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.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.MA - 多代理系统 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.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 math.AG - 代数几何 math.NA - 数值分析 math.OC - 优化与控制 math.ST - 统计理论 physics.flu-dyn - 流体动力学 physics.soc-ph - 物理学与社会 q-bio.NC - 神经元与认知 q-bio.QM - 定量方法 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [astro-ph.IM]LEO-Py: Estimating likelihoods for correlated, censored, and uncertain data with given marginal distributions
    • [cs.AI]Artificial Intelligence: Powering Human Exploration of the Moon and Mars
    • [cs.AI]Designing Trustworthy AI: A Human-Machine Teaming Framework to Guide Development
    • [cs.AI]Detecting AI Trojans Using Meta Neural Analysis
    • [cs.AI]Tactical Reward Shaping: Bypassing Reinforcement Learning with Strategy-Based Goals
    • [cs.CL]Aligning Multilingual Word Embeddings for Cross-Modal Retrieval Task
    • [cs.CL]An Interactive Machine Translation Framework for Modernizing Historical Documents
    • [cs.CL]CONAN — COunter NArratives through Nichesourcing: a Multilingual Dataset of Responses to Fight Online Hate Speech
    • [cs.CL]Capturing Argument Interaction in Semantic Role Labeling with Capsule Networks
    • [cs.CL]Federated Learning of N-gram Language Models
    • [cs.CL]Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking
    • [cs.CL]Generating Highly Relevant Questions
    • [cs.CL]Gunrock: A Social Bot for Complex and Engaging Long Conversations
    • [cs.CL]Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back Translation
    • [cs.CL]In Search for Linear Relations in Sentence Embedding Spaces
    • [cs.CL]Linguistically Informed Relation Extraction and Neural Architectures for Nested Named Entity Recognition in BioNLP-OST 2019
    • [cs.CL]Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations
    • [cs.CL]Neural Language Priors
    • [cs.CL]One-To-Many Multilingual End-to-end Speech Translation
    • [cs.CL]Overcoming the Rare Word Problem for Low-Resource Language Pairs in Neural Machine Translation
    • [cs.CL]Riposte! A Large Corpus of Counter-Arguments
    • [cs.CL]SentiCite: An Approach for Publication Sentiment Analysis
    • [cs.CL]SesameBERT: Attention for Anywhere
    • [cs.CL]Text Level Graph Neural Network for Text Classification
    • [cs.CL]When Specialization Helps: Using Pooled Contextualized Embeddings to Detect Chemical and Biomedical Entities in Spanish
    • [cs.CR]A Distributed Ledger Based Infrastructure for Smart Transportation System and Social Good
    • [cs.CV]A Study on Wrist Identification for Forensic Investigation
    • [cs.CV]ATFaceGAN: Single Face Image Restoration and Recognition from Atmospheric Turbulence
    • [cs.CV]Deep Multiphase Level Set for Scene Parsing
    • [cs.CV]Defective samples simulation through Neural Style Transfer for automatic surface defect segment
    • [cs.CV]DexPilot: Vision Based Teleoperation of Dexterous Robotic Hand-Arm System
    • [cs.CV]Dynamic Mode Decomposition based feature for Image Classification
    • [cs.CV]ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
    • [cs.CV]Eyenet: Attention based Convolutional Encoder-Decoder Network for Eye Region Segmentation
    • [cs.CV]GetNet: Get Target Area for Image Pairing
    • [cs.CV]Identifying Candidate Spaces for Advert Implantation
    • [cs.CV]Improving Map Re-localization with Deep ‘Movable’ Objects Segmentation on 3D LiDAR Point Clouds
    • [cs.CV]Leveraging Vision Reconstruction Pipelines for Satellite Imagery
    • [cs.CV]Meta Module Network for Compositional Visual Reasoning
    • [cs.CV]Metric Pose Estimation for Human-Machine Interaction Using Monocular Vision
    • [cs.CV]Modulated Self-attention Convolutional Network for VQA
    • [cs.CV]Multi-Source Domain Adaptation and Semi-Supervised Domain Adaptation with Focus on Visual Domain Adaptation Challenge 2019
    • [cs.CV]Object-centric Forward Modeling for Model Predictive Control
    • [cs.CV]Real-time processing of high resolution video and 3D model-based tracking in remote tower operations
    • [cs.CV]Refining 6D Object Pose Predictions using Abstract Render-and-Compare
    • [cs.CV]SMArT: Training Shallow Memory-aware Transformers for Robotic Explainability
    • [cs.CV]Self-Paced Deep Regression Forests for Facial Age Estimation
    • [cs.CV]Semi Few-Shot Attribute Translation
    • [cs.CV]Sky pixel detection in outdoor imagery using an adaptive algorithm and machine learning
    • [cs.CV]The ‘Paris-end’ of town? Urban typology through machine learning
    • [cs.CV]TraffickCam: Explainable Image Matching For Sex Trafficking Investigations
    • [cs.CV]When Does Self-supervision Improve Few-shot Learning?
    • [cs.CV]xYOLO: A Model For Real-Time Object Detection In Humanoid Soccer On Low-End Hardware
    • [cs.CY]Online Surveys and Digital Demography in the Developing World: Facebook Users in Kenya
    • [cs.CY]Voice for the Voiceless: Active Sampling to Detect Comments Supporting the Rohingyas
    • [cs.DB]Rekall: Specifying Video Events using Compositions of Spatiotemporal Labels
    • [cs.DB]The Query Translation Landscape: a Survey
    • [cs.DC]ABEONA: an Architecture for Energy-Aware Task Migrations from the Edge to the Cloud
    • [cs.DC]Active-Code Replacement in the OODIDA Data Analytics Platform
    • [cs.DC]An XML-based Factory Description Language for Smart Manufacturing Plants in Industry 4.0
    • [cs.DC]Impact of Inference Accelerators on hardware selection
    • [cs.DC]Integrated Process Planning and Scheduling in Commercial Smart Kitchens
    • [cs.DC]IoTSim-Edge: A Simulation Framework for Modeling the Behaviour of IoT and Edge Computing Environments
    • [cs.DC]Parallel computational optimization in operations research: A new integrative framework, literature review and research directions
    • [cs.DC]Provenance tracking in the LHCb software
    • [cs.DC]Task-Adaptive Incremental Learning for Intelligent Edge Devices
    • [cs.IR]Accurate and Fast Retrieval for Complex Non-metric Data via Neighborhood Graphs
    • [cs.IR]Conceptualize and Infer User Needs in E-commerce
    • [cs.IR]Look before you Hop: Conversational Question Answering over Knowledge Graphs Using Judicious Context Expansion
    • [cs.IR]Pruning Algorithms for Low-Dimensional Non-metric k-NN Search: A Case Study
    • [cs.IT]An Information-theoretic Approach to Unsupervised Feature Selection for High-Dimensional Data
    • [cs.IT]Constructions of MDS Euclidean Self-dual Codes from small length
    • [cs.IT]Timely Distributed Computation with Stragglers
    • [cs.LG]A Machine Learning Model for Long-Term Power Generation Forecasting at Bidding Zone Level
    • [cs.LG]ATL: Autonomous Knowledge Transfer from Many Streaming Processes
    • [cs.LG]Accelerating Federated Learning via Momentum Gradient Descent
    • [cs.LG]Auto-Rotating Perceptrons
    • [cs.LG]Automatic Construction of Multi-layer Perceptron Network from Streaming Examples
    • [cs.LG]Beyond Vector Spaces: Compact Data Representationas Differentiable Weighted Graphs
    • [cs.LG]Can We Distinguish Machine Learning from Human Learning?
    • [cs.LG]Combining No-regret and Q-learning
    • [cs.LG]Credible Sample Elicitation by Deep Learning, for Deep Learning
    • [cs.LG]Deep Network classification by Scattering and Homotopy dictionary learning
    • [cs.LG]Deep Value Model Predictive Control
    • [cs.LG]DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators
    • [cs.LG]Differentiable Sparsification for Deep Neural Networks
    • [cs.LG]Differentially private anonymized histograms
    • [cs.LG]Directional Adversarial Training for Cost Sensitive Deep Learning Classification Applications
    • [cs.LG]Energy-Aware Neural Architecture Optimization with Fast Splitting Steepest Descent
    • [cs.LG]Evaluating Scalable Uncertainty Estimation Methods for DNN-Based Molecular Property Prediction
    • [cs.LG]Generating valid Euclidean distance matrices
    • [cs.LG]Graph Few-shot Learning via Knowledge Transfer
    • [cs.LG]High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes
    • [cs.LG]Improved Regret Bounds for Projection-free Bandit Convex Optimization
    • [cs.LG]Inferring Dynamical Systems with Long-Range Dependencies through Line Attractor Regularization
    • [cs.LG]Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?
    • [cs.LG]Kernel-based Approach to Handle Mixed Data for Inferring Causal Graphs
    • [cs.LG]Learning event representations in image sequences by dynamic graph embedding
    • [cs.LG]MIM: Mutual Information Machine
    • [cs.LG]NGBoost: Natural Gradient Boosting for Probabilistic Prediction
    • [cs.LG]On the Interpretability and Evaluation of Graph Representation Learning
    • [cs.LG]Operational Calibration: Debugging Confidence Errors for DNNs in the Field
    • [cs.LG]Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates
    • [cs.LG]Random forest model identifies serve strength as a key predictor of tennis match outcome
    • [cs.LG]Read, Highlight and Summarize: A Hierarchical Neural Semantic Encoder-based Approach
    • [cs.LG]Self-Paced Multi-Label Learning with Diversity
    • [cs.LG]Sequence embeddings help to identify fraudulent cases in healthcare insurance
    • [cs.LG]Stochastic Optimal Control as Approximate Input Inference
    • [cs.LG]TorchBeast: A PyTorch Platform for Distributed RL
    • [cs.MA]Decentralized Multi-Agent Actor-Critic with Generative Inference
    • [cs.MA]Multi-Robot Coordinated Planning in Confined Environments under Kinematic Constraints
    • [cs.NE]Research on the Concept of Liquid State Machine
    • [cs.NI]Fast Session Resumption in DTLS for Mobile Communications
    • [cs.RO]A Review of Soft Robots
    • [cs.RO]Advanced Autonomy on a Low-Cost Educational Drone Platform
    • [cs.RO]CRANE: A highly dexterous needle placement robot for evaluation of interventional radiology procedures
    • [cs.RO]Force Field Generalization and the Internal Representation of Motor Learning
    • [cs.RO]Improvements to Target-Based 3D LiDAR to Camera Calibration
    • [cs.RO]Learning Parametric Constraints in High Dimensions from Demonstrations
    • [cs.RO]Model-based Behavioral Cloning with Future Image Similarity Learning
    • [cs.RO]Motion Generation Considering Situation with Conditional Generative Adversarial Networks for Throwing Robots
    • [cs.RO]Riemannian Motion Policy Fusion through Learnable Lyapunov Function Reshaping
    • [cs.RO]Toward Synergic Learning for Autonomous Manipulation of Deformable Tissues via Surgical Robots: An Approximate Q-Learning Approach
    • [cs.SI]Describing Alt-Right communities and their discourse on Twitter during the 2018 US mid-term elections
    • [econ.EM]Application of Machine Learning in Forecasting International Trade Trends
    • [econ.EM]Boosting High Dimensional Predictive Regressions with Time Varying Parameters
    • [eess.IV]CeliacNet: Celiac Disease Severity Diagnosis on Duodenal Histopathological Images Using Deep Residual Networks
    • [eess.IV]Lossy Image Compression with Recurrent Neural Networks: from Human Perceived Visual Quality to Classification Accuracy
    • [eess.IV]Lung nodule segmentation via level set machine learning
    • [math.AG]Computational complexity in algebraic regression
    • [math.NA]Implicit Neural Solver for Time-dependent Linear PDEs with Convergence Guarantee
    • [math.NA]Optimizing Geometric Multigrid Methods with Evolutionary Computation
    • [math.OC]Integrated Optimization of Ascent Trajectory and SRM Design of Multistage Launch Vehicles
    • [math.OC]On Polyhedral and Second-Order-Cone Decompositions of Semidefinite Optimization Problems
    • [math.ST]Bregman-divergence-guided Legendre exponential dispersion model with finite cumulants (K-LED)
    • [math.ST]Identifying causal effects in maximally oriented partially directed acyclic graphs
    • [math.ST]Nonparametric principal subspace regression
    • [math.ST]The density ratio of generalized binomial versus Poisson distributions
    • [physics.flu-dyn]Generalization of machine-learned turbulent heat flux models applied to film cooling flows
    • [physics.soc-ph]The Nature of Human Settlement: Building an understanding of high performance city design
    • [q-bio.NC]Analysis of an Automated Machine Learning Approach in Brain Predictive Modelling: A data-driven approach to Predict Brain Age from Cortical Anatomical Measures
    • [q-bio.QM]A Pan-Cancer and Polygenic Bayesian Hierarchical Model for the Effect of Somatic Mutations on Survival
    • [q-bio.QM]Joint analysis of clinical risk factors and 4D cardiac motion for survival prediction using a hybrid deep learning network
    • [q-bio.QM]Stochastic modeling of hyposmotic lysis and characterization of different osmotic stability subgroups of human erythrocytes
    • [stat.AP]A direct approach to detection and attribution of climate change
    • [stat.AP]Simulation of land use dynamics in Paragominas-PA: differences in spatial rules between smallholdings and agribusiness areas
    • [stat.ME]A Distributed and Integrated Method of Moments for High-Dimensional Correlated Data Analysis
    • [stat.ME]Accelerating Bayesian inference in hydrological modeling with a mechanistic emulator
    • [stat.ME]Causal Inference for Comprehensive Cohort Studies
    • [stat.ME]Combining Biomarkers by Maximizing the True Positive Rate for a Fixed False Positive Rate
    • [stat.ME]Gaussian Process Assisted Active Learning of Physical Laws
    • [stat.ME]Inhomogeneous higher-order summary statistics for linear network point processes
    • [stat.ME]Inverse Probability Weighted Estimators of Vaccine Effects Accommodating Partial Interference and Censoring
    • [stat.ME]Partial Separability and Functional Graphical Models for Multivariate Gaussian Processes
    • [stat.ME]Perturbed factor analysis: Improving generalizability across studies
    • [stat.ME]SIMPCA: A framework for rotating and sparsifying principal components
    • [stat.ML]Universal Approximation Theorems

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    • [astro-ph.IM]LEO-Py: Estimating likelihoods for correlated, censored, and uncertain data with given marginal distributions
    R. Feldmann
    http://arxiv.org/abs/1910.02958v1

    • [cs.AI]Artificial Intelligence: Powering Human Exploration of the Moon and Mars
    Jeremy D. Frank
    http://arxiv.org/abs/1910.03014v1

    • [cs.AI]Designing Trustworthy AI: A Human-Machine Teaming Framework to Guide Development
    Carol J. Smith
    http://arxiv.org/abs/1910.03515v1

    • [cs.AI]Detecting AI Trojans Using Meta Neural Analysis
    Xiaojun Xu, Qi Wang, Huichen Li, Nikita Borisov, Carl A. Gunter, Bo Li
    http://arxiv.org/abs/1910.03137v1

    • [cs.AI]Tactical Reward Shaping: Bypassing Reinforcement Learning with Strategy-Based Goals
    Yizheng Zhang, Andre Rosendo
    http://arxiv.org/abs/1910.03144v1

    • [cs.CL]Aligning Multilingual Word Embeddings for Cross-Modal Retrieval Task
    Alireza Mohammadshahi, Remi Lebret, Karl Aberer
    http://arxiv.org/abs/1910.03291v1

    • [cs.CL]An Interactive Machine Translation Framework for Modernizing Historical Documents
    Miguel Domingo, Francisco Casacuberta
    http://arxiv.org/abs/1910.03355v1

    • [cs.CL]CONAN — COunter NArratives through Nichesourcing: a Multilingual Dataset of Responses to Fight Online Hate Speech
    Y. L. Chung, E. Kuzmenko, S. S. Tekiroglu, M. Guerini
    http://arxiv.org/abs/1910.03270v1

    • [cs.CL]Capturing Argument Interaction in Semantic Role Labeling with Capsule Networks
    Xinchi Chen, Chunchuan Lyu, Ivan Titov
    http://arxiv.org/abs/1910.03136v1

    • [cs.CL]Federated Learning of N-gram Language Models
    Mingqing Chen, Ananda Theertha Suresh, Rajiv Mathews, Adeline Wong, Cyril Allauzen, Françoise Beaufays, Michael Riley
    http://arxiv.org/abs/1910.03432v1

    • [cs.CL]Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking
    Jian-Guo Zhang, Kazuma Hashimoto, Chien-Sheng Wu, Yao Wan, Philip S. Yu, Richard Socher, Caiming Xiong
    http://arxiv.org/abs/1910.03544v1

    • [cs.CL]Generating Highly Relevant Questions
    Jiazuo Qiu, Deyi Xiong
    http://arxiv.org/abs/1910.03401v1

    • [cs.CL]Gunrock: A Social Bot for Complex and Engaging Long Conversations
    Dian Yu, Michelle Cohn, Yi Mang Yang, Chun-Yen Chen, Weiming Wen, Jiaping Zhang, Mingyang Zhou, Kevin Jesse, Austin Chau, Antara Bhowmick, Shreenath Iyer, Giritheja Sreenivasulu, Sam Davidson, Ashwin Bhandare, Zhou Yu
    http://arxiv.org/abs/1910.03042v1

    • [cs.CL]Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back Translation
    Zhenhao Li, Lucia Specia
    http://arxiv.org/abs/1910.03009v1

    • [cs.CL]In Search for Linear Relations in Sentence Embedding Spaces
    Petra Barančíková, Ondřej Bojar
    http://arxiv.org/abs/1910.03375v1

    • [cs.CL]Linguistically Informed Relation Extraction and Neural Architectures for Nested Named Entity Recognition in BioNLP-OST 2019
    Usama Yaseen, Pankaj Gupta, Hinrich Schütze
    http://arxiv.org/abs/1910.03385v1

    • [cs.CL]Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations
    Camburu Oana-Maria, Shillingford Brendan, Minervini Pasquale, Lukasiewicz Thomas, Blunsom Phil
    http://arxiv.org/abs/1910.03065v1

    • [cs.CL]Neural Language Priors
    Joseph Enguehard, Dan Busbridge, Vitalii Zhelezniak, Nils Hammerla
    http://arxiv.org/abs/1910.03492v1

    • [cs.CL]One-To-Many Multilingual End-to-end Speech Translation
    Mattia Antonino Di Gangi, Matteo Negri, Marco Turchi
    http://arxiv.org/abs/1910.03320v1

    • [cs.CL]Overcoming the Rare Word Problem for Low-Resource Language Pairs in Neural Machine Translation
    Thi-Vinh Ngo, Thanh-Le Ha, Phuong-Thai Nguyen, Le-Minh Nguyen
    http://arxiv.org/abs/1910.03467v1

    • [cs.CL]Riposte! A Large Corpus of Counter-Arguments
    Paul Reisert, Benjamin Heinzerling, Naoya Inoue, Shun Kiyono, Kentaro Inui
    http://arxiv.org/abs/1910.03246v1

    • [cs.CL]SentiCite: An Approach for Publication Sentiment Analysis
    Dominique Mercier, Akansha Bhardwaj, Andreas Dengel, Sheraz Ahmed
    http://arxiv.org/abs/1910.03498v1

    • [cs.CL]SesameBERT: Attention for Anywhere
    Ta-Chun Su, Hsiang-Chih Cheng
    http://arxiv.org/abs/1910.03176v1

    • [cs.CL]Text Level Graph Neural Network for Text Classification
    Lianzhe Huang, Dehong Ma, Sujian Li, Xiaodong Zhang, Houfeng WANG
    http://arxiv.org/abs/1910.02356v2

    • [cs.CL]When Specialization Helps: Using Pooled Contextualized Embeddings to Detect Chemical and Biomedical Entities in Spanish
    Manuel Stoeckel, Wahed Hemati, Alexander Mehler
    http://arxiv.org/abs/1910.03387v1

    • [cs.CR]A Distributed Ledger Based Infrastructure for Smart Transportation System and Social Good
    Mirko Zichichi, Stefano Ferretti, Gabriele D’Angelo
    http://arxiv.org/abs/1910.03280v1

    • [cs.CV]A Study on Wrist Identification for Forensic Investigation
    Wojciech Michal Matkowski, Frodo Kin Sun Chan, Adams Wai Kin Kong
    http://arxiv.org/abs/1910.03213v1

    • [cs.CV]ATFaceGAN: Single Face Image Restoration and Recognition from Atmospheric Turbulence
    Chun Pong Lau, Hossein Souri, Rama Chellappa
    http://arxiv.org/abs/1910.03119v1

    • [cs.CV]Deep Multiphase Level Set for Scene Parsing
    Pingping Zhang, Wei Liu, Yinjie Lei, Chunhua Shen, Huchuan Lu
    http://arxiv.org/abs/1910.03166v1

    • [cs.CV]Defective samples simulation through Neural Style Transfer for automatic surface defect segment
    Taoran Wei, Danhua Cao, Xingru Jiang, Caiyun Zheng, Lizhe Liu
    http://arxiv.org/abs/1910.03334v1

    • [cs.CV]DexPilot: Vision Based Teleoperation of Dexterous Robotic Hand-Arm System
    Ankur Handa, Karl Van Wyk, Wei Yang, Jacky Liang, Yu-Wei Chao, Qian Wan, Stan Birchfield, Nathan Ratliff, Dieter Fox
    http://arxiv.org/abs/1910.03135v1

    • [cs.CV]Dynamic Mode Decomposition based feature for Image Classification
    Rahul-Vigneswaran K, Sachin-Kumar S, Neethu Mohan, Soman KP
    http://arxiv.org/abs/1910.03188v1

    • [cs.CV]ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
    Qilong Wang, Banggu Wu, Pengfei Zhu, Peihua Li, Wangmeng Zuo, Qinghua Hu
    http://arxiv.org/abs/1910.03151v1

    • [cs.CV]Eyenet: Attention based Convolutional Encoder-Decoder Network for Eye Region Segmentation
    Priya Kansal, Sabari Nathan
    http://arxiv.org/abs/1910.03274v1

    • [cs.CV]GetNet: Get Target Area for Image Pairing
    Henry H. Yu, Jiang Liu, Hao Sun, Ziwen Wang, Haotian Zhang
    http://arxiv.org/abs/1910.03152v1

    • [cs.CV]Identifying Candidate Spaces for Advert Implantation
    Soumyabrata Dev, Hossein Javidnia, Murhaf Hossari, Matthew Nicholson, Killian McCabe, Atul Nautiyal, Clare Conran, Jian Tang, Wei Xu, François Pitié
    http://arxiv.org/abs/1910.03227v1

    • [cs.CV]Improving Map Re-localization with Deep ‘Movable’ Objects Segmentation on 3D LiDAR Point Clouds
    Victor Vaquero, Kai Fischer, Francesc Moreno-Noguer, Alberto Sanfeliu, Stefan Milz
    http://arxiv.org/abs/1910.03336v1

    • [cs.CV]Leveraging Vision Reconstruction Pipelines for Satellite Imagery
    Kai Zhang, Noah Snavely, Jin Sun
    http://arxiv.org/abs/1910.02989v1

    • [cs.CV]Meta Module Network for Compositional Visual Reasoning
    Wenhu Chen, Zhe Gan, Linjie Li, Yu Cheng, William Wang, Jingjing Liu
    http://arxiv.org/abs/1910.03230v1

    • [cs.CV]Metric Pose Estimation for Human-Machine Interaction Using Monocular Vision
    Christoph Heindl, Markus Ikeda, Gernot Stübl, Andreas Pichler, Josef Scharinger
    http://arxiv.org/abs/1910.03239v1

    • [cs.CV]Modulated Self-attention Convolutional Network for VQA
    Jean-Benoit Delbrouck, Antoine Maiorca, Nathan Hubens, Stéphane Dupont
    http://arxiv.org/abs/1910.03343v1

    • [cs.CV]Multi-Source Domain Adaptation and Semi-Supervised Domain Adaptation with Focus on Visual Domain Adaptation Challenge 2019
    Yingwei Pan, Yehao Li, Qi Cai, Yang Chen, Ting Yao
    http://arxiv.org/abs/1910.03548v1

    • [cs.CV]Object-centric Forward Modeling for Model Predictive Control
    Yufei Ye, Dhiraj Gandhi, Abhinav Gupta, Shubham Tulsiani
    http://arxiv.org/abs/1910.03568v1

    • [cs.CV]Real-time processing of high resolution video and 3D model-based tracking in remote tower operations
    Oliver J. D. Barrowclough, Sverre Briseid, Georg Muntingh, Torbjørn Viksand
    http://arxiv.org/abs/1910.03517v1

    • [cs.CV]Refining 6D Object Pose Predictions using Abstract Render-and-Compare
    Arul Selvam Periyasamy, Max Schwarz, Sven Behnke
    http://arxiv.org/abs/1910.03412v1

    • [cs.CV]SMArT: Training Shallow Memory-aware Transformers for Robotic Explainability
    Marcella Cornia, Lorenzo Baraldi, Rita Cucchiara
    http://arxiv.org/abs/1910.02974v1

    • [cs.CV]Self-Paced Deep Regression Forests for Facial Age Estimation
    Shijie Ai, Yazhou Ren, Lili Pan
    http://arxiv.org/abs/1910.03244v1

    • [cs.CV]Semi Few-Shot Attribute Translation
    Ricard Durall, Franz-Josef Pfreundt, Janis Keuper
    http://arxiv.org/abs/1910.03240v1

    • [cs.CV]Sky pixel detection in outdoor imagery using an adaptive algorithm and machine learning
    Kerry A. Nice, Jasper S. Wijnands, Ariane Middel, Jingcheng Wang, Yiming Qiu, Nan Zhao, Jason Thompson, Gideon D. P. A. Aschwanden, Haifeng Zhao, Mark Stevenson
    http://arxiv.org/abs/1910.03182v1

    • [cs.CV]The ‘Paris-end’ of town? Urban typology through machine learning
    Kerry A. Nice, Jason Thompson, Jasper S. Wijnands, Gideon D. P. A. Aschwanden, Mark Stevenson
    http://arxiv.org/abs/1910.03220v1

    • [cs.CV]TraffickCam: Explainable Image Matching For Sex Trafficking Investigations
    Abby Stylianou, Richard Souvenir, Robert Pless
    http://arxiv.org/abs/1910.03455v1

    • [cs.CV]When Does Self-supervision Improve Few-shot Learning?
    Jong-Chyi Su, Subhransu Maji, Bharath Hariharan
    http://arxiv.org/abs/1910.03560v1

    • [cs.CV]xYOLO: A Model For Real-Time Object Detection In Humanoid Soccer On Low-End Hardware
    Daniel Barry, Munir Shah, Merel Keijsers, Humayun Khan, Banon Hopman
    http://arxiv.org/abs/1910.03159v1

    • [cs.CY]Online Surveys and Digital Demography in the Developing World: Facebook Users in Kenya
    Katherine Hoffmann Pham, Francesco Rampazzo, Leah R. Rosenzweig
    http://arxiv.org/abs/1910.03448v1

    • [cs.CY]Voice for the Voiceless: Active Sampling to Detect Comments Supporting the Rohingyas
    Shriphani Palakodety, Ashiqur R. KhudaBukhsh, Jaime G. Carbonell
    http://arxiv.org/abs/1910.03206v1

    • [cs.DB]Rekall: Specifying Video Events using Compositions of Spatiotemporal Labels
    Daniel Y. Fu, Will Crichton, James Hong, Xinwei Yao, Haotian Zhang, Anh Truong, Avanika Narayan, Maneesh Agrawala, Christopher Ré, Kayvon Fatahalian
    http://arxiv.org/abs/1910.02993v1

    • [cs.DB]The Query Translation Landscape: a Survey
    Mohamed Nadjib Mami, Damien Graux, Harsh Thakkar, Simon Scerri, Sören Auer, Jens Lehmann
    http://arxiv.org/abs/1910.03118v1

    • [cs.DC]ABEONA: an Architecture for Energy-Aware Task Migrations from the Edge to the Cloud
    Isabelly Rocha, Gabriel Vinha, Andrey Brito, Pascal Felber, Marcelo Pasin, Valerio Schiavoni
    http://arxiv.org/abs/1910.03445v1

    • [cs.DC]Active-Code Replacement in the OODIDA Data Analytics Platform
    Gregor Ulm, Emil Gustavsson, Mats Jirstrand
    http://arxiv.org/abs/1910.03575v1

    • [cs.DC]An XML-based Factory Description Language for Smart Manufacturing Plants in Industry 4.0
    Shuai Zhao, Piotr Dziurzanski, Leandro Soares Indrusiak
    http://arxiv.org/abs/1910.03331v1

    • [cs.DC]Impact of Inference Accelerators on hardware selection
    Dibyajyoti Pati, Caroline Favart, Purujit Bahl, Vivek Soni, Yun-chan Tsai, Michael Potter, Jiahui Guan, Xiaomeng Dong, V. Ratna Saripalli
    http://arxiv.org/abs/1910.03060v1

    • [cs.DC]Integrated Process Planning and Scheduling in Commercial Smart Kitchens
    Piotr Dziurzanski, Shuai Zhao, Leandro Soares Indrusiak
    http://arxiv.org/abs/1910.03322v1

    • [cs.DC]IoTSim-Edge: A Simulation Framework for Modeling the Behaviour of IoT and Edge Computing Environments
    Devki Nandan Jha, Khaled Alwasel, Areeb Alshoshan, Xianghua Huang, Ranesh Kumar Naha, Sudheer Kumar Battula, Saurabh Garg, Deepak Puthal, Philip James, Albert Y. Zomaya, Schahram Dustdar, Rajiv Ranjan
    http://arxiv.org/abs/1910.03026v1

    • [cs.DC]Parallel computational optimization in operations research: A new integrative framework, literature review and research directions
    Guido Schryen
    http://arxiv.org/abs/1910.03028v1

    • [cs.DC]Provenance tracking in the LHCb software
    Ana Trisovic, Chris R. Jones, Ben Couturier, Marco Clemencic
    http://arxiv.org/abs/1910.02863v1

    • [cs.DC]Task-Adaptive Incremental Learning for Intelligent Edge Devices
    Zhuwei Qin, Fuxun Yu, Xiang Chen
    http://arxiv.org/abs/1910.03122v1

    • [cs.IR]Accurate and Fast Retrieval for Complex Non-metric Data via Neighborhood Graphs
    Leonid Boytsov, Eric Nyberg
    http://arxiv.org/abs/1910.03534v1

    • [cs.IR]Conceptualize and Infer User Needs in E-commerce
    Xusheng Luo, Yonghua Yang, Kenny Q. Zhu, Yu Gong, Keping Yang
    http://arxiv.org/abs/1910.03295v1

    • [cs.IR]Look before you Hop: Conversational Question Answering over Knowledge Graphs Using Judicious Context Expansion
    Philipp Christmann, Rishiraj Saha Roy, Abdalghani Abujabal, Jyotsna Singh, Gerhard Weikum
    http://arxiv.org/abs/1910.03262v1

    • [cs.IR]Pruning Algorithms for Low-Dimensional Non-metric k-NN Search: A Case Study
    Leonid Boytsov, Eric Nyberg
    http://arxiv.org/abs/1910.03539v1

    • [cs.IT]An Information-theoretic Approach to Unsupervised Feature Selection for High-Dimensional Data
    Shao-Lun Huang, Xiangxiang Xu, Lizhong Zheng
    http://arxiv.org/abs/1910.03196v1

    • [cs.IT]Constructions of MDS Euclidean Self-dual Codes from small length
    Derong Xie, Xiaolei Fang, Jinquan Luo
    http://arxiv.org/abs/1910.02255v2

    • [cs.IT]Timely Distributed Computation with Stragglers
    Baturalp Buyukates, Sennur Ulukus
    http://arxiv.org/abs/1910.03564v1

    • [cs.LG]A Machine Learning Model for Long-Term Power Generation Forecasting at Bidding Zone Level
    Michela Moschella, Mauro Tucci, Emanuele Crisostomi, Alessandro Betti
    http://arxiv.org/abs/1910.03276v1

    • [cs.LG]ATL: Autonomous Knowledge Transfer from Many Streaming Processes
    Mahardhika Pratama, Marcus de Carvalho, Renchunzi Xie, Edwin Lughofer, Jie Lu
    http://arxiv.org/abs/1910.03434v1

    • [cs.LG]Accelerating Federated Learning via Momentum Gradient Descent
    Wei Liu, Li Chen, Yunfei Chen, Wenyi Zhang
    http://arxiv.org/abs/1910.03197v1

    • [cs.LG]Auto-Rotating Perceptrons
    Daniel Saromo, Elizabeth Villota, Edwin Villanueva
    http://arxiv.org/abs/1910.02483v2

    • [cs.LG]Automatic Construction of Multi-layer Perceptron Network from Streaming Examples
    Mahardhika Pratama, Choiru Za’in, Andri Ashfahani, Yew Soon Ong, Weiping Ding
    http://arxiv.org/abs/1910.03437v1

    • [cs.LG]Beyond Vector Spaces: Compact Data Representationas Differentiable Weighted Graphs
    Denis Mazur, Vage Egiazarian, Stanislav Morozov, Artem Babenko
    http://arxiv.org/abs/1910.03524v1

    • [cs.LG]Can We Distinguish Machine Learning from Human Learning?
    Vicki Bier, Paul B. Kantor, Gary Lupyan, Xiaojin Zhu
    http://arxiv.org/abs/1910.03466v1

    • [cs.LG]Combining No-regret and Q-learning
    Ian A. Kash, Michael Sullins, Katja Hofmann
    http://arxiv.org/abs/1910.03094v1

    • [cs.LG]Credible Sample Elicitation by Deep Learning, for Deep Learning
    Yang Liu, Zuyue Fu, Zhuoran Yang, Zhaoran Wang
    http://arxiv.org/abs/1910.03155v1

    • [cs.LG]Deep Network classification by Scattering and Homotopy dictionary learning
    John Zarka, Louis Thiry, Tomás Angles, Stéphane Mallat
    http://arxiv.org/abs/1910.03561v1

    • [cs.LG]Deep Value Model Predictive Control
    Farbod Farshidian, David Hoeller, Marco Hutter
    http://arxiv.org/abs/1910.03358v1

    • [cs.LG]DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators
    Lu Lu, Pengzhan Jin, George Em Karniadakis
    http://arxiv.org/abs/1910.03193v1

    • [cs.LG]Differentiable Sparsification for Deep Neural Networks
    Yognjin Lee
    http://arxiv.org/abs/1910.03201v1

    • [cs.LG]Differentially private anonymized histograms
    Ananda Theertha Suresh
    http://arxiv.org/abs/1910.03553v1

    • [cs.LG]Directional Adversarial Training for Cost Sensitive Deep Learning Classification Applications
    Matteo Terzi, Gian Antonio Susto, Pratik Chaudhari
    http://arxiv.org/abs/1910.03468v1

    • [cs.LG]Energy-Aware Neural Architecture Optimization with Fast Splitting Steepest Descent
    Dilin Wang, Meng Li, Lemeng Wu, Vikas Chandra, Qiang Liu
    http://arxiv.org/abs/1910.03103v1

    • [cs.LG]Evaluating Scalable Uncertainty Estimation Methods for DNN-Based Molecular Property Prediction
    Gabriele Scalia, Colin A. Grambow, Barbara Pernici, Yi-Pei Li, William H. Green
    http://arxiv.org/abs/1910.03127v1

    • [cs.LG]Generating valid Euclidean distance matrices
    Moritz Hoffmann, Frank Noé
    http://arxiv.org/abs/1910.03131v1

    • [cs.LG]Graph Few-shot Learning via Knowledge Transfer
    Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li
    http://arxiv.org/abs/1910.03053v1

    • [cs.LG]High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes
    David Salinas, Michael Bohlke-Schneider, Laurent Callot, Roberto Medico, Jan Gasthaus
    http://arxiv.org/abs/1910.03002v1

    • [cs.LG]Improved Regret Bounds for Projection-free Bandit Convex Optimization
    Dan Garber, Ben Kretzu
    http://arxiv.org/abs/1910.03374v1

    • [cs.LG]Inferring Dynamical Systems with Long-Range Dependencies through Line Attractor Regularization
    Dominik Schmidt, Georgia Koppe, Max Beutelspacher, Daniel Durstewitz
    http://arxiv.org/abs/1910.03471v1

    • [cs.LG]Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?
    Simon S. Du, Sham M. Kakade, Ruosong Wang, Lin F. Yang
    http://arxiv.org/abs/1910.03016v1

    • [cs.LG]Kernel-based Approach to Handle Mixed Data for Inferring Causal Graphs
    Teny Handhayani, James Cussens
    http://arxiv.org/abs/1910.03055v1

    • [cs.LG]Learning event representations in image sequences by dynamic graph embedding
    Mariella Dimiccoli, Herwig Wendt
    http://arxiv.org/abs/1910.03483v1

    • [cs.LG]MIM: Mutual Information Machine
    Micha Livne, Kevin Swersky, David J. Fleet
    http://arxiv.org/abs/1910.03175v1

    • [cs.LG]NGBoost: Natural Gradient Boosting for Probabilistic Prediction
    Tony Duan, Anand Avati, Daisy Yi Ding, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler
    http://arxiv.org/abs/1910.03225v1

    • [cs.LG]On the Interpretability and Evaluation of Graph Representation Learning
    Antonia Gogoglou, C. Bayan Bruss, Keegan E. Hines
    http://arxiv.org/abs/1910.03081v1

    • [cs.LG]Operational Calibration: Debugging Confidence Errors for DNNs in the Field
    Zenan Li, Xiaoxing Ma, Chang Xu, Jingwei Xu, Chun Cao, Jian Lü
    http://arxiv.org/abs/1910.02352v1

    • [cs.LG]Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates
    Yang Liu, Hongyi Guo
    http://arxiv.org/abs/1910.03231v1

    • [cs.LG]Random forest model identifies serve strength as a key predictor of tennis match outcome
    Zijian Gao, Amanda Kowalczyk
    http://arxiv.org/abs/1910.03203v1

    • [cs.LG]Read, Highlight and Summarize: A Hierarchical Neural Semantic Encoder-based Approach
    Rajeev Bhatt Ambati, Saptarashmi Bandyopadhyay, Prasenjit Mitra
    http://arxiv.org/abs/1910.03177v1

    • [cs.LG]Self-Paced Multi-Label Learning with Diversity
    Seyed Amjad Seyedi, S. Siamak Ghodsi, Fardin Akhlaghian, Mahdi Jalili, Parham Moradi
    http://arxiv.org/abs/1910.03497v1

    • [cs.LG]Sequence embeddings help to identify fraudulent cases in healthcare insurance
    I. Fursov, A. Zaytsev, R. Khasyanov, M. Spindler, E. Burnaev
    http://arxiv.org/abs/1910.03072v1

    • [cs.LG]Stochastic Optimal Control as Approximate Input Inference
    Joe Watson, Hany Abdulsamad, Jan Peters
    http://arxiv.org/abs/1910.03003v1

    • [cs.LG]TorchBeast: A PyTorch Platform for Distributed RL
    Heinrich Küttler, Nantas Nardelli, Thibaut Lavril, Marco Selvatici, Viswanath Sivakumar, Tim Rocktäschel, Edward Grefenstette
    http://arxiv.org/abs/1910.03552v1

    • [cs.MA]Decentralized Multi-Agent Actor-Critic with Generative Inference
    Kevin Corder, Manuel M. Vindiola, Keith Decker
    http://arxiv.org/abs/1910.03058v1

    • [cs.MA]Multi-Robot Coordinated Planning in Confined Environments under Kinematic Constraints
    Clayton Mangette, Pratap Tokekar
    http://arxiv.org/abs/1910.03101v1

    • [cs.NE]Research on the Concept of Liquid State Machine
    Gideon Gbenga Oladipupo
    http://arxiv.org/abs/1910.03354v1

    • [cs.NI]Fast Session Resumption in DTLS for Mobile Communications
    Gyordan Caminati, Sara Kiade, Gabriele D’Angelo, Stefano Ferretti, Vittorio Ghini
    http://arxiv.org/abs/1910.03281v1

    • [cs.RO]A Review of Soft Robots
    Gideon Gbenga Oladipupo
    http://arxiv.org/abs/1910.03382v1

    • [cs.RO]Advanced Autonomy on a Low-Cost Educational Drone Platform
    Luke Eller, Theo Guerin, Baichuan Huang, Garrett Warren, Sophie Yang, Josh Roy, Stefanie Tellex
    http://arxiv.org/abs/1910.03516v1

    • [cs.RO]CRANE: A highly dexterous needle placement robot for evaluation of interventional radiology procedures
    Dimitri A. Schreiber, Hanpeng Jiang, Guosong Li, Julie Yu, Zhaowei Yu, Renjie Zhu, Alexander M. Norbash, Michael C. Yip
    http://arxiv.org/abs/1910.03063v1

    • [cs.RO]Force Field Generalization and the Internal Representation of Motor Learning
    Alireza Rezazadeh, Max Berniker
    http://arxiv.org/abs/1910.03087v1

    • [cs.RO]Improvements to Target-Based 3D LiDAR to Camera Calibration
    Jiunn-Kai Huang, Jessy W. Grizzle
    http://arxiv.org/abs/1910.03126v1

    • [cs.RO]Learning Parametric Constraints in High Dimensions from Demonstrations
    Glen Chou, Necmiye Ozay, Dmitry Berenson
    http://arxiv.org/abs/1910.03477v1

    • [cs.RO]Model-based Behavioral Cloning with Future Image Similarity Learning
    Alan Wu, AJ Piergiovanni, Michael S. Ryoo
    http://arxiv.org/abs/1910.03157v1

    • [cs.RO]Motion Generation Considering Situation with Conditional Generative Adversarial Networks for Throwing Robots
    Kyo Kutsuzawa, Hitoshi Kusano, Ayaka Kume, Shoichiro Yamaguchi
    http://arxiv.org/abs/1910.03253v1

    • [cs.RO]Riemannian Motion Policy Fusion through Learnable Lyapunov Function Reshaping
    Mustafa Mukadam, Ching-An Cheng, Dieter Fox, Byron Boots, Nathan Ratliff
    http://arxiv.org/abs/1910.02646v2

    • [cs.RO]Toward Synergic Learning for Autonomous Manipulation of Deformable Tissues via Surgical Robots: An Approximate Q-Learning Approach
    Sahba Aghajani Pedram, Peter Walker Ferguson, Changyeob Shin, Ankur Mehta, Erik P. Dutson, Farshid Alambeigi, Jacob Rosen
    http://arxiv.org/abs/1910.03398v1

    • [cs.SI]Describing Alt-Right communities and their discourse on Twitter during the 2018 US mid-term elections
    Ángel Panizo-LLedot, Javier Torregrosa, Gema Bello-Orgaz, Joshua Thronburn, David Camacho
    http://arxiv.org/abs/1910.03431v1

    • [econ.EM]Application of Machine Learning in Forecasting International Trade Trends
    Feras Batarseh, Munisamy Gopinath, Ganesh Nalluru, Jayson Beckman
    http://arxiv.org/abs/1910.03112v1

    • [econ.EM]Boosting High Dimensional Predictive Regressions with Time Varying Parameters
    Kashif Yousuf, Serena Ng
    http://arxiv.org/abs/1910.03109v1

    • [eess.IV]CeliacNet: Celiac Disease Severity Diagnosis on Duodenal Histopathological Images Using Deep Residual Networks
    Rasoul Sali, Lubaina Ehsan, Kamran Kowsari, Marium Khan, Christopher A. Moskaluk, Sana Syed, Donald E. Brown
    http://arxiv.org/abs/1910.03084v1

    • [eess.IV]Lossy Image Compression with Recurrent Neural Networks: from Human Perceived Visual Quality to Classification Accuracy
    Maurice Weber, Cedric Renggli, Helmut Grabner, Ce Zhang
    http://arxiv.org/abs/1910.03472v1

    • [eess.IV]Lung nodule segmentation via level set machine learning
    Matthew C Hancock, Jerry F Magnan
    http://arxiv.org/abs/1910.03191v1

    • [math.AG]Computational complexity in algebraic regression
    Oliver Gäfvert
    http://arxiv.org/abs/1910.03305v1

    • [math.NA]Implicit Neural Solver for Time-dependent Linear PDEs with Convergence Guarantee
    Suprosanna Shit, Abinav Ravi, Ivan Ezhov, Jana Lipkova, Marie Piraud, Bjoern Menze
    http://arxiv.org/abs/1910.03452v1

    • [math.NA]Optimizing Geometric Multigrid Methods with Evolutionary Computation
    Jonas Schmitt, Sebastian Kuckuk, Harald Köstler
    http://arxiv.org/abs/1910.02749v2

    • [math.OC]Integrated Optimization of Ascent Trajectory and SRM Design of Multistage Launch Vehicles
    Lorenzo Federici, Alessandro Zavoli, Guido Colasurdo, Lucandrea Mancini, Agostino Neri
    http://arxiv.org/abs/1910.03268v1

    • [math.OC]On Polyhedral and Second-Order-Cone Decompositions of Semidefinite Optimization Problems
    Dimitris Bertsimas, Ryan Cory-Wright
    http://arxiv.org/abs/1910.03143v1

    • [math.ST]Bregman-divergence-guided Legendre exponential dispersion model with finite cumulants (K-LED)
    Hyenkyun Woo
    http://arxiv.org/abs/1910.03025v1

    • [math.ST]Identifying causal effects in maximally oriented partially directed acyclic graphs
    Emilija Perković
    http://arxiv.org/abs/1910.02997v1

    • [math.ST]Nonparametric principal subspace regression
    Mark Koudstaal, Dengdeng Yu, Dehan Kong, Fang Yao
    http://arxiv.org/abs/1910.02866v2

    • [math.ST]The density ratio of generalized binomial versus Poisson distributions
    Lutz Duembgen, Jon A. Wellner
    http://arxiv.org/abs/1910.03444v1

    • [physics.flu-dyn]Generalization of machine-learned turbulent heat flux models applied to film cooling flows
    Pedro M. Milani, Julia Ling, John K. Eaton
    http://arxiv.org/abs/1910.03097v1

    • [physics.soc-ph]The Nature of Human Settlement: Building an understanding of high performance city design
    Kerry A. Nice, Gideon D. P. A. Aschwanden, Jasper S. Wijnands, Jason Thompson, Haifeng Zhao, Mark Stevenson
    http://arxiv.org/abs/1910.03219v1

    • [q-bio.NC]Analysis of an Automated Machine Learning Approach in Brain Predictive Modelling: A data-driven approach to Predict Brain Age from Cortical Anatomical Measures
    Jessica Dafflon, Walter H. L Pinaya, Federico Turkheimer, James H. Cole, Robert Leech, Mathew A. Harris, Simon R. Cox, Heather C. Whalley, Andrew M. McIntosh, Peter J. Hellyer
    http://arxiv.org/abs/1910.03349v1

    • [q-bio.QM]A Pan-Cancer and Polygenic Bayesian Hierarchical Model for the Effect of Somatic Mutations on Survival
    Sarah Samorodnitsky, Katherine A. Hoadley, Eric F. Lock
    http://arxiv.org/abs/1910.03447v1

    • [q-bio.QM]Joint analysis of clinical risk factors and 4D cardiac motion for survival prediction using a hybrid deep learning network
    Shihao Jin, Nicolò Savioli, Antonio de Marvao, Timothy JW Dawes, Axel Gandy, Daniel Rueckert, Declan P O’Regan
    http://arxiv.org/abs/1910.02951v1

    • [q-bio.QM]Stochastic modeling of hyposmotic lysis and characterization of different osmotic stability subgroups of human erythrocytes
    Adriano Francisco Siqueira, Morun Bernardino Neto, Ana Lucia Gabas Ferreira, Luciana Alves de Medeiros, Mario da Silva Garrote-Filho, Ubirajara Coutinho Filho, Nilson Penha-Silva
    http://arxiv.org/abs/1910.03491v1

    • [stat.AP]A direct approach to detection and attribution of climate change
    Eniko Székely, Sebastian Sippel, Reto Knutti, Guillaume Obozinski, Nicolai Meinshausen
    http://arxiv.org/abs/1910.03346v1

    • [stat.AP]Simulation of land use dynamics in Paragominas-PA: differences in spatial rules between smallholdings and agribusiness areas
    Reinis Osis, François Laurent, René Poccard-Chapuis
    http://arxiv.org/abs/1910.03458v1

    • [stat.ME]A Distributed and Integrated Method of Moments for High-Dimensional Correlated Data Analysis
    Emily C. Hector, Peter X. -K. Song
    http://arxiv.org/abs/1910.02986v1

    • [stat.ME]Accelerating Bayesian inference in hydrological modeling with a mechanistic emulator
    David Machac, Peter Reichert, Jörg Rieckermann, Dario Del Giudice, Carlo Albert
    http://arxiv.org/abs/1910.03481v1

    • [stat.ME]Causal Inference for Comprehensive Cohort Studies
    Yi Lu, Daniel O. Scharfstein, Maria M. Brooks, Kevin Quach, Edward H. Kennedy
    http://arxiv.org/abs/1910.03531v1

    • [stat.ME]Combining Biomarkers by Maximizing the True Positive Rate for a Fixed False Positive Rate
    Allison Meisner, Marco Carone, Margaret S. Pepe, Kathleen F. Kerr
    http://arxiv.org/abs/1910.02087v1

    • [stat.ME]Gaussian Process Assisted Active Learning of Physical Laws
    Jiuhai Chen, Lulu Kang, Guang Lin
    http://arxiv.org/abs/1910.03120v1

    • [stat.ME]Inhomogeneous higher-order summary statistics for linear network point processes
    Ottmar Cronie, Mehdi Moradi, Jorge Mateu
    http://arxiv.org/abs/1910.03304v1

    • [stat.ME]Inverse Probability Weighted Estimators of Vaccine Effects Accommodating Partial Interference and Censoring
    Sujatro Chakladar, Michael G. Hudgens, M. Elizabeth Halloran, John D. Clemens, Mohammad Ali, Michael E. Emch
    http://arxiv.org/abs/1910.03536v1

    • [stat.ME]Partial Separability and Functional Graphical Models for Multivariate Gaussian Processes
    Javier Zapata, Sang-Yun Oh, Alexander Petersen
    http://arxiv.org/abs/1910.03134v1

    • [stat.ME]Perturbed factor analysis: Improving generalizability across studies
    Arkaprava Roy, Isaac Lavine, Amy H. Herring, David B. Dunson
    http://arxiv.org/abs/1910.03021v1

    • [stat.ME]SIMPCA: A framework for rotating and sparsifying principal components
    Giovanni Maria Merola
    http://arxiv.org/abs/1910.03266v1

    • [stat.ML]Universal Approximation Theorems
    Anastasis Kratsios
    http://arxiv.org/abs/1910.03344v1