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• [cs.CL]An Interactive Machine Translation Framework for Modernizing Historical Documents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