in Portfolio Management
    Ziming Gao, Yuan Gao, Yi Hu, Zhengyong Jiang, Jionglong Su
    http://arxiv.org/abs/2003.06365v1

    • [stat.AP]A Note on Early Epidemiological Analysis of Coronavirus Disease 2019 Outbreak using Crowdsourced Data
    Giuseppe Arbia
    http://arxiv.org/abs/2003.06207v1

    • [stat.AP]Bayesian Posterior Interval Calibration to Improve the Interpretability of Observational Studies
    Jami J. Mulgrave, David Madigan, George Hripcsak
    http://arxiv.org/abs/2003.06002v1

    • [stat.AP]Power and Sample Size for Marginal Structural Models
    Bonnie E. Shook-Sa, Michael G. Hudgens
    http://arxiv.org/abs/2003.05979v1

    • [stat.AP]Spatial multiresolution analysis approach to identify crash hotspots and estimate crash risk
    Samer Katicha, John Khoury, Gerardo Flintsch
    http://arxiv.org/abs/2003.06378v1

    • [stat.CO]Extending the MaCSim approach using similarity weight matrix to assess the accuracy of record linkage
    Shovanur Haque, Kerrie Mengersen
    http://arxiv.org/abs/2003.06291v1

    • [stat.ME]A comparison of parameter estimation in function-on-function regression
    Ufuk Beyaztas, Han Lin Shang
    http://arxiv.org/abs/2003.06067v1

    • [stat.ME]A spatial causal analysis of wildland fire-contributed PM2.5 using numerical model output
    Alexandra Larsen, Shu Yang, Brian J. Reich, Ana G. Rappold
    http://arxiv.org/abs/2003.06037v1

    • [stat.ME]Default Bayes Factors for Testing the (In)equality of Several Population Variances
    Fabian Dablander, Don van den Bergh, Alexander Ly, Eric-Jan Wagenmakers
    http://arxiv.org/abs/2003.06278v1

    • [stat.ME]Estimating Basis Functions in Massive Fields under the Spatial Mixed Effects Model
    Karl T. Pazdernik, Ranjan Maitra
    http://arxiv.org/abs/2003.05990v1

    • [stat.ME]Spatial Tweedie exponential dispersion models
    Aritra Halder, Shariq Mohammed, Kun Chen, Dipak K. Dey
    http://arxiv.org/abs/2003.06299v1

    • [stat.ME]Use of Cross-validation Bayes Factors to Test Equality of Two Densities
    Jeffery Hart, Taeryon Choi, Naveed Merchant
    http://arxiv.org/abs/2003.06368v1

    • [stat.ME]VC-BART: Bayesian trees for varying coefficients
    Sameer K. Deshpande, Ray Bai, Cecilia Balocchi, Jennifer E. Starling
    http://arxiv.org/abs/2003.06416v1

    • [stat.ML]An Evaluation of Change Point Detection Algorithms
    Gerrit J. J. van den Burg, Christopher K. I. Williams
    http://arxiv.org/abs/2003.06222v1

    • [stat.ML]B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data
    Liu Yang, Xuhui Meng, George Em Karniadakis
    http://arxiv.org/abs/2003.06097v1

    • [stat.ML]BayesFlow: Learning complex stochastic models with invertible neural networks
    Stefan T. Radev, Ulf K. Mertens, Andreass Voss, Lynton Ardizzone, Ullrich Köthe

    http://arxiv.org/abs/2003.06281v1