cs.AI - 人工智能
cs.CG - 计算几何学 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.ET - 新兴技术 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.MS - 数学软件 cs.NE - 神经与进化计算 cs.PF - 计算性能 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 econ.GN - 一般经济学 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.NA - 数值分析 math.OC - 优化与控制 math.ST - 统计理论 physics.comp-ph - 计算物理学 physics.soc-ph - 物理学与社会 q-fin.ST - 统计金融学 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习 stat.OT - 其他统计学
• [cs.AI]A Framework for Evaluating Agricultural Ontologies
• [cs.AI]An AGI with Time-Inconsistent Preferences
• [cs.AI]Awareness of Voter Passion Greatly Improves the Distortion of Metric Social Choice
• [cs.AI]House Markets and Single-Peaked Preferences: From Centralized to Decentralized Allocation Procedures
• [cs.AI]Learning to Interactively Learn and Assist
• [cs.AI]Training an Interactive Helper
• [cs.CG]Structural Design Using Laplacian Shells
• [cs.CL]Compound Probabilistic Context-Free Grammars for Grammar Induction
• [cs.CL]Embedding Projection for Targeted Cross-Lingual Sentiment: Model Comparisons and a Real-World Study
• [cs.CL]Good Secretaries, Bad Truck Drivers? Occupational Gender Stereotypes in Sentiment Analysis
• [cs.CL]Multimodal and Multi-view Models for Emotion Recognition
• [cs.CL]Mutual exclusivity as a challenge for neural networks
• [cs.CL]Saliency-driven Word Alignment Interpretation for Neural Machine Translation
• [cs.CR]Quantitative Verification of Neural Networks And its Security Applications
• [cs.CV]3D Surface Reconstruction from Voxel-based Lidar Data
• [cs.CV]A CNN-Based Super-Resolution Technique for Active Fire Detection on Sentinel-2 Data
• [cs.CV]COP: Customized Deep Model Compression via Regularized Correlation-Based Filter-Level Pruning
• [cs.CV]Discrete Optimization of Ray Potentials for Semantic 3D Reconstruction
• [cs.CV]EKFPnP: Extended Kalman Filter for Camera Pose Estimation in a Sequence of Images
• [cs.CV]Efficient Multi-Domain Network Learning by Covariance Normalization
• [cs.CV]End-to-End Learning of Multi-scale Convolutional Neural Network for Stereo Matching
• [cs.CV]Graph-Based Offline Signature Verification
• [cs.CV]Interpretable Image Recognition with Hierarchical Prototypes
• [cs.CV]Learning Features with Differentiable Closed-Form Solver for Tracking
• [cs.CV]RUBi: Reducing Unimodal Biases in Visual Question Answering
• [cs.CV]Serif or Sans: Visual Font Analytics on Book Covers and Online Advertisements
• [cs.CV]Shape from Water Reflection
• [cs.CV]SkyNet: A Champion Model for DAC-SDC on Low Power Object Detection
• [cs.CV]Technical Report: Fast Robot Arm Inverse Kinematics and Path Planning Under Complex Obstacle Constraint
• [cs.CY]Age and gender bias in pedestrian detection algorithms
• [cs.CY]BPM for the masses: empowering participants of Cognitive Business Processes
• [cs.CY]Blocking Mechanism of Porn Website in India: Claim and Truth
• [cs.CY]Future of Computing is Boring (and that is exciting!) or How to get to Computing Nirvana in 20 years or less
• [cs.CY]In-Vehicle False Information Attack Detection and Mitigation Framework using Machine Learning and Software Defined Networking
• [cs.CY]Towards Enterprise-Ready AI Deployments Minimizing the Risk of Consuming AI Models in Business Applications
• [cs.DB]Datalog Materialisation in Distributed RDF Stores with Dynamic Data Exchange
• [cs.DC]2-Edge-Connectivity and 2-Vertex-Connectivity of an Asynchronous Distributed Network
• [cs.DC]A Language for Programming Edge Clouds for Next Generation IoT Applications
• [cs.DC]A Permit-Based Optimistic Byzantine Ledger
• [cs.DC]Container Density Improvements with Dynamic Memory Extension using NAND Flash
• [cs.DC]Fast Data: Moving beyond from Big Data’s map-reduce
• [cs.DC]Improving Branch Prediction By Modeling Global History with Convolutional Neural Networks
• [cs.DC]Pyramid: A General Framework for Distributed Similarity Search
• [cs.DC]The Coming Age of Pervasive Data Processing
• [cs.ET]A Winograd-based Integrated Photonics Accelerator for Convolutional Neural Networks
• [cs.HC]Deep Learning in a Computational Model for Conceptual Shifts in a Co-Creative Design System
• [cs.IR]Newswire versus Social Media for Disaster Response and Recovery
• [cs.IT]A note on Bianchi-Donà’s proof to the variance formula of von Neumann entropy
• [cs.IT]ETTR Bounds and Approximation Solutions of Blind Rendezvous Policies in Cognitive Radio Networks with Random Channel States
• [cs.IT]Isometry-Dual Flags of AG Codes
• [cs.IT]On List Decoding of Insertion and Deletion Errors
• [cs.IT]On the Relationship Between Measures of Relative Efficiency for Random Signal Detection
• [cs.IT]On the Upload versus Download Cost for Secure and Private Matrix Multiplication
• [cs.IT]Repairing Generalized Reed-Muller Codes
• [cs.IT]Tone-index Multisine Modulation for SWIPT
• [cs.LG]A Review of Statistical Learning Machines from ATR to DNA Microarrays: design, assessment, and advice for practitioners
• [cs.LG]A Theoretical Connection Between Statistical Physics and Reinforcement Learning
• [cs.LG]An Unsupervised Bayesian Neural Network for Truth Discovery
• [cs.LG]Assessing the Applicability of Authorship Verification Methods
• [cs.LG]DLIME: A Deterministic Local Interpretable Model-Agnostic Explanations Approach for Computer-Aided Diagnosis Systems
• [cs.LG]Deceptive Reinforcement Learning Under Adversarial Manipulations on Cost Signals
• [cs.LG]Emotion Recognition Using Fusion of Audio and Video Features
• [cs.LG]Explaining Deep Learning Models with Constrained Adversarial Examples
• [cs.LG]Gauge theory and twins paradox of disentangled representations
• [cs.LG]Generating User-friendly Explanations for Loan Denials using GANs
• [cs.LG]Improving Stochastic Neighbour Embedding fundamentally with a well-defined data-dependent kernel
• [cs.LG]Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning
• [cs.LG]Learning Causal State Representations of Partially Observable Environments
• [cs.LG]Learning Explainable Models Using Attribution Priors
• [cs.LG]Modeling Severe Traffic Accidents With Spatial And Temporal Features
• [cs.LG]Multi-label Classification with Optimal Thresholding for Multi-composition Spectroscopic Analysis
• [cs.LG]Neural Proximal/Trust Region Policy Optimization Attains Globally Optimal Policy
• [cs.LG]Neural Transfer Learning for Cry-based Diagnosis of Perinatal Asphyxia
• [cs.LG]Perceptual Generative Autoencoders
• [cs.LG]Policy Optimization with Stochastic Mirror Descent
• [cs.LG]Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives
• [cs.LG]Semi-Supervised Learning with Self-Supervised Networks
• [cs.LG]Sequential Neural Processes
• [cs.LG]TS-CHIEF: A Scalable and Accurate Forest Algorithm for Time Series Classification
• [cs.LG]Traffic Flow Combination Forecasting Method Based on Improved LSTM and ARIMA
• [cs.MA]On Multi-Agent Learning in Team Sports Games
• [cs.MS]Parallel Performance of Algebraic Multigrid Domain Decomposition (AMG-DD)
• [cs.NE]Derivation of the Variational Bayes Equations
• [cs.NE]Evolutionary Computation and AI Safety: Research Problems Impeding Routine and Safe Real-world Application of Evolution
• [cs.NE]Sharp Bounds on the Runtime of the (1+1) EA via Drift Analysis and Analytic Combinatorial Tools
• [cs.NE]Tactile Hallucinations on Artificial Skin Induced by Homeostasis in a Deep Boltzmann Machine
• [cs.PF]Mirovia: A Benchmarking Suite for Modern Heterogeneous Computing
• [cs.PF]Straggler Mitigation at Scale
• [cs.RO]A laser-microfabricated electrohydrodynamic thruster for centimeter-scale aerial robots
• [cs.RO]DensePeds: Pedestrian Tracking in Dense Crowds Using Front-RVO and Sparse Features
• [cs.RO]Flower Interaction Subsystem for a Precision Pollination Robot
• [cs.RO]Micro Air Vehicle Link (MAVLink) in a Nutshell: A Survey
• [cs.RO]Modeling Multi-Vehicle Interaction Scenarios Using Gaussian Random Field
• [cs.RO]Planning Robot Motion using Deep Visual Prediction
• [cs.RO]The Role of Compute in Autonomous Aerial Vehicles
• [cs.SD]A Convolutional Approach to Melody Line Identification in Symbolic Scores
• [cs.SD]Naver at ActivityNet Challenge 2019 — Task B Active Speaker Detection (AVA)
• [cs.SE]SampleFix: Learning to Correct Programs by Sampling Diverse Fixes
• [cs.SE]Software Engineering Practices for Machine Learning
• [cs.SI]Diversifying Seeds and Audience in Social Influence Maximization
• [cs.SI]Dynamic Network Embeddings for Network Evolution Analysis
• [cs.SI]Emotion Cognizance Improves Fake News Identification
• [cs.SI]Models of Continuous-Time Networks with Tie Decay, Diffusion, and Convection
• [cs.SI]Predicting kills in Game of Thrones using network properties
• [cs.SI]Protecting shared information in networks: a network security game with strategic attacks
• [econ.EM]Policy Targeting under Network Interference
• [econ.GN]Identify and understand pay-it-forward reciprocity using millions of online red packets
• [eess.AS]Acoustic Modeling for Automatic Lyrics-to-Audio Alignment
• [eess.AS]DALI: a large Dataset of synchronized Audio, LyrIcs and notes, automatically created using teacher-student machine learning paradigm
• [eess.IV]3DBGrowth: volumetric vertebrae segmentation and reconstruction in magnetic resonance imaging
• [eess.IV]A Deep Regression Model for Seed Identification in Prostate Brachytherapy
• [eess.IV]Brain MR Image Segmentation in Small Dataset with Adversarial Defense and Task Reorganization
• [eess.IV]Deep Learning of Compressed Sensing Operators with Structural Similarity Loss
• [eess.IV]Learning a sparse database for patch-based medical image segmentation
• [eess.IV]MFP-Unet: A Novel Deep Learning Based Approach for Left Ventricle Segmentation in Echocardiography
• [eess.SP]Complex Signal Denoising and Interference Mitigation for Automotive Radar Using Convolutional Neural Networks
• [eess.SP]Deep Neural Network Based Resource Allocation for V2X Communications
• [eess.SP]Optimal Least-Squares Estimator and Precoder for Energy Beamforming over IQ-Impaired Channels
• [eess.SY]Keep soft robots soft — a data-driven based trade-off between feed-forward and feedback control
• [eess.SY]ReachNN: Reachability Analysis of Neural-Network Controlled Systems
• [eess.SY]Trajectory Generation for UAVs in Unknown Environments with Extreme Wind Disturbances
• [math.NA]Advances in Implementation, Theoretical Motivation, and Numerical Results for the Nested Iteration with Range Decomposition Algorithm
• [math.NA]Comments on the article “A Bayesian conjugate gradient method”
• [math.OC]A Stochastic Composite Gradient Method with Incremental Variance Reduction
• [math.OC]Complexity of Highly Parallel Non-Smooth Convex Optimization
• [math.OC]Riemannian optimization on the simplex of positive definite matrices
• [math.ST]A note on locally optimal designs for generalized linear models with restricted support
• [math.ST]Approximate separability of symmetrically penalized least squares in high dimensions: characterization and consequences
• [math.ST]Distribution-robust mean estimation via smoothed random perturbations
• [math.ST]Refinements of the Kiefer-Wolfowitz Theorem and a Test of Concavity
• [math.ST]Regression medians and uniqueness
• [math.ST]Uniformly consistently estimating the proportion of false null hypotheses for composite null hypotheses via Lebesgue-Stieltjes integral equations
• [physics.comp-ph]A unified sparse optimization framework to learn parsimonious physics-informed models from data
• [physics.soc-ph]Link Prediction in Real-World Multiplex Networks via Layer Reconstruction Method
• [q-fin.ST]Hybrid symbiotic organisms search feedforward neural net-works model for stock price prediction
• [stat.AP]Assessing the Validity of a a priori Patient-Trial Generalizability Score using Real-world Data from a Large Clinical Data Research Network: A Colorectal Cancer Clinical Trial Case Study
• [stat.AP]Forecasting the Remittances of the Overseas Filipino Workers in the Philippines
• [stat.AP]New approach for stochastic downscaling and bias correction of daily mean temperatures to a high-resolution grid
• [stat.AP]Simultaneous Variable Selection, Clustering, and Smoothing in Function on Scalar Regression
• [stat.ME]An Interval Estimation Approach to Selection Bias in Observational Studies
• [stat.ME]Bayesian Nonparametric Clustering of Continuous-Time Hidden Markov Models for Health Trajectories
• [stat.ME]Bayesian influence diagnostics and outlier detection for meta-analysis of diagnostic test accuracy
• [stat.ME]Dynamic time series clustering via volatility change-points
• [stat.ME]Parametric versus Semi and Nonparametric Regression Models
• [stat.ME]Spatial 3D Matérn priors for fast whole-brain fMRI analysis
• [stat.ME]The Power of Unbiased Recursive Partitioning: A Unifying View of CTree, MOB, and GUIDE
• [stat.ML]A Self-supervised Approach to Hierarchical Forecasting with Applications to Groupwise Synthetic Controls
• [stat.ML]AMF: Aggregated Mondrian Forests for Online Learning
• [stat.ML]Certifiably Optimal Sparse Inverse Covariance Estimation
• [stat.ML]Coding for Crowdsourced Classification with XOR Queries
• [stat.ML]From Non-Paying to Premium: Predicting User Conversion in Video Games with Ensemble Learning
• [stat.ML]Learning Fair and Transferable Representations
• [stat.ML]Monte Carlo Gradient Estimation in Machine Learning
• [stat.ML]Non-Asymptotic Pure Exploration by Solving Games
• [stat.ML]Res-embedding for Deep Learning Based Click-Through Rate Prediction Modeling
• [stat.ML]Restless dependent bandits with fading memory
• [stat.ML]Spectral Properties of Radial Kernels and Clustering in High Dimensions
• [stat.OT]A Role for Symmetry in the Bayesian Solution of Differential Equations
·····································
• [cs.AI]A Framework for Evaluating Agricultural Ontologies
Anat Goldstein, Orit Raphaeli, Lior Fink, Amots Hetzroni, Gilad Ravid
http://arxiv.org/abs/1906.10450v1
• [cs.AI]An AGI with Time-Inconsistent Preferences
James D. Miller, Roman Yampolskiy
http://arxiv.org/abs/1906.10536v1
• [cs.AI]Awareness of Voter Passion Greatly Improves the Distortion of Metric Social Choice
Ben Abramowitz, Elliot Anshelevich, Wennan Zhu
http://arxiv.org/abs/1906.10562v1
• [cs.AI]House Markets and Single-Peaked Preferences: From Centralized to Decentralized Allocation Procedures
Aurélie Beynier, Nicolas Maudet, Simon Rey, Parham Shams
http://arxiv.org/abs/1906.10250v1
• [cs.AI]Learning to Interactively Learn and Assist
Mark Woodward, Chelsea Finn, Karol Hausman
http://arxiv.org/abs/1906.10187v1
• [cs.AI]Training an Interactive Helper
Mark Woodward, Chelsea Finn, Karol Hausman
http://arxiv.org/abs/1906.10165v1
• [cs.CG]Structural Design Using Laplacian Shells
Erva Ulu, James McCann, Levent Burak Kara
http://arxiv.org/abs/1906.10669v1
• [cs.CL]Compound Probabilistic Context-Free Grammars for Grammar Induction
Yoon Kim, Chris Dyer, Alexander M. Rush
http://arxiv.org/abs/1906.10225v1
• [cs.CL]Embedding Projection for Targeted Cross-Lingual Sentiment: Model Comparisons and a Real-World Study
Jeremy Barnes, Roman Klinger
http://arxiv.org/abs/1906.10519v1
• [cs.CL]Good Secretaries, Bad Truck Drivers? Occupational Gender Stereotypes in Sentiment Analysis
Jayadev Bhaskaran, Isha Bhallamudi
http://arxiv.org/abs/1906.10256v1
• [cs.CL]Multimodal and Multi-view Models for Emotion Recognition
Gustavo Aguilar, Viktor Rozgić, Weiran Wang, Chao Wang
http://arxiv.org/abs/1906.10198v1
• [cs.CL]Mutual exclusivity as a challenge for neural networks
Kanishk Gandhi, Brenden M. Lake
http://arxiv.org/abs/1906.10197v1
• [cs.CL]Saliency-driven Word Alignment Interpretation for Neural Machine Translation
Shuoyang Ding, Hainan Xu, Philipp Koehn
http://arxiv.org/abs/1906.10282v1
• [cs.CR]Quantitative Verification of Neural Networks And its Security Applications
Teodora Baluta, Shiqi Shen, Shweta Shinde, Kuldeep S. Meel, Prateek Saxena
http://arxiv.org/abs/1906.10395v1
• [cs.CV]3D Surface Reconstruction from Voxel-based Lidar Data
Luis Roldão, Raoul de Charette, Anne Verroust-Blondet
http://arxiv.org/abs/1906.10515v1
• [cs.CV]A CNN-Based Super-Resolution Technique for Active Fire Detection on Sentinel-2 Data
Massimiliano Gargiulo, Domenico Antonio Giuseppe Dell’Aglio, Antonio Iodice, Daniele Riccio, Giuseppe Ruello
http://arxiv.org/abs/1906.10413v1
• [cs.CV]COP: Customized Deep Model Compression via Regularized Correlation-Based Filter-Level Pruning
Wenxiao Wang, Cong Fu, Jishun Guo, Deng Cai, Xiaofei He
http://arxiv.org/abs/1906.10337v1
• [cs.CV]Discrete Optimization of Ray Potentials for Semantic 3D Reconstruction
Nikolay Savinov, Lubor Ladicky, Christian Haene, Marc Pollefeys
http://arxiv.org/abs/1906.10491v1
• [cs.CV]EKFPnP: Extended Kalman Filter for Camera Pose Estimation in a Sequence of Images
Mohammad Amin Mehralian, Mohsen Soryani
http://arxiv.org/abs/1906.10324v1
• [cs.CV]Efficient Multi-Domain Network Learning by Covariance Normalization
Yunsheng Li, Nuno Vasconcelos
http://arxiv.org/abs/1906.10267v1
• [cs.CV]End-to-End Learning of Multi-scale Convolutional Neural Network for Stereo Matching
Li Zhang, Quanhong Wang, Haihua Lu, Yong Zhao
http://arxiv.org/abs/1906.10399v1
• [cs.CV]Graph-Based Offline Signature Verification
Paul Maergner, Nicholas R. Howe, Kaspar Riesen, Rolf Ingold, Andreas Fischer
http://arxiv.org/abs/1906.10401v1
• [cs.CV]Interpretable Image Recognition with Hierarchical Prototypes
Peter Hase, Chaofan Chen, Oscar Li, Cynthia Rudin
http://arxiv.org/abs/1906.10651v1
• [cs.CV]Learning Features with Differentiable Closed-Form Solver for Tracking
Linyu Zheng, Ming Tang, JinqiaoWang, Hanqing Lu
http://arxiv.org/abs/1906.10414v1
• [cs.CV]RUBi: Reducing Unimodal Biases in Visual Question Answering
Remi Cadene, Corentin Dancette, Hedi Ben-younes, Matthieu Cord, Devi Parikh
http://arxiv.org/abs/1906.10169v1
• [cs.CV]Serif or Sans: Visual Font Analytics on Book Covers and Online Advertisements
Yuto Shinahara, Takuro Karamatsu, Daisuke Harada, Kota Yamaguchi, Seiichi Uchida
http://arxiv.org/abs/1906.10269v1
• [cs.CV]Shape from Water Reflection
Ryo Kawahara, Shohei Nobuhara, Ko Nishino
http://arxiv.org/abs/1906.10284v1
• [cs.CV]SkyNet: A Champion Model for DAC-SDC on Low Power Object Detection
Xiaofan Zhang, Yuhong Li, Cong Hao, Kyle Rupnow, Jinjun Xiong, Wen-mei Hwu, Deming Chen
http://arxiv.org/abs/1906.10327v1
• [cs.CV]Technical Report: Fast Robot Arm Inverse Kinematics and Path Planning Under Complex Obstacle Constraint
David W. Arathorn
http://arxiv.org/abs/1906.10678v1
• [cs.CY]Age and gender bias in pedestrian detection algorithms
Martim Brandao
http://arxiv.org/abs/1906.10490v1
• [cs.CY]BPM for the masses: empowering participants of Cognitive Business Processes
Aleksander Slominski, Vinod Muthusamy
http://arxiv.org/abs/1906.10415v1
• [cs.CY]Blocking Mechanism of Porn Website in India: Claim and Truth
Saurabh Pandey, Dr. Harish Sharma
http://arxiv.org/abs/1906.10379v1
• [cs.CY]Future of Computing is Boring (and that is exciting!) or How to get to Computing Nirvana in 20 years or less
Aleksander Slominski, Vinod Muthusamy, Vatche Ishakian
http://arxiv.org/abs/1906.10398v1
• [cs.CY]In-Vehicle False Information Attack Detection and Mitigation Framework using Machine Learning and Software Defined Networking
Zadid Khan, Mashrur Chowdhury, Mhafuzul Islam, Chin-Ya Huang, Mizanur Rahman
http://arxiv.org/abs/1906.10203v1
• [cs.CY]Towards Enterprise-Ready AI Deployments Minimizing the Risk of Consuming AI Models in Business Applications
Aleksander Slominski, Vinod Muthusamy, Vatche Ishakian
http://arxiv.org/abs/1906.10418v1
• [cs.DB]Datalog Materialisation in Distributed RDF Stores with Dynamic Data Exchange
Temitope Ajileye, Boris Motik, Ian Horrocks
http://arxiv.org/abs/1906.10261v1
• [cs.DC]2-Edge-Connectivity and 2-Vertex-Connectivity of an Asynchronous Distributed Network
Abusayeed Saifullah
http://arxiv.org/abs/1906.10275v1
• [cs.DC]A Language for Programming Edge Clouds for Next Generation IoT Applications
Muthucumaru Maheswaran, Robert Wenger, Richard Olaniyan, Salman Memon, Olamilekan Fadahunsi, Richboy Echomgbe
http://arxiv.org/abs/1906.09962v1
• [cs.DC]A Permit-Based Optimistic Byzantine Ledger
Roland Schmid, Roger Wattenhofer
http://arxiv.org/abs/1906.10368v1
• [cs.DC]Container Density Improvements with Dynamic Memory Extension using NAND Flash
Jan S. Rellermeyer, Maher Amer, Richard Smutzer, Karthick Rajamani
http://arxiv.org/abs/1906.10239v1
• [cs.DC]Fast Data: Moving beyond from Big Data’s map-reduce
Adam Lev-Libfeld, Alexander Margolin
http://arxiv.org/abs/1906.10468v1
• [cs.DC]Improving Branch Prediction By Modeling Global History with Convolutional Neural Networks
Stephen J Tarsa, Chit-Kwan Lin, Gokce Keskin, Gautham Chinya, Hong Wang
http://arxiv.org/abs/1906.09889v1
• [cs.DC]Pyramid: A General Framework for Distributed Similarity Search
Shiyuan Deng, Xiao Yan, Kelvin K. W. Ng, Chenyu Jiang, James Cheng
http://arxiv.org/abs/1906.10602v1
• [cs.DC]The Coming Age of Pervasive Data Processing
Jan S. Rellermeyer, Sobhan Omranian Khorasani, Dan Graur, Apourva Parthasarathy
http://arxiv.org/abs/1906.10496v1
• [cs.ET]A Winograd-based Integrated Photonics Accelerator for Convolutional Neural Networks
Armin Mehrabian, Mario Miscuglio, Yousra Alkabani, Volker J. Sorger, Tarek El-Ghazawi
http://arxiv.org/abs/1906.10487v1
• [cs.HC]Deep Learning in a Computational Model for Conceptual Shifts in a Co-Creative Design System
Pegah Karimi, Mary Lou Maher, Nicholas Davis, Kazjon Grace
http://arxiv.org/abs/1906.10188v1
• [cs.IR]Newswire versus Social Media for Disaster Response and Recovery
Rakesh Verma, Samaneh Karimi, Daniel Lee, Omprakash Gnawali, Azadeh Shakery
http://arxiv.org/abs/1906.10607v1
• [cs.IT]A note on Bianchi-Donà’s proof to the variance formula of von Neumann entropy
Lu Wei
http://arxiv.org/abs/1906.10303v1
• [cs.IT]ETTR Bounds and Approximation Solutions of Blind Rendezvous Policies in Cognitive Radio Networks with Random Channel States
Cheng-Shang Chang, Duan-Shin Lee, Yu-Lun Lin, Jen-Hung Wang
http://arxiv.org/abs/1906.10424v1
• [cs.IT]Isometry-Dual Flags of AG Codes
Maria Bras-Amorós, Iwan Duursma, Euijin Hong
http://arxiv.org/abs/1906.10620v1
• [cs.IT]On List Decoding of Insertion and Deletion Errors
Shu Liu, Ivan Tjuawinata, Chaoping Xing
http://arxiv.org/abs/1906.09705v2
• [cs.IT]On the Relationship Between Measures of Relative Efficiency for Random Signal Detection
Nagananda, K. G
http://arxiv.org/abs/1906.10427v1
• [cs.IT]On the Upload versus Download Cost for Secure and Private Matrix Multiplication
Wei-Ting Chang, Ravi Tandon
http://arxiv.org/abs/1906.10684v1
• [cs.IT]Repairing Generalized Reed-Muller Codes
Tingting Chen, Xiande Zhang
http://arxiv.org/abs/1906.10310v1
• [cs.IT]Tone-index Multisine Modulation for SWIPT
Ioannis Krikidis, Constantinos Psomas
http://arxiv.org/abs/1906.10386v1
• [cs.LG]A Review of Statistical Learning Machines from ATR to DNA Microarrays: design, assessment, and advice for practitioners
Waleed A. Yousef
http://arxiv.org/abs/1906.10019v2
• [cs.LG]A Theoretical Connection Between Statistical Physics and Reinforcement Learning
Jad Rahme, Ryan P. Adams
http://arxiv.org/abs/1906.10228v1
• [cs.LG]An Unsupervised Bayesian Neural Network for Truth Discovery
Jielong Yang, Wee Peng Tay
http://arxiv.org/abs/1906.10470v1
• [cs.LG]Assessing the Applicability of Authorship Verification Methods
Oren Halvani, Christian Winter, Lukas Graner
http://arxiv.org/abs/1906.10551v1
• [cs.LG]DLIME: A Deterministic Local Interpretable Model-Agnostic Explanations Approach for Computer-Aided Diagnosis Systems
Muhammad Rehman Zafar, Naimul Mefraz Khan
http://arxiv.org/abs/1906.10263v1
• [cs.LG]Deceptive Reinforcement Learning Under Adversarial Manipulations on Cost Signals
Yunhan Huang, Quanyan Zhu
http://arxiv.org/abs/1906.10571v1
• [cs.LG]Emotion Recognition Using Fusion of Audio and Video Features
Juan D. S. Ortega, Patrick Cardinal, Alessandro L. Koerich
http://arxiv.org/abs/1906.10623v1
• [cs.LG]Explaining Deep Learning Models with Constrained Adversarial Examples
Jonathan Moore, Nils Hammerla, Chris Watkins
http://arxiv.org/abs/1906.10671v1
• [cs.LG]Gauge theory and twins paradox of disentangled representations
X. Dong, L. Zhou
http://arxiv.org/abs/1906.10545v1
• [cs.LG]Generating User-friendly Explanations for Loan Denials using GANs
Ramya Srinivasan, Ajay Chander, Pouya Pezeshkpour
http://arxiv.org/abs/1906.10244v1
• [cs.LG]Improving Stochastic Neighbour Embedding fundamentally with a well-defined data-dependent kernel
Ye Zhu, Kai Ming Ting
http://arxiv.org/abs/1906.09744v2
• [cs.LG]Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning
Sihui Luo, Xinchao Wang, Gongfan Fang, Yao Hu, Dapeng Tao, Mingli Song
http://arxiv.org/abs/1906.10546v1
• [cs.LG]Learning Causal State Representations of Partially Observable Environments
Amy Zhang, Zachary C. Lipton, Luis Pineda, Kamyar Azizzadenesheli, Anima Anandkumar, Laurent Itti, Joelle Pineau, Tommaso Furlanello
http://arxiv.org/abs/1906.10437v1
• [cs.LG]Learning Explainable Models Using Attribution Priors
Gabriel Erion, Joseph D. Janizek, Pascal Sturmfels, Scott Lundberg, Su-In Lee
http://arxiv.org/abs/1906.10670v1
• [cs.LG]Modeling Severe Traffic Accidents With Spatial And Temporal Features
Devashish Khulbe, Soumya Sourav
http://arxiv.org/abs/1906.10317v1
• [cs.LG]Multi-label Classification with Optimal Thresholding for Multi-composition Spectroscopic Analysis
Luyun Gan, Brosnan Yuen, Tao Lu
http://arxiv.org/abs/1906.10242v1
• [cs.LG]Neural Proximal/Trust Region Policy Optimization Attains Globally Optimal Policy
Boyi Liu, Qi Cai, Zhuoran Yang, Zhaoran Wang
http://arxiv.org/abs/1906.10306v1
• [cs.LG]Neural Transfer Learning for Cry-based Diagnosis of Perinatal Asphyxia
Charles C. Onu, Jonathan Lebensold, William L. Hamilton, Doina Precup
http://arxiv.org/abs/1906.10199v1
• [cs.LG]Perceptual Generative Autoencoders
Zijun Zhang, Ruixiang Zhang, Zongpeng Li, Yoshua Bengio, Liam Paull
http://arxiv.org/abs/1906.10335v1
• [cs.LG]Policy Optimization with Stochastic Mirror Descent
Long Yang, Yu Zhang
http://arxiv.org/abs/1906.10462v1
• [cs.LG]Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives
Anirudh Goyal, Shagun Sodhani, Jonathan Binas, Xue Bin Peng, Sergey Levine, Yoshua Bengio
http://arxiv.org/abs/1906.10667v1
• [cs.LG]Semi-Supervised Learning with Self-Supervised Networks
Phi Vu Tran
http://arxiv.org/abs/1906.10343v1
• [cs.LG]Sequential Neural Processes
Gautam Singh, Jaesik Yoon, Youngsung Son, Sungjin Ahn
http://arxiv.org/abs/1906.10264v1
• [cs.LG]TS-CHIEF: A Scalable and Accurate Forest Algorithm for Time Series Classification
Ahmed Shifaz, Charlotte Pelletier, Francois Petitjean, Geoffrey I. Webb
http://arxiv.org/abs/1906.10329v1
• [cs.LG]Traffic Flow Combination Forecasting Method Based on Improved LSTM and ARIMA
Boyi Liu, Xiangyan Tang, Jieren Cheng, Pengchao Shi
http://arxiv.org/abs/1906.10407v1
• [cs.MA]On Multi-Agent Learning in Team Sports Games
Yunqi Zhao, Igor Borovikov, Jason Rupert, Caedmon Somers, Ahmad Beirami
http://arxiv.org/abs/1906.10124v1
• [cs.MS]Parallel Performance of Algebraic Multigrid Domain Decomposition (AMG-DD)
Wayne Mitchell, Robert Strzodka, Robert Falgout, Stephen McCormick
http://arxiv.org/abs/1906.10575v1
• [cs.NE]Derivation of the Variational Bayes Equations
Alianna J. Maren
http://arxiv.org/abs/1906.08804v2
• [cs.NE]Evolutionary Computation and AI Safety: Research Problems Impeding Routine and Safe Real-world Application of Evolution
Joel Lehman
http://arxiv.org/abs/1906.10189v1
• [cs.NE]Sharp Bounds on the Runtime of the (1+1) EA via Drift Analysis and Analytic Combinatorial Tools
Hsien-Kuei Hwang, Carsten Witt
http://arxiv.org/abs/1906.09047v2
• [cs.NE]Tactile Hallucinations on Artificial Skin Induced by Homeostasis in a Deep Boltzmann Machine
Michael Deistler, Yagmur Yener, Florian Bergner, Pablo Lanillos, Gordon Cheng
http://arxiv.org/abs/1906.10592v1
• [cs.PF]Mirovia: A Benchmarking Suite for Modern Heterogeneous Computing
Bodun Hu, Christopher J. Rossbach
http://arxiv.org/abs/1906.10347v1
• [cs.PF]Straggler Mitigation at Scale
Mehmet Fatih Aktas, Emina Soljanin
http://arxiv.org/abs/1906.10664v1
• [cs.RO]A laser-microfabricated electrohydrodynamic thruster for centimeter-scale aerial robots
Elma Dedic, Yogesh M Chukewad, Ravi Sankar Vaddi, Igor Novosselov, Sawyer B Fuller
http://arxiv.org/abs/1906.10210v1
• [cs.RO]DensePeds: Pedestrian Tracking in Dense Crowds Using Front-RVO and Sparse Features
Rohan Chandra, Uttaran Bhattacharya, Aniket Bera, Dinesh Manocha
http://arxiv.org/abs/1906.10313v1
• [cs.RO]Flower Interaction Subsystem for a Precision Pollination Robot
Jared Strader, Jennifer Nguyen, Christopher Tatsch, Yixin Du, Kyle Lassak, Benjamin Buzzo, Ryan Watson, Henry Cerbone, Nicholas Ohi, Chizhao Yang, Yu Gu
http://arxiv.org/abs/1906.09294v1
• [cs.RO]Micro Air Vehicle Link (MAVLink) in a Nutshell: A Survey
Anis Koubaa, Azza Allouch, Maram Alajlan, Yasir Javed, Abdelfettah Belghith, Mohamed Khalgui
http://arxiv.org/abs/1906.10641v1
• [cs.RO]Modeling Multi-Vehicle Interaction Scenarios Using Gaussian Random Field
Yaohui Guo, Vinay Varma Kalidindi, Mansur Arief, Wenshuo Wang, Jiacheng Zhu, Huei Peng, Ding Zhao
http://arxiv.org/abs/1906.10307v1
• [cs.RO]Planning Robot Motion using Deep Visual Prediction
Meenakshi Sarkar, Prabhu Pradhan, Debasish Ghose
http://arxiv.org/abs/1906.10182v1
• [cs.RO]The Role of Compute in Autonomous Aerial Vehicles
Behzad Boroujerdian, Hasan Genc, Srivatsan Krishnan, Bardienus Pieter Duisterhof, Brian Plancher, Kayvan Mansoorshahi, Marcelino Almeida, Wenzhi Cui, Aleksandra Faust, Vijay Janapa Reddi
http://arxiv.org/abs/1906.10513v1
• [cs.SD]A Convolutional Approach to Melody Line Identification in Symbolic Scores
Federico Simonetta, Carlos Cancino-Chacón, Stavros Ntalampiras, Gerhard Widmer
http://arxiv.org/abs/1906.10547v1
• [cs.SD]Naver at ActivityNet Challenge 2019 — Task B Active Speaker Detection (AVA)
Joon Son Chung
http://arxiv.org/abs/1906.10555v1
• [cs.SE]SampleFix: Learning to Correct Programs by Sampling Diverse Fixes
Hossein Hajipour, Apratim Bhattacharya, Mario Fritz
http://arxiv.org/abs/1906.10502v1
• [cs.SE]Software Engineering Practices for Machine Learning
Peter Kriens, Tim Verbelen
http://arxiv.org/abs/1906.10366v1
• [cs.SI]Diversifying Seeds and Audience in Social Influence Maximization
Yu Zhang
http://arxiv.org/abs/1906.09357v1
• [cs.SI]Dynamic Network Embeddings for Network Evolution Analysis
Chuanchang Chen, Yubo Tao, Hai Lin
http://arxiv.org/abs/1906.09860v1
• [cs.SI]Emotion Cognizance Improves Fake News Identification
Anoop K, Deepak P, Lajish V L
http://arxiv.org/abs/1906.10365v1
• [cs.SI]Models of Continuous-Time Networks with Tie Decay, Diffusion, and Convection
Xinzhe Zuo, Mason A Porter
http://arxiv.org/abs/1906.09394v1
• [cs.SI]Predicting kills in Game of Thrones using network properties
Jaka Stavanja, Matej Klemen
http://arxiv.org/abs/1906.09468v1
• [cs.SI]Protecting shared information in networks: a network security game with strategic attacks
Bram de Witte, Paolo Frasca, Bastiaan Overvest, Judith Timmer
http://arxiv.org/abs/1906.09486v1
• [econ.EM]Policy Targeting under Network Interference
Davide Viviano
http://arxiv.org/abs/1906.10258v1
• [econ.GN]Identify and understand pay-it-forward reciprocity using millions of online red packets
Yuan Yuan, Tracy Liu, Chenhao Tan, Qian Chen, Alex Pentland, Jie Tang
http://arxiv.org/abs/1906.09698v1
• [eess.AS]Acoustic Modeling for Automatic Lyrics-to-Audio Alignment
Chitralekha Gupta, Emre Yılmaz, Haizhou Li
http://arxiv.org/abs/1906.10369v1
• [eess.AS]DALI: a large Dataset of synchronized Audio, LyrIcs and notes, automatically created using teacher-student machine learning paradigm
Gabriel Meseguer-Brocal, Alice Cohen-Hadria, Geoffroy Peeters
http://arxiv.org/abs/1906.10606v1
• [eess.IV]3DBGrowth: volumetric vertebrae segmentation and reconstruction in magnetic resonance imaging
Jonathan S. Ramos, Mirela T. Cazzolato, Bruno S. Faiçal, Marcello H. Nogueira-Barbosa, Caetano Traina Jr., Agma J. M. Traina
http://arxiv.org/abs/1906.10288v1
• [eess.IV]A Deep Regression Model for Seed Identification in Prostate Brachytherapy
Yading Yuan, Ren-Dih Sheu, Luke Fu, Yeh-Chi Lo
http://arxiv.org/abs/1906.10183v1
• [eess.IV]Brain MR Image Segmentation in Small Dataset with Adversarial Defense and Task Reorganization
Xuhua Ren, Lichi Zhang, Qian Wang, Dinggang Shen
http://arxiv.org/abs/1906.10400v1
• [eess.IV]Deep Learning of Compressed Sensing Operators with Structural Similarity Loss
Yochai Zur, Amir Adler
http://arxiv.org/abs/1906.10411v1
• [eess.IV]Learning a sparse database for patch-based medical image segmentation
Moti Freiman, Hannes Nickisch, Holger Schmitt, Pal Maurovich-Horvat, Patrick Donnelly, Mani Vembar, Liran Goshen
http://arxiv.org/abs/1906.10338v1
• [eess.IV]MFP-Unet: A Novel Deep Learning Based Approach for Left Ventricle Segmentation in Echocardiography
Shakiba Moradi, Azin Alizadehasl, Jan Dhooge, Isaac Shiri, Niki Oveisi, Mehrdad Oveisi, Majid Maleki, Mostafa Ghelich-Oghli
http://arxiv.org/abs/1906.10486v1
• [eess.SP]Complex Signal Denoising and Interference Mitigation for Automotive Radar Using Convolutional Neural Networks
Johanna Rock, Mate Toth, Elmar Messner, Paul Meissner, Franz Pernkopf
http://arxiv.org/abs/1906.10044v2
• [eess.SP]Deep Neural Network Based Resource Allocation for V2X Communications
Jin Gao, Muhammad R. A. Khandaker, Faisal Tariq, Kai-Kit Wong, Risala T. Khan
http://arxiv.org/abs/1906.10194v1
• [eess.SP]Optimal Least-Squares Estimator and Precoder for Energy Beamforming over IQ-Impaired Channels
Deepak Mishra, Håkan Johansson
http://arxiv.org/abs/1906.10181v1
• [eess.SY]Keep soft robots soft — a data-driven based trade-off between feed-forward and feedback control
Thomas Beckers, Sandra Hirche
http://arxiv.org/abs/1906.10489v1
• [eess.SY]ReachNN: Reachability Analysis of Neural-Network Controlled Systems
Chao Huang, Jiameng Fan, Wenchao Li, Xin Chen, Qi Zhu
http://arxiv.org/abs/1906.10654v1
• [eess.SY]Trajectory Generation for UAVs in Unknown Environments with Extreme Wind Disturbances
Kenan Cole, Adam M. Wickenheiser
http://arxiv.org/abs/1906.09508v1
• [math.NA]Advances in Implementation, Theoretical Motivation, and Numerical Results for the Nested Iteration with Range Decomposition Algorithm
Wayne Mitchell, Tom Manteuffel
http://arxiv.org/abs/1906.10613v1
• [math.NA]Comments on the article “A Bayesian conjugate gradient method”
T. J. Sullivan
http://arxiv.org/abs/1906.10240v1
• [math.OC]A Stochastic Composite Gradient Method with Incremental Variance Reduction
Junyu Zhang, Lin Xiao
http://arxiv.org/abs/1906.10186v1
• [math.OC]Complexity of Highly Parallel Non-Smooth Convex Optimization
Sébastien Bubeck, Qijia Jiang, Yin Tat Lee, Yuanzhi Li, Aaron Sidford
http://arxiv.org/abs/1906.10655v1
• [math.OC]Riemannian optimization on the simplex of positive definite matrices
Bamdev Mishra, Hiroyuki Kasai, Pratik Jawanpuria
http://arxiv.org/abs/1906.10436v1
• [math.ST]A note on locally optimal designs for generalized linear models with restricted support
Osama Idais
http://arxiv.org/abs/1906.10125v1
• [math.ST]Approximate separability of symmetrically penalized least squares in high dimensions: characterization and consequences
Michael Celentano
http://arxiv.org/abs/1906.10319v1
• [math.ST]Distribution-robust mean estimation via smoothed random perturbations
Matthew J. Holland
http://arxiv.org/abs/1906.10300v1
• [math.ST]Refinements of the Kiefer-Wolfowitz Theorem and a Test of Concavity
Zheng Fang
http://arxiv.org/abs/1906.10305v1
• [math.ST]Regression medians and uniqueness
Yijun Zuo
http://arxiv.org/abs/1906.10461v1
• [math.ST]Uniformly consistently estimating the proportion of false null hypotheses for composite null hypotheses via Lebesgue-Stieltjes integral equations
Xiongzhi Chen
http://arxiv.org/abs/1906.10246v1
• [physics.comp-ph]A unified sparse optimization framework to learn parsimonious physics-informed models from data
Kathleen Champion, Peng Zheng, Aleksandr Y. Aravkin, Steven L. Brunton, J. Nathan Kutz
http://arxiv.org/abs/1906.10612v1
• [physics.soc-ph]Link Prediction in Real-World Multiplex Networks via Layer Reconstruction Method
Amir Mahdi Abdolhosseini-Qomi, Seyed Hossein Jafari, Amirheckmat Taghizadeh, Naser Yazdani, Masoud Asadpour, Masoud Rahgozar
http://arxiv.org/abs/1906.09422v1
• [q-fin.ST]Hybrid symbiotic organisms search feedforward neural net-works model for stock price prediction
Bradley J. Pillay, Absalom E. Ezugwu
http://arxiv.org/abs/1906.10121v1
• [stat.AP]Assessing the Validity of a a priori Patient-Trial Generalizability Score using Real-world Data from a Large Clinical Data Research Network: A Colorectal Cancer Clinical Trial Case Study
Qian Li, Zhe He, Yi Guo, Hansi Zhang, Thomas J George Jr, William Hogan, Neil Charness, Jiang Bian
http://arxiv.org/abs/1906.10163v1
• [stat.AP]Forecasting the Remittances of the Overseas Filipino Workers in the Philippines
Merry Christ E. Manayaga, Roel F. Ceballos
http://arxiv.org/abs/1906.10422v1
• [stat.AP]New approach for stochastic downscaling and bias correction of daily mean temperatures to a high-resolution grid
Qifen Yuan, Thordis Thorarinsdottir, Stein Beldring, Wai Kwok Wong, Shaochun Huang, Chong-Yu Xu
http://arxiv.org/abs/1906.10464v1
• [stat.AP]Simultaneous Variable Selection, Clustering, and Smoothing in Function on Scalar Regression
Suchit Mehrotra, Arnab Maity
http://arxiv.org/abs/1906.10286v1
• [stat.ME]An Interval Estimation Approach to Selection Bias in Observational Studies
Matthew Tudball, Rachael Hughes, Kate Tilling, Qingyuan Zhao, Jack Bowden
http://arxiv.org/abs/1906.10159v1
• [stat.ME]Bayesian Nonparametric Clustering of Continuous-Time Hidden Markov Models for Health Trajectories
Yu Luo, David A. Stephens, David L. Buckeridge
http://arxiv.org/abs/1906.10252v1
• [stat.ME]Bayesian influence diagnostics and outlier detection for meta-analysis of diagnostic test accuracy
Yuki Matsushima, Hisashi Noma, Tomohide Yamada, Toshi A. Furukawa
http://arxiv.org/abs/1906.10445v1
• [stat.ME]Dynamic time series clustering via volatility change-points
Nick Whiteley
http://arxiv.org/abs/1906.10372v1
• [stat.ME]Parametric versus Semi and Nonparametric Regression Models
Hamdy F. F. Mahmoud
http://arxiv.org/abs/1906.10221v1
• [stat.ME]Spatial 3D Matérn priors for fast whole-brain fMRI analysis
Per Sidén, Finn Lindgren, David Bolin, Anders Eklund, Mattias Villani
http://arxiv.org/abs/1906.10591v1
• [stat.ME]The Power of Unbiased Recursive Partitioning: A Unifying View of CTree, MOB, and GUIDE
Lisa Schlosser, Torsten Hothorn, Achim Zeileis
http://arxiv.org/abs/1906.10179v1
• [stat.ML]A Self-supervised Approach to Hierarchical Forecasting with Applications to Groupwise Synthetic Controls
Konstantin Mishchenko, Mallory Montgomery, Federico Vaggi
http://arxiv.org/abs/1906.10586v1
• [stat.ML]AMF: Aggregated Mondrian Forests for Online Learning
Jaouad Mourtada, Stéphane Gaïffas, Erwan Scornet
http://arxiv.org/abs/1906.10529v1
• [stat.ML]Certifiably Optimal Sparse Inverse Covariance Estimation
Dimitris Bertsimas, Jourdain Lamperski, Jean Pauphilet
http://arxiv.org/abs/1906.10283v1
• [stat.ML]Coding for Crowdsourced Classification with XOR Queries
James, Pang, Hessam Mahdavifar, S. Sandeep Pradhan
http://arxiv.org/abs/1906.10637v1
• [stat.ML]From Non-Paying to Premium: Predicting User Conversion in Video Games with Ensemble Learning
Anna Guitart, Shi Hui Tan, Ana Fernández del Río, Pei Pei Chen, África Periáñez
http://arxiv.org/abs/1906.10320v1
• [stat.ML]Learning Fair and Transferable Representations
Luca Oneto, Michele Donini, Andreas Maurer, Massimiliano Pontil
http://arxiv.org/abs/1906.10673v1
• [stat.ML]Monte Carlo Gradient Estimation in Machine Learning
Shakir Mohamed, Mihaela Rosca, Michael Figurnov, Andriy Mnih
http://arxiv.org/abs/1906.10652v1
• [stat.ML]Non-Asymptotic Pure Exploration by Solving Games
Rémy Degenne, Wouter M. Koolen, Pierre Ménard
http://arxiv.org/abs/1906.10431v1
• [stat.ML]Res-embedding for Deep Learning Based Click-Through Rate Prediction Modeling
Guorui Zhou, Kailun Wu, Weijie Bian, Zhao Yang, Xiaoqiang Zhu, Kun Gai
http://arxiv.org/abs/1906.10304v1
• [stat.ML]Restless dependent bandits with fading memory
Oleksandr Zadorozhnyi, Gilles Blanchard, Alexandra Carpentier
http://arxiv.org/abs/1906.10454v1
• [stat.ML]Spectral Properties of Radial Kernels and Clustering in High Dimensions
David Cohen-Steiner, Alba Chiara de Vitis
http://arxiv.org/abs/1906.10583v1
• [stat.OT]A Role for Symmetry in the Bayesian Solution of Differential Equations
Junyang Wang, Jon Cockayne, Chris J. Oates
http://arxiv.org/abs/1906.10564v1
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