cond-mat.stat-mech - 统计数学

    cs.AI - 人工智能 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DS - 数据结构与算法 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 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.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 physics.soc-ph - 物理学与社会 quant-ph - 量子物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cond-mat.stat-mech]Oracular information and the second law of thermodynamics
    • [cs.AI]Alternative Function Approximation Parameterizations for Solving Games: An Analysis of $f$-Regression Counterfactual Regret Minimization
    • [cs.AI]Making Smart Homes Smarter: Optimizing Energy Consumption with Human in the Loop
    • [cs.AI]Reinforcement Learning Upside Down: Don’t Predict Rewards — Just Map Them to Actions
    • [cs.AI]Tools for Mathematical Ludology
    • [cs.CL]A limited-size ensemble of homogeneous CNN/LSTMs for high-performance word classification
    • [cs.CL]Classifying Diagrams and Their Parts using Graph Neural Networks: A Comparison of Crowd-Sourced and Expert Annotations
    • [cs.CL]GoodNewsEveryone: A Corpus of News Headlines Annotated with Emotions, Semantic Roles, and Reader Perception
    • [cs.CL]Integrating Deep Learning with Logic Fusion for Information Extraction
    • [cs.CL]Machine Translation Evaluation Meets Community Question Answering
    • [cs.CL]Pairwise Neural Machine Translation Evaluation
    • [cs.CL]SemEval-2014 Task 9: Sentiment Analysis in Twitter
    • [cs.CL]Semantic Mask for Transformer based End-to-End Speech Recognition
    • [cs.CR]Designing for Privacy and Confidentiality on Distributed Ledgers for Enterprise (Industry Track)
    • [cs.CV]300 GHz Radar Object Recognition based on Deep Neural Networks and Transfer Learning
    • [cs.CV]3D CNN with Localized Residual Connections for Hyperspectral Image Classification
    • [cs.CV]A Benchmark for Lidar Sensors in Fog: Is Detection Breaking Down?
    • [cs.CV]Connecting Vision and Language with Localized Narratives
    • [cs.CV]Controlling Style and Semantics in Weakly-Supervised Image Generation
    • [cs.CV]DeepEthnic: Multi-Label Ethnic Classification from Face Images
    • [cs.CV]Dynamic Convolutions: Exploiting Spatial Sparsity for Faster Inference
    • [cs.CV]End-to-end Training of CNN-CRF via Differentiable Dual-Decomposition
    • [cs.CV]Exploring Unlabeled Faces for Novel Attribute Discovery
    • [cs.CV]Face Recognition via Locality Constrained Low Rank Representation and Dictionary Learning
    • [cs.CV]Grid-GCN for Fast and Scalable Point Cloud Learning
    • [cs.CV]LaTeS: Latent Space Distillation for Teacher-Student Driving Policy Learning
    • [cs.CV]NASA: Neural Articulated Shape Approximation
    • [cs.CV]Perspective-consistent multifocus multiview 3D reconstruction of small objects
    • [cs.CV]Pyramid Multi-view Stereo Net with Self-adaptive View Aggregation
    • [cs.CV]Video to Events: Bringing Modern Computer Vision Closer to Event Cameras
    • [cs.CV]Visual-Textual Association with Hardest and Semi-Hard Negative Pairs Mining for Person Search
    • [cs.CV]Waterfall Atrous Spatial Pooling Architecture for Efficient Semantic Segmentation
    • [cs.CV]Weak Supervision helps Emergence of Word-Object Alignment and improves Vision-Language Tasks
    • [cs.CY]An Algorithmic Equity Toolkit for Technology Audits by Community Advocates and Activists
    • [cs.CY]EdNet: A Large-Scale Hierarchical Dataset in Education
    • [cs.DB]Towards Interpretable and Learnable Risk Analysis for Entity Resolution
    • [cs.DC]Communication-Efficient Network-Distributed Optimization with Differential-Coded Compressors
    • [cs.DC]FBase: A Replication Service for Data-Intensive Fog Applications
    • [cs.DC]Merlin: Enabling Machine Learning-Ready HPC Ensembles
    • [cs.DS]Lower Bounds for Compressed Sensing with Generative Models
    • [cs.IR]Document Network Embedding: Coping for Missing Content and Missing Links
    • [cs.IR]Information Privacy Opinions on Twitter: A Cross-Language Study
    • [cs.IR]Recommending investors for new startups by integrating network diffusion and investors’ domain preference
    • [cs.IR]WIKIR: A Python toolkit for building a large-scale Wikipedia-based English Information Retrieval Dataset
    • [cs.IT]Information theory for non-stationary processes with stationary increments
    • [cs.LG]A Neural Spiking Approach Compared to Deep Feedforward Networks on Stepwise Pixel Erasement
    • [cs.LG]A pedestrian path-planning model in accordance with obstacle’s danger with reinforcement learning
    • [cs.LG]A priori generalization error for two-layer ReLU neural network through minimum norm solution
    • [cs.LG]Achieving Robustness in the Wild via Adversarial Mixing with Disentangled Representations
    • [cs.LG]Differentially Private Mixed-Type Data Generation For Unsupervised Learning
    • [cs.LG]Does Knowledge Transfer Always Help to Learn a Better Policy?
    • [cs.LG]Hyperbolic Graph Attention Network
    • [cs.LG]Improved Analysis of Spectral Algorithm for Clustering
    • [cs.LG]Improved PAC-Bayesian Bounds for Linear Regression
    • [cs.LG]Influenza Modeling Based on Massive Feature Engineering and International Flow Deconvolution
    • [cs.LG]Knowledge extraction from the learning of sequences in a long short term memory (LSTM) architecture
    • [cs.LG]Learning to Correspond Dynamical Systems
    • [cs.LG]Observational Overfitting in Reinforcement Learning
    • [cs.LG]Performing Arithmetic Using a Neural Network Trained on Digit Permutation Pairs
    • [cs.LG]Physics-Informed Neural Networks for Multiphysics Data Assimilation with Application to Subsurface Transport
    • [cs.LG]Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers
    • [cs.LG]Regularization Shortcomings for Continual Learning
    • [cs.LG]Risk-Averse Trust Region Optimization for Reward-Volatility Reduction
    • [cs.LG]Sampling-Free Learning of Bayesian Quantized Neural Networks
    • [cs.LG]Training Agents using Upside-Down Reinforcement Learning
    • [cs.LG]Tree bark re-identification using a deep-learning feature descriptor
    • [cs.LG]VALAN: Vision and Language Agent Navigation
    • [cs.LG]What Do You Mean I’m Funny? Personalizing the Joke Skill of a Voice-Controlled Virtual Assistant
    • [cs.LG]Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One
    • [cs.NE]Modeling the Chlorophyll-a from Sea Surface Reflectance in West Africa by Deep Learning Methods: A Comparison of Multiple Algorithms
    • [cs.RO]Self-Supervised Visual Terrain Classification from Unsupervised Acoustic Feature Learning
    • [cs.RO]Smart Cloud: Scalable Cloud Robotic Architecture for Web-powered Multi-Robot Applications
    • [cs.SI]Self-falsifiable Hierarchical Detection of Overlapping Communities On Social Networks
    • [econ.EM]High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing
    • [econ.EM]Triple the gamma — A unifying shrinkage prior for variance and variable selection in sparse state space and TVP models
    • [eess.AS]Synchronous Transformers for End-to-End Speech Recognition
    • [eess.IV]Benchmarking Image Sensors Under Adverse Weather Conditions for Autonomous Driving
    • [eess.IV]Generating Patient-like Phantoms Using Fully Unsupervised Deformable Image Registration with Convolutional Neural Networks
    • [eess.IV]NASNet: A Neuron Attention Stage-by-Stage Net for Single Image Deraining
    • [eess.IV]Recent advances in deep learning applied to skin cancer detection
    • eess.SP-RIP and Projected Back-Projection Reconstruction for Phase-Only Measurements
    • [eess.SP]Data Augmentation for Deep Learning-based Radio Modulation Classification
    • [eess.SY]A Method towards the Systematic Architecting of Functionally Safe Automated Driving — Leveraging Diagnostic Specifications for FSC design
    • [math.OC]Optimization algorithms inspired by the geometry of dissipative systems
    • [math.OC]Risk-Aware MMSE Estimation
    • [math.OC]Scalable Reinforcement Learning of Localized Policies for Multi-Agent Networked Systems
    • [math.OC]Why ADAM Beats SGD for Attention Models
    • [math.PR]Hypothesis testing for a Lévy-driven storage system by Poisson sampling
    • [math.ST]A note on identifiability conditions in confirmatory factor analysis
    • [math.ST]Bayesian stochastic multi-scale analysis via energy considerations
    • [math.ST]On using empirical null distribution in Benjamini-Hochberg procedure
    • [math.ST]The coupling method in extreme value theory
    • [math.ST]The limits of the sample spiked eigenvalues for a high-dimensional generalized Fisher matrix and its applications
    • [physics.soc-ph]Transitivity and degree assortativity explained: The bipartite structure of social networks
    • [physics.soc-ph]Upscaling human activity data: an ecological perspective
    • [quant-ph]A quantum active learning algorithm for sampling against adversarial attacks
    • [stat.AP]Data-Driven Uncertainty Quantification and Propagation in Structural Dynamics through a Hierarchical Bayesian Framework
    • [stat.AP]Identification of mineralization in geochemistry along a transect based on the spatial curvature of log-ratios
    • [stat.AP]On Racial Disparities in Recent Fatal Police Shootings
    • [stat.CO]Manifold Markov chain Monte Carlo methods for Bayesian inference in a wide class of diffusion models
    • [stat.ME]A Convex Optimization Approach to High-Dimensional Sparse Quadratic Discriminant Analysis
    • [stat.ME]Hybrid Kronecker Product Decomposition and Approximation
    • [stat.ME]Synthetic Controls and Weighted Event Studies with Staggered Adoption
    • [stat.ML]Gaussian Process Priors for View-Aware Inference
    • [stat.ML]Non-asymptotic error bounds for scaled underdamped Langevin MCMC
    • [stat.ML]Solving Bernoulli Rank-One Bandits with Unimodal Thompson Sampling

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

    • [cond-mat.stat-mech]Oracular information and the second law of thermodynamics
    Andrew J. P. Garner
    http://arxiv.org/abs/1912.03217v1

    • [cs.AI]Alternative Function Approximation Parameterizations for Solving Games: An Analysis of $f$-Regression Counterfactual Regret Minimization
    Ryan D’Orazio, Dustin Morrill, James R. Wright, Michael Bowling
    http://arxiv.org/abs/1912.02967v1

    • [cs.AI]Making Smart Homes Smarter: Optimizing Energy Consumption with Human in the Loop
    Mudit Verma, Siddhant Bhambri, Arun Balaji Buduru
    http://arxiv.org/abs/1912.03298v1

    • [cs.AI]Reinforcement Learning Upside Down: Don’t Predict Rewards — Just Map Them to Actions
    Juergen Schmidhuber
    http://arxiv.org/abs/1912.02875v1

    • [cs.AI]Tools for Mathematical Ludology
    Paul Riggins, David McPherson
    http://arxiv.org/abs/1912.03295v1

    • [cs.CL]A limited-size ensemble of homogeneous CNN/LSTMs for high-performance word classification
    Mahya Ameryan, Lambert Schomaker
    http://arxiv.org/abs/1912.03223v1

    • [cs.CL]Classifying Diagrams and Their Parts using Graph Neural Networks: A Comparison of Crowd-Sourced and Expert Annotations
    Tuomo Hiippala
    http://arxiv.org/abs/1912.02866v1

    • [cs.CL]GoodNewsEveryone: A Corpus of News Headlines Annotated with Emotions, Semantic Roles, and Reader Perception
    Laura Bostan, Evgeny Kim, Roman Klinger
    http://arxiv.org/abs/1912.03184v1

    • [cs.CL]Integrating Deep Learning with Logic Fusion for Information Extraction
    Wenya Wang, Sinno Jialin Pan
    http://arxiv.org/abs/1912.03041v1

    • [cs.CL]Machine Translation Evaluation Meets Community Question Answering
    Francisco Guzmán, Lluís Màrquez, Preslav Nakov
    http://arxiv.org/abs/1912.02998v1

    • [cs.CL]Pairwise Neural Machine Translation Evaluation
    Francisco Guzman, Shafiq Joty, Lluis Marquez, Preslav Nakov
    http://arxiv.org/abs/1912.03135v1

    • [cs.CL]SemEval-2014 Task 9: Sentiment Analysis in Twitter
    Sara Rosenthal, Preslav Nakov, Alan Ritter, Veselin Stoyanov
    http://arxiv.org/abs/1912.02990v1

    • [cs.CL]Semantic Mask for Transformer based End-to-End Speech Recognition
    Chengyi Wang, Yu Wu, Yujiao Du, Jinyu Li, Shujie Liu, Liang Lu, Shuo Ren, Guoli Ye, Sheng Zhao, Ming Zhou
    http://arxiv.org/abs/1912.03010v1

    • [cs.CR]Designing for Privacy and Confidentiality on Distributed Ledgers for Enterprise (Industry Track)
    Allison Irvin, Isabell Kiral
    http://arxiv.org/abs/1912.02924v1

    • [cs.CV]300 GHz Radar Object Recognition based on Deep Neural Networks and Transfer Learning
    Marcel Sheeny, Andrew Wallace, Sen Wang
    http://arxiv.org/abs/1912.03157v1

    • [cs.CV]3D CNN with Localized Residual Connections for Hyperspectral Image Classification
    Shivangi Dwivedi, Murari Mandal, Shekhar Yadav, Santosh Kumar Vipparthi
    http://arxiv.org/abs/1912.03000v1

    • [cs.CV]A Benchmark for Lidar Sensors in Fog: Is Detection Breaking Down?
    Mario Bijelic, Tobias Gruber, Werner Ritter
    http://arxiv.org/abs/1912.03251v1

    • [cs.CV]Connecting Vision and Language with Localized Narratives
    Jordi Pont-Tuset, Jasper Uijlings, Soravit Changpinyo, Radu Soricut, Vittorio Ferrari
    http://arxiv.org/abs/1912.03098v1

    • [cs.CV]Controlling Style and Semantics in Weakly-Supervised Image Generation
    Dario Pavllo, Aurelien Lucchi, Thomas Hofmann
    http://arxiv.org/abs/1912.03161v1

    • [cs.CV]DeepEthnic: Multi-Label Ethnic Classification from Face Images
    Katia Huri, Eli David, Nathan S. Netanyahu
    http://arxiv.org/abs/1912.02983v1

    • [cs.CV]Dynamic Convolutions: Exploiting Spatial Sparsity for Faster Inference
    Thomas Verelst, Tinne Tuytelaars
    http://arxiv.org/abs/1912.03203v1

    • [cs.CV]End-to-end Training of CNN-CRF via Differentiable Dual-Decomposition
    Shaofei Wang, Vishnu Lokhande, Maneesh Singh, Konrad Kording, Julian Yarkony
    http://arxiv.org/abs/1912.02937v1

    • [cs.CV]Exploring Unlabeled Faces for Novel Attribute Discovery
    Hyojin Bahng, Sunghyo Chung, Seungjoo Yoo, Jaegul Choo
    http://arxiv.org/abs/1912.03085v1

    • [cs.CV]Face Recognition via Locality Constrained Low Rank Representation and Dictionary Learning
    He-Feng Yin, Xiao-Jun Wu, Josef Kittler
    http://arxiv.org/abs/1912.03145v1

    • [cs.CV]Grid-GCN for Fast and Scalable Point Cloud Learning
    Qiangeng Xu
    http://arxiv.org/abs/1912.02984v1

    • [cs.CV]LaTeS: Latent Space Distillation for Teacher-Student Driving Policy Learning
    Albert Zhao, Tong He, Yitao Liang, Haibin Huang, Guy Van den Broeck, Stefano Soatto
    http://arxiv.org/abs/1912.02973v1

    • [cs.CV]NASA: Neural Articulated Shape Approximation
    Timothy Jeruzalski, Boyang Deng, Mohammad Norouzi, JP Lewis, Geoffrey Hinton, Andrea Tagliasacchi
    http://arxiv.org/abs/1912.03207v1

    • [cs.CV]Perspective-consistent multifocus multiview 3D reconstruction of small objects
    Hengjia Li, Chuong Nguyen
    http://arxiv.org/abs/1912.03005v1

    • [cs.CV]Pyramid Multi-view Stereo Net with Self-adaptive View Aggregation
    Hongwei Yi, Zizhuang Wei, Mingyu Ding, Runze Zhang, Yisong Chen, Guoping Wang, Yu-Wing Tai
    http://arxiv.org/abs/1912.03001v1

    • [cs.CV]Video to Events: Bringing Modern Computer Vision Closer to Event Cameras
    Daniel Gehrig, Mathias Gehrig, Javier Hidalgo-Carrió, Davide Scaramuzza
    http://arxiv.org/abs/1912.03095v1

    • [cs.CV]Visual-Textual Association with Hardest and Semi-Hard Negative Pairs Mining for Person Search
    Jing Ge, Guangyu Gao, Zhen Liu
    http://arxiv.org/abs/1912.03083v1

    • [cs.CV]Waterfall Atrous Spatial Pooling Architecture for Efficient Semantic Segmentation
    Bruno Artacho, Andreas Savakis
    http://arxiv.org/abs/1912.03183v1

    • [cs.CV]Weak Supervision helps Emergence of Word-Object Alignment and improves Vision-Language Tasks
    Corentin Kervadec, Grigory Antipov, Moez Baccouche, Christian Wolf
    http://arxiv.org/abs/1912.03063v1

    • [cs.CY]An Algorithmic Equity Toolkit for Technology Audits by Community Advocates and Activists
    Michael Katell, Meg Young, Bernease Herman, Dharma Dailey, Aaron Tam, Vivian Guetler, Corinne Binz, Daniella Raz, P. M. Krafft
    http://arxiv.org/abs/1912.02943v1

    • [cs.CY]EdNet: A Large-Scale Hierarchical Dataset in Education
    Youngduck Choi, Youngnam Lee, Dongmin Shin, Junghyun Cho, Seoyon Park, Seewoo Lee, Jineon Baek, Byungsoo Kim, Youngjun Jang
    http://arxiv.org/abs/1912.03072v1

    • [cs.DB]Towards Interpretable and Learnable Risk Analysis for Entity Resolution
    Zhaoqiang Chen, Qun Chen, Boyi Hou, Tianyi Duan, Zhanhuai Li, Guoliang Li
    http://arxiv.org/abs/1912.02947v1

    • [cs.DC]Communication-Efficient Network-Distributed Optimization with Differential-Coded Compressors
    Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth S. Bentley
    http://arxiv.org/abs/1912.03208v1

    • [cs.DC]FBase: A Replication Service for Data-Intensive Fog Applications
    Jonathan Hasenburg, Martin Grambow, David Bermbach
    http://arxiv.org/abs/1912.03107v1

    • [cs.DC]Merlin: Enabling Machine Learning-Ready HPC Ensembles
    J. Luc Peterson, Rushil Anirudh, Kevin Athey, Benjamin Bay, Peer-Timo Bremer, Vic Castillo, Francesco Di Natale, David Fox, Jim A. Gaffney, David Hysom, Sam Ade Jacobs, Bhavya Kailkhura, Joe Koning, Bogdan Kustowski, Steven Langer, Peter Robinson, Jessica Semler, Brian Spears, Jayaraman Thiagarajan, Brian Van Essen, Jae-Seung Yeom
    http://arxiv.org/abs/1912.02892v1

    • [cs.DS]Lower Bounds for Compressed Sensing with Generative Models
    Akshay Kamath, Sushrut Karmalkar, Eric Price
    http://arxiv.org/abs/1912.02938v1

    • [cs.IR]Document Network Embedding: Coping for Missing Content and Missing Links
    Jean Dupuy, Adrien Guille, Julien Jacques
    http://arxiv.org/abs/1912.03048v1

    • [cs.IR]Information Privacy Opinions on Twitter: A Cross-Language Study
    Felipe González, Andrea Figueroa, Claudia López, Cecilia Aragón
    http://arxiv.org/abs/1912.02852v1

    • [cs.IR]Recommending investors for new startups by integrating network diffusion and investors’ domain preference
    Shuqi Xu, Qianming Zhang, Linyuan Lv, Manuel Sebastian Mariani
    http://arxiv.org/abs/1912.02962v1

    • [cs.IR]WIKIR: A Python toolkit for building a large-scale Wikipedia-based English Information Retrieval Dataset
    Jibril Frej, Didier Schwab, Jean-Pierre Chevallet
    http://arxiv.org/abs/1912.01901v3

    • [cs.IT]Information theory for non-stationary processes with stationary increments
    Carlos Granero-Belinchon, Stéphane G. Roux, Nicolas Garnier
    http://arxiv.org/abs/1912.03172v1

    • [cs.LG]A Neural Spiking Approach Compared to Deep Feedforward Networks on Stepwise Pixel Erasement
    René Larisch, Michael Teichmann, Fred H. Hamker
    http://arxiv.org/abs/1912.03201v1

    • [cs.LG]A pedestrian path-planning model in accordance with obstacle’s danger with reinforcement learning
    Thanh-Trung Trinh, Dinh-Minh Vu, Masaomi Kimura
    http://arxiv.org/abs/1912.02945v1

    • [cs.LG]A priori generalization error for two-layer ReLU neural network through minimum norm solution
    Zhi-Qin John Xu, Jiwei Zhang, Yaoyu Zhang, Chengchao Zhao
    http://arxiv.org/abs/1912.03011v1

    • [cs.LG]Achieving Robustness in the Wild via Adversarial Mixing with Disentangled Representations
    Sven Gowal, Chongli Qin, Po-Sen Huang, Taylan Cemgil, Krishnamurthy Dvijotham, Timothy Mann, Pushmeet Kohli
    http://arxiv.org/abs/1912.03192v1

    • [cs.LG]Differentially Private Mixed-Type Data Generation For Unsupervised Learning
    Uthaipon Tantipongpipat, Chris Waites, Digvijay Boob, Amaresh Ankit Siva, Rachel Cummings
    http://arxiv.org/abs/1912.03250v1

    • [cs.LG]Does Knowledge Transfer Always Help to Learn a Better Policy?
    Fei Feng, Wotao Yin, Lin F. Yang
    http://arxiv.org/abs/1912.02986v1

    • [cs.LG]Hyperbolic Graph Attention Network
    Yiding Zhang, Xiao Wang, Xunqiang Jiang, Chuan Shi, Yanfang Ye
    http://arxiv.org/abs/1912.03046v1

    • [cs.LG]Improved Analysis of Spectral Algorithm for Clustering
    Tomohiko Mizutani
    http://arxiv.org/abs/1912.02997v1

    • [cs.LG]Improved PAC-Bayesian Bounds for Linear Regression
    Vera Shalaeva, Alireza Fakhrizadeh Esfahani, Pascal Germain, Mihaly Petreczky
    http://arxiv.org/abs/1912.03036v1

    • [cs.LG]Influenza Modeling Based on Massive Feature Engineering and International Flow Deconvolution
    Ziming Liu, Yixuan Wang, Zizhao Han, Dian Wu
    http://arxiv.org/abs/1912.02989v1

    • [cs.LG]Knowledge extraction from the learning of sequences in a long short term memory (LSTM) architecture
    Ikram Chraibi Kaadoud, Nicolas P. Rougier, Frédéric Alexandre
    http://arxiv.org/abs/1912.03126v1

    • [cs.LG]Learning to Correspond Dynamical Systems
    Nam Hee Kim, Zhaoming Xie, Michiel van de Panne
    http://arxiv.org/abs/1912.03015v1

    • [cs.LG]Observational Overfitting in Reinforcement Learning
    Xingyou Song, Yiding Jiang, Yilun Du, Behnam Neyshabur
    http://arxiv.org/abs/1912.02975v1

    • [cs.LG]Performing Arithmetic Using a Neural Network Trained on Digit Permutation Pairs
    Marcus D. Bloice, Peter M. Roth, Andreas Holzinger
    http://arxiv.org/abs/1912.03035v1

    • [cs.LG]Physics-Informed Neural Networks for Multiphysics Data Assimilation with Application to Subsurface Transport
    QiZhi He, David Brajas-Solano, Guzel Tartakovsky, Alexandre M. Tartakovsky
    http://arxiv.org/abs/1912.02968v1

    • [cs.LG]Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers
    Divyat Mahajan, Chenhao Tan, Amit Sharma
    http://arxiv.org/abs/1912.03277v1

    • [cs.LG]Regularization Shortcomings for Continual Learning
    Timothée Lesort, Andrei Stoian, David Filliat
    http://arxiv.org/abs/1912.03049v1

    • [cs.LG]Risk-Averse Trust Region Optimization for Reward-Volatility Reduction
    Lorenzo Bisi, Luca Sabbioni, Edoardo Vittori, Matteo Papini, Marcello Restelli
    http://arxiv.org/abs/1912.03193v1

    • [cs.LG]Sampling-Free Learning of Bayesian Quantized Neural Networks
    Jiahao Su, Milan Cvitkovic, Furong Huang
    http://arxiv.org/abs/1912.02992v1

    • [cs.LG]Training Agents using Upside-Down Reinforcement Learning
    Rupesh Kumar Srivastava, Pranav Shyam, Filipe Mutz, Wojciech Jaśkowski, Jürgen Schmidhuber
    http://arxiv.org/abs/1912.02877v1

    • [cs.LG]Tree bark re-identification using a deep-learning feature descriptor
    Martin Robert, Patrick Dallaire, Philippe Giguère
    http://arxiv.org/abs/1912.03221v1

    • [cs.LG]VALAN: Vision and Language Agent Navigation
    Larry Lansing, Vihan Jain, Harsh Mehta, Haoshuo Huang, Eugene Ie
    http://arxiv.org/abs/1912.03241v1

    • [cs.LG]What Do You Mean I’m Funny? Personalizing the Joke Skill of a Voice-Controlled Virtual Assistant
    Alejandro Mottini, Amber Roy Chowdhury
    http://arxiv.org/abs/1912.03234v1

    • [cs.LG]Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One
    Will Grathwohl, Kuan-Chieh Wang, Jörn-Henrik Jacobsen, David Duvenaud, Mohammad Norouzi, Kevin Swersky
    http://arxiv.org/abs/1912.03263v1

    • [cs.NE]Modeling the Chlorophyll-a from Sea Surface Reflectance in West Africa by Deep Learning Methods: A Comparison of Multiple Algorithms
    Daouda Diouf, Djibril Seck
    http://arxiv.org/abs/1912.03216v1

    • [cs.RO]Self-Supervised Visual Terrain Classification from Unsupervised Acoustic Feature Learning
    Jannik Zürn, Wolfram Burgard, Abhinav Valada
    http://arxiv.org/abs/1912.03227v1

    • [cs.RO]Smart Cloud: Scalable Cloud Robotic Architecture for Web-powered Multi-Robot Applications
    Manoj Penmetcha, Shyam Sundar Kannan, Byung-Cheol Min
    http://arxiv.org/abs/1912.02927v1

    • [cs.SI]Self-falsifiable Hierarchical Detection of Overlapping Communities On Social Networks
    Tianyi Li, Pan Zhang
    http://arxiv.org/abs/1912.02903v1

    • [econ.EM]High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing
    Alexandre Belloni, Mingli Chen, Oscar Hernan Madrid Padilla, Zixuan, Wang
    http://arxiv.org/abs/1912.02151v1

    • [econ.EM]Triple the gamma — A unifying shrinkage prior for variance and variable selection in sparse state space and TVP models
    Annalisa Cadonna, Sylvia Frühwirth-Schnatter, Peter Knaus
    http://arxiv.org/abs/1912.03100v1

    • [eess.AS]Synchronous Transformers for End-to-End Speech Recognition
    Zhengkun Tian, Jiangyan Yi, Ye Bai, Jianhua Tao, Shuai Zhang, Zhengqi Wen
    http://arxiv.org/abs/1912.02958v1

    • [eess.IV]Benchmarking Image Sensors Under Adverse Weather Conditions for Autonomous Driving
    Mario Bijelic, Tobias Gruber, Werner Ritter
    http://arxiv.org/abs/1912.03238v1

    • [eess.IV]Generating Patient-like Phantoms Using Fully Unsupervised Deformable Image Registration with Convolutional Neural Networks
    Junyu Chen, Ye Li, Eric C. Frey
    http://arxiv.org/abs/1912.02942v1

    • [eess.IV]NASNet: A Neuron Attention Stage-by-Stage Net for Single Image Deraining
    Xu Qin, Zhilin Wang
    http://arxiv.org/abs/1912.03151v1

    • [eess.IV]Recent advances in deep learning applied to skin cancer detection
    Andre G. C. Pacheco, Renato A. Krohling
    http://arxiv.org/abs/1912.03280v1

    • [eess.SP](l1,l2)-RIP and Projected Back-Projection Reconstruction for Phase-Only Measurements
    Thomas Feuillen, Mike E. Davies, Luc Vandendorpe, Laurent Jacques
    http://arxiv.org/abs/1912.02880v1

    • [eess.SP]Data Augmentation for Deep Learning-based Radio Modulation Classification
    Liang Huang, Weijian Pan, You Zhang, LiPing Qian, Nan Gao, Yuan Wu
    http://arxiv.org/abs/1912.03026v1

    • [eess.SY]A Method towards the Systematic Architecting of Functionally Safe Automated Driving — Leveraging Diagnostic Specifications for FSC design
    Naveen Mohan, Martin Törngren, Sagar Behere
    http://arxiv.org/abs/1912.03178v1

    • [math.OC]Optimization algorithms inspired by the geometry of dissipative systems
    Alessandro Bravetti, Maria L. Daza-Torres, Hugo Flores-Arguedas, Michael Betancourt
    http://arxiv.org/abs/1912.02928v1

    • [math.OC]Risk-Aware MMSE Estimation
    Dionysios S. Kalogerias, Luiz F. O. Chamon, George J. Pappas, Alejandro Ribeiro
    http://arxiv.org/abs/1912.02933v1

    • [math.OC]Scalable Reinforcement Learning of Localized Policies for Multi-Agent Networked Systems
    Guannan Qu, Adam Wierman, Na Li
    http://arxiv.org/abs/1912.02906v1

    • [math.OC]Why ADAM Beats SGD for Attention Models
    Jingzhao Zhang, Sai Praneeth Karimireddy, Andreas Veit, Seungyeon Kim, Sashank J Reddi, Sanjiv Kumar, Suvrit Sra
    http://arxiv.org/abs/1912.03194v1

    • [math.PR]Hypothesis testing for a Lévy-driven storage system by Poisson sampling
    Michel Mandjes, Liron Ravner
    http://arxiv.org/abs/1912.02891v1

    • [math.ST]A note on identifiability conditions in confirmatory factor analysis
    William Leeb
    http://arxiv.org/abs/1912.02879v1

    • [math.ST]Bayesian stochastic multi-scale analysis via energy considerations
    M. S. Sarfaraz, B. Rosic, H. G. Matthies, A. Ibrahimbegovic
    http://arxiv.org/abs/1912.03108v1

    • [math.ST]On using empirical null distribution in Benjamini-Hochberg procedure
    Etienne Roquain, Nicolas Verzelen
    http://arxiv.org/abs/1912.03109v1

    • [math.ST]The coupling method in extreme value theory
    Benjamin Bobbia, Clément Dombry, Davit Varron
    http://arxiv.org/abs/1912.03155v1

    • [math.ST]The limits of the sample spiked eigenvalues for a high-dimensional generalized Fisher matrix and its applications
    Dandan Jiang, Jiang Hu, Zhiqiang Hou
    http://arxiv.org/abs/1912.02819v1

    • [physics.soc-ph]Transitivity and degree assortativity explained: The bipartite structure of social networks
    Demival Vasques Filho, Dion R. J. O’Neale
    http://arxiv.org/abs/1912.03211v1

    • [physics.soc-ph]Upscaling human activity data: an ecological perspective
    Anna Tovo, Samuele Stivanello, Amos Maritan, Samir Suweis, Stefano Favaro, Marco Formentin
    http://arxiv.org/abs/1912.03023v1

    • [quant-ph]A quantum active learning algorithm for sampling against adversarial attacks
    P. A. M. Casares, M. A. Martin-Delgado
    http://arxiv.org/abs/1912.03283v1

    • [stat.AP]Data-Driven Uncertainty Quantification and Propagation in Structural Dynamics through a Hierarchical Bayesian Framework
    Omid Sedehi, Costas Papadimitriou, Lambros S. Katafygiotis
    http://arxiv.org/abs/1912.02966v1

    • [stat.AP]Identification of mineralization in geochemistry along a transect based on the spatial curvature of log-ratios
    Dominika Mikšová, Christopher Rieser, Peter Filzmoser
    http://arxiv.org/abs/1912.02867v1

    • [stat.AP]On Racial Disparities in Recent Fatal Police Shootings
    Lucas Mentch
    http://arxiv.org/abs/1912.03018v1

    • [stat.CO]Manifold Markov chain Monte Carlo methods for Bayesian inference in a wide class of diffusion models
    Matthew M. Graham, Alexandre H. Thiery, Alexandros Beskos
    http://arxiv.org/abs/1912.02982v1

    • [stat.ME]A Convex Optimization Approach to High-Dimensional Sparse Quadratic Discriminant Analysis
    T. Tony Cai, Linjun Zhang
    http://arxiv.org/abs/1912.02872v1

    • [stat.ME]Hybrid Kronecker Product Decomposition and Approximation
    Chencheng Cai, Rong Chen, Han Xiao
    http://arxiv.org/abs/1912.02955v1

    • [stat.ME]Synthetic Controls and Weighted Event Studies with Staggered Adoption
    Eli Ben-Michael, Avi Feller, Jesse Rothstein
    http://arxiv.org/abs/1912.03290v1

    • [stat.ML]Gaussian Process Priors for View-Aware Inference
    Yuxin Hou, Ari Heljakka, Arno Solin
    http://arxiv.org/abs/1912.03249v1

    • [stat.ML]Non-asymptotic error bounds for scaled underdamped Langevin MCMC
    Tim Zajic
    http://arxiv.org/abs/1912.03154v1

    • [stat.ML]Solving Bernoulli Rank-One Bandits with Unimodal Thompson Sampling
    Cindy Trinh, Emilie Kaufmann, Claire Vernade, Richard Combes
    http://arxiv.org/abs/1912.03074v1