cs.AI - 人工智能

    cs.CC - 计算复杂度 cs.CL - 计算与语言 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.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.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.SE - 软件工程 cs.SI - 社交网络与信息网络 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 math.ST - 统计理论 physics.bio-ph - 生物物理 physics.chem-ph -化学物理 physics.soc-ph - 物理学与社会 q-bio.QM - 定量方法 quant-ph - 量子物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]Interactive Collaborative Exploration using Incomplete Contexts
    • [cs.CC]Complexity and Geometry of Sampling Connected Graph Partitions
    • [cs.CL]Deep Learning Based Chatbot Models
    • [cs.CL]Gender Representation in French Broadcast Corpora and Its Impact on ASR Performance
    • [cs.CL]Hierarchically-Refined Label Attention Network for Sequence Labeling
    • [cs.CL]Joint Extraction of Entities and Relations with a Hierarchical Multi-task Tagging Model
    • [cs.CL]Neural Poetry: Learning to Generate Poems using Syllables
    • [cs.CL]Training Optimus Prime, M.D.: Generating Medical Certification Items by Fine-Tuning OpenAI’s gpt2 Transformer Model
    • [cs.CL]Unsupervised Text Summarization via Mixed Model Back-Translation
    • [cs.CV]A BLSTM Network for Printed Bengali OCR System with High Accuracy
    • [cs.CV]A Review of Point Cloud Semantic Segmentation
    • [cs.CV]AdvHat: Real-world adversarial attack on ArcFace Face ID system
    • [cs.CV]Cephalometric Landmark Detection by AttentiveFeature Pyramid Fusion and Regression-Voting
    • [cs.CV]Crowd Counting with Deep Structured Scale Integration Network
    • [cs.CV]DRFN: Deep Recurrent Fusion Network for Single-Image Super-Resolution with Large Factors
    • [cs.CV]Feature Learning to Automatically Assess Radiographic Knee Osteoarthritis Severity
    • [cs.CV]Generating High-Resolution Fashion Model Images Wearing Custom Outfits
    • [cs.CV]Learning Filter Basis for Convolutional Neural Network Compression
    • [cs.CV]Learning Similarity Conditions Without Explicit Supervision
    • [cs.CV]Multi-Spectral Visual Odometry without Explicit Stereo Matching
    • [cs.CV]Mutual information neural estimation in CNN-based end-to-end medical image registration
    • [cs.CV]Onion-Peel Networks for Deep Video Completion
    • [cs.CV]Region Tracking in an Image Sequence: Preventing Driver Inattention
    • [cs.CV]Sequential Adversarial Learning for Self-Supervised Deep Visual Odometry
    • [cs.CV]Shadow Removal via Shadow Image Decomposition
    • [cs.CV]Sign Language Recognition, Generation, and Translation: An Interdisciplinary Perspective
    • [cs.CV]Trajectory Prediction by Coupling Scene-LSTM with Human Movement LSTM
    • [cs.CY]A Contextual Bandit Algorithm for Ad Creative under Ad Fatigue
    • [cs.CY]AI and Accessibility: A Discussion of Ethical Considerations
    • [cs.CY]Analysis of User Dwell Time by Category in News Application
    • [cs.CY]On the importance of system-view centric validation for the design and operation of a crypto-based digital economy
    • [cs.CY]Tracking Behavioral Patterns among Students in an Online Educational System
    • [cs.CY]Trajectory-Based Urban Air Mobility (UAM) Operations Simulator (TUS)
    • [cs.DB]Revisiting Wedge Sampling for Budgeted Maximum Inner Product Search
    • [cs.DC]Coalesced TLB to Exploit Diverse Contiguity of Memory Mapping
    • [cs.DC]Simulation of Quantum Many-Body Systems on Amazon Cloud
    • [cs.HC]Stackelberg Punishment and Bully-Proofing Autonomous Vehicles
    • [cs.IR]DC3 — A Diagnostic Case Challenge Collection for Clinical Decision Support
    • [cs.IR]Improving Few-shot Text Classification via Pretrained Language Representations
    • [cs.IR]Intent term selection and refinement in e-commerce queries
    • [cs.IR]Song Hit Prediction: Predicting Billboard Hits Using Spotify Data
    • [cs.IT]A novel approach to multivariate redundancy and synergy
    • [cs.IT]Beating the probabilistic lower bound on perfect hashing
    • [cs.IT]Beyond the Channel Capacity of BPSK Input
    • [cs.IT]Multi-Tag Backscattering to MIMO Reader: Channel Estimation and Throughput Fairness
    • [cs.IT]On the minimum weights of ternary linear complementary dual codes
    • [cs.IT]Remark on subcodes of linear complementary dual codes
    • [cs.LG]$α$ Belief Propagation as Fully Factorized Approximation
    • [cs.LG]Applications of Nature-Inspired Algorithms for Dimension Reduction: Enabling Efficient Data Analytics
    • [cs.LG]Bayesian Receiver Operating Characteristic Metric for Linear Classifiers
    • [cs.LG]Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms
    • [cs.LG]Fairness in Deep Learning: A Computational Perspective
    • [cs.LG]Feedbackward Decoding for Semantic Segmentation
    • [cs.LG]Interpretable Cognitive Diagnosis with Neural Network for Intelligent Educational Systems
    • [cs.LG]Lukthung Classification Using Neural Networks on Lyrics and Audios
    • [cs.LG]MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation
    • [cs.LG]Mish: A Self Regularized Non-Monotonic Neural Activation Function
    • [cs.LG]Quadratic Surface Support Vector Machine with L1 Norm Regularization
    • [cs.LG]QuicK-means: Acceleration of K-means by learning a fast transform
    • [cs.LG]Reinforcement Learning in Healthcare: A Survey
    • [cs.LG]Tiered Graph Autoencoders with PyTorch Geometric for Molecular Graphs
    • [cs.LG]Viability of machine learning to reduce workload in systematic review screenings in the health sciences: a working paper
    • [cs.MA]Immediate Observation in Mediated Population Protocols
    • [cs.MA]Semantic Structures for Spatially-Distributed Multi-Agent Systems
    • [cs.NE]Runtime Analysis of Fitness-Proportionate Selection on Linear Functions
    • [cs.NE]Spiking Neural Predictive Coding for Continual Learning from Data Streams
    • [cs.NI]Multiple D2D Multicasts in Underlay Cellular Networks
    • [cs.NI]Network-Accelerated Non-Contiguous Memory Transfers
    • [cs.RO]A Comparison of Action Spaces for Learning Manipulation Tasks
    • [cs.RO]A Robust Regression Approach for Robot Model Learning
    • [cs.RO]Flexible Trinocular: Non-rigid Multi-Camera-IMU Dense Reconstruction for UAV Navigation and Mapping
    • [cs.RO]Object-RPE: Dense 3D Reconstruction and Pose Estimation with Convolutional Neural Networks for Warehouse Robots
    • [cs.RO]Robust Navigation of a Soft Growing Robot by Exploiting Contact with the Environment
    • [cs.SE]Automated Generation of Test Models from Semi-Structured Requirements
    • [cs.SI]Delivering Scientific Influence Analysis as a Service on Research Grants Repository
    • [cs.SI]From Community to Role-based Graph Embeddings
    • [cs.SI]Linear response theory for Google matrix
    • [cs.SI]On the Structural Properties of Social Networks and their Measurement-calibrated Synthetic Counterparts
    • [cs.SI]Toward Maximizing the Visibility of Content in Social Media Brand Pages: A Temporal Analysis
    • [econ.GN]Economically rational sample-size choice and irreproducibility
    • [eess.AS]Incremental Binarization On Recurrent Neural Networks For Single-Channel Source Separation
    • [eess.IV]A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs
    • [eess.IV]Assessing Knee OA Severity with CNN attention-based end-to-end architectures
    • [eess.IV]Automatic Rodent Brain MRI Lesion Segmentation with Fully Convolutional Networks
    • [eess.IV]Predicting knee osteoarthritis severity: comparative modeling based on patient’s data and plain X-ray images
    • [eess.IV]Topology-preserving augmentation for CNN-based segmentation of congenital heart defects from 3D paediatric CMR
    • [eess.SP]Gaussian implementation of the multi-Bernoulli mixture filter
    • [eess.SP]Reconfigurable Intelligent Surfaces vs. Relaying: Differences, Similarities, and Performance Comparison
    • [eess.SP]Spooky effect in optimal OSPA estimation and how GOSPA solves it
    • [math.ST]Conformal prediction with localization
    • [math.ST]Graphical Construction of Spatial Gibbs Random Graphs
    • [math.ST]On the asymptotic properties of SLOPE
    • [math.ST]On the estimation of high-dimensional integrated covariance matrix based on high-frequency data with multiple transactions
    • [math.ST]Sparse Additive Gaussian Process Regression
    • [physics.bio-ph]Image based cellular contractile force evaluation with small-world network inspired CNN: SW-UNet
    • [physics.chem-ph]Automated Fitting of Neural Network Potentials at Coupled Cluster Accuracy: Protonated Water Clusters as Testing Ground
    • [physics.soc-ph]Dissent and Rebellion in the House of Commons: A Social Network Analysis of Brexit-Related Divisions in the 57$^{ th}$ Parliament
    • [q-bio.QM]Exact inference under the perfect phylogeny model
    • [quant-ph]Predicting Features of Quantum Systems using Classical Shadows
    • [stat.AP]Peak Electricity Demand and Global Warming in the Industrial and Residential areas of Pune : An Extreme Value Approach
    • [stat.CO]Accelerating proximal Markov chain Monte Carlo by using explicit stabilised methods
    • [stat.ME]A relation between log-likelihood and cross-validation log-scores
    • [stat.ME]BdryGP: a new Gaussian process model for incorporating boundary information
    • [stat.ME]M-type penalized splines for functional linear regression
    • [stat.ME]On Poisson-exponential-Tweedie models for ultra-overdispersed data
    • [stat.ME]Regression Analysis of Unmeasured Confounding
    • [stat.ML]Adversary-resilient Inference and Machine Learning: From Distributed to Decentralized
    • [stat.ML]Increasing the Generalisaton Capacity of Conditional VAEs
    • [stat.ML]Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning

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    • [cs.AI]Interactive Collaborative Exploration using Incomplete Contexts
    Maximilian Felde, Gerd Stumme
    http://arxiv.org/abs/1908.08740v1

    • [cs.CC]Complexity and Geometry of Sampling Connected Graph Partitions
    Lorenzo Najt, Daryl DeFord, Justin Solomon
    http://arxiv.org/abs/1908.08881v1

    • [cs.CL]Deep Learning Based Chatbot Models
    Richard Csaky
    http://arxiv.org/abs/1908.08835v1

    • [cs.CL]Gender Representation in French Broadcast Corpora and Its Impact on ASR Performance
    Mahault Garnerin, Solange Rossato, Laurent Besacier
    http://arxiv.org/abs/1908.08717v1

    • [cs.CL]Hierarchically-Refined Label Attention Network for Sequence Labeling
    Leyang Cui, Yue Zhang
    http://arxiv.org/abs/1908.08676v1

    • [cs.CL]Joint Extraction of Entities and Relations with a Hierarchical Multi-task Tagging Model
    Zhepei Wei, Yantao Jia, Yuan Tian, Mohammad Javad Hosseini, Mark Steedman, Yi Chang
    http://arxiv.org/abs/1908.08672v1

    • [cs.CL]Neural Poetry: Learning to Generate Poems using Syllables
    Andrea Zugarini, Stefano Melacci, Marco Maggini
    http://arxiv.org/abs/1908.08861v1

    • [cs.CL]Training Optimus Prime, M.D.: Generating Medical Certification Items by Fine-Tuning OpenAI’s gpt2 Transformer Model
    Matthias von Davier
    http://arxiv.org/abs/1908.08594v1

    • [cs.CL]Unsupervised Text Summarization via Mixed Model Back-Translation
    Yacine Jernite
    http://arxiv.org/abs/1908.08566v1

    • [cs.CV]A BLSTM Network for Printed Bengali OCR System with High Accuracy
    Debabrata Paul, Bidyut Baran Chaudhuri
    http://arxiv.org/abs/1908.08674v1

    • [cs.CV]A Review of Point Cloud Semantic Segmentation
    Yuxing Xie, Jiaojiao Tian, Xiao Xiang Zhu
    http://arxiv.org/abs/1908.08854v1

    • [cs.CV]AdvHat: Real-world adversarial attack on ArcFace Face ID system
    Stepan Komkov, Aleksandr Petiushko
    http://arxiv.org/abs/1908.08705v1

    • [cs.CV]Cephalometric Landmark Detection by AttentiveFeature Pyramid Fusion and Regression-Voting
    Runnan Chen, Yuexin Ma, Nenglun Chen, Daniel Lee, Wenping Wang
    http://arxiv.org/abs/1908.08841v1

    • [cs.CV]Crowd Counting with Deep Structured Scale Integration Network
    Lingbo Liu, Zhilin Qiu, Guanbin Li, Shufan Liu, Wanli Ouyang, Liang Lin
    http://arxiv.org/abs/1908.08692v1

    • [cs.CV]DRFN: Deep Recurrent Fusion Network for Single-Image Super-Resolution with Large Factors
    Xin Yang, Haiyang Mei, Jiqing Zhang, Ke Xu, Baocai Yin, Qiang Zhang, Xiaopeng Wei
    http://arxiv.org/abs/1908.08837v1

    • [cs.CV]Feature Learning to Automatically Assess Radiographic Knee Osteoarthritis Severity
    Joseph Antony, Kevin McGuinness, Kieran Moran, Noel E O’ Connor
    http://arxiv.org/abs/1908.08840v1

    • [cs.CV]Generating High-Resolution Fashion Model Images Wearing Custom Outfits
    Gökhan Yildirim, Nikolay Jetchev, Roland Vollgraf, Urs Bergmann
    http://arxiv.org/abs/1908.08847v1

    • [cs.CV]Learning Filter Basis for Convolutional Neural Network Compression
    Yawei Li, Shuhang Gu, Luc Van Gool, Radu Timofte
    http://arxiv.org/abs/1908.08932v1

    • [cs.CV]Learning Similarity Conditions Without Explicit Supervision
    Reuben Tan, Mariya I. Vasileva, Kate Saenko, Bryan A. Plummer
    http://arxiv.org/abs/1908.08589v1

    • [cs.CV]Multi-Spectral Visual Odometry without Explicit Stereo Matching
    Weichen Dai, Yu Zhang, Donglei Sun, Naira Hovakimyan, Ping Li
    http://arxiv.org/abs/1908.08814v1

    • [cs.CV]Mutual information neural estimation in CNN-based end-to-end medical image registration
    Yechong Huang, Tao Song, Jieru Zhu, Wenqi Luo, Jiahang Xu, Xiahai Zhuang
    http://arxiv.org/abs/1908.08767v1

    • [cs.CV]Onion-Peel Networks for Deep Video Completion
    Seoung Wug Oh, Sungho Lee, Joon-Young Lee, Seon Joo Kim
    http://arxiv.org/abs/1908.08718v1

    • [cs.CV]Region Tracking in an Image Sequence: Preventing Driver Inattention
    Matthew Kowal, Gillian Sandison, Len Yabuki-Soh, Raner la Bastide
    http://arxiv.org/abs/1908.08914v1

    • [cs.CV]Sequential Adversarial Learning for Self-Supervised Deep Visual Odometry
    Shunkai Li, Fei Xue, Xin Wang, Zike Yan, Hongbin Zha
    http://arxiv.org/abs/1908.08704v1

    • [cs.CV]Shadow Removal via Shadow Image Decomposition
    Hieu Le, Dimitris Samaras
    http://arxiv.org/abs/1908.08628v1

    • [cs.CV]Sign Language Recognition, Generation, and Translation: An Interdisciplinary Perspective
    Danielle Bragg, Oscar Koller, Mary Bellard, Larwan Berke, Patrick Boudrealt, Annelies Braffort, Naomi Caselli, Matt Huenerfauth, Hernisa Kacorri, Tessa Verhoef, Christian Vogler, Meredith Ringel Morris
    http://arxiv.org/abs/1908.08597v1

    • [cs.CV]Trajectory Prediction by Coupling Scene-LSTM with Human Movement LSTM
    Manh Huynh, Gita Alaghband
    http://arxiv.org/abs/1908.08908v1

    • [cs.CY]A Contextual Bandit Algorithm for Ad Creative under Ad Fatigue
    Daisuke Moriwaki, Komei Fujita, Shota Yasui, Takahiro Hoshino
    http://arxiv.org/abs/1908.08936v1

    • [cs.CY]AI and Accessibility: A Discussion of Ethical Considerations
    Meredith Ringel Morris
    http://arxiv.org/abs/1908.08939v1

    • [cs.CY]Analysis of User Dwell Time by Category in News Application
    Yoshifumi Seki, Mitsuo Yoshida
    http://arxiv.org/abs/1908.08690v1

    • [cs.CY]On the importance of system-view centric validation for the design and operation of a crypto-based digital economy
    Alexander Poddey, Nik Scharmann
    http://arxiv.org/abs/1908.08675v1

    • [cs.CY]Tracking Behavioral Patterns among Students in an Online Educational System
    Stephan Lorenzen, Niklas Hjuler, Stephen Alstrup
    http://arxiv.org/abs/1908.08937v1

    • [cs.CY]Trajectory-Based Urban Air Mobility (UAM) Operations Simulator (TUS)
    Euclides C. Pinto Neto, Derick M. Baum, Jorge Rady de Almeida Junior, João Batista Camargo Junior, Paulo Sérgio Cugnasca
    http://arxiv.org/abs/1908.08651v1

    • [cs.DB]Revisiting Wedge Sampling for Budgeted Maximum Inner Product Search
    Stephan S. Lorenzen, Ninh Pham
    http://arxiv.org/abs/1908.08656v1

    • [cs.DC]Coalesced TLB to Exploit Diverse Contiguity of Memory Mapping
    Yikun Ban, Yuchen Zhou, Jingrui He, Xu Cheng, Jiangfang Yi
    http://arxiv.org/abs/1908.08774v1

    • [cs.DC]Simulation of Quantum Many-Body Systems on Amazon Cloud
    Justin A. Reyes, Eduardo R. Mucciolo, Dan Marinescu
    http://arxiv.org/abs/1908.08553v1

    • [cs.HC]Stackelberg Punishment and Bully-Proofing Autonomous Vehicles
    Matt Cooper, Jun Ki Lee, Jacob Beck, Joshua D. Fishman, Michael Gillett, Zoë Papakipos, Aaron Zhang, Jerome Ramos, Aansh Shah, Michael L. Littman
    http://arxiv.org/abs/1908.08641v1

    • [cs.IR]DC3 — A Diagnostic Case Challenge Collection for Clinical Decision Support
    Carsten Eickhoff, Floran Gmehlin, Anu V. Patel, Jocelyn Boullier, Hamish Fraser
    http://arxiv.org/abs/1908.08581v1

    • [cs.IR]Improving Few-shot Text Classification via Pretrained Language Representations
    Ningyu Zhang, Zhanlin Sun, Shumin Deng, Jiaoyan Chen, Huajun Chen
    http://arxiv.org/abs/1908.08788v1

    • [cs.IR]Intent term selection and refinement in e-commerce queries
    Saurav Manchanda, Mohit Sharma, George Karypis
    http://arxiv.org/abs/1908.08564v1

    • [cs.IR]Song Hit Prediction: Predicting Billboard Hits Using Spotify Data
    Kai Middlebrook, Kian Sheik
    http://arxiv.org/abs/1908.08609v1

    • [cs.IT]A novel approach to multivariate redundancy and synergy
    Artemy Kolchinsky
    http://arxiv.org/abs/1908.08642v1

    • [cs.IT]Beating the probabilistic lower bound on perfect hashing
    Chaoping Xing, Chen Yuan
    http://arxiv.org/abs/1908.08792v1

    • [cs.IT]Beyond the Channel Capacity of BPSK Input
    Bingli Jiao, Dongsheng Zheng, Mingxi Yin, Yuli Yang
    http://arxiv.org/abs/1908.08836v1

    • [cs.IT]Multi-Tag Backscattering to MIMO Reader: Channel Estimation and Throughput Fairness
    Deepak Mishra, Erik G. Larsson
    http://arxiv.org/abs/1908.08748v1

    • [cs.IT]On the minimum weights of ternary linear complementary dual codes
    Makoto Araya, Masaaki Harada
    http://arxiv.org/abs/1908.08661v1

    • [cs.IT]Remark on subcodes of linear complementary dual codes
    Masaaki Harada, Ken Saito
    http://arxiv.org/abs/1908.08662v1

    • [cs.LG]$α$ Belief Propagation as Fully Factorized Approximation
    Dong Liu, Nima N. Moghadam, Lars K. Rasmussen, Jinliang Huang, Saikat Chatterjee
    http://arxiv.org/abs/1908.08906v1

    • [cs.LG]Applications of Nature-Inspired Algorithms for Dimension Reduction: Enabling Efficient Data Analytics
    Farid Ghareh Mohammadi, M. Hadi Amini, Hamid R. Arabnia
    http://arxiv.org/abs/1908.08563v1

    • [cs.LG]Bayesian Receiver Operating Characteristic Metric for Linear Classifiers
    Syeda Sakira Hassan, Heikki Huttunen, Jari Niemi, Jussi Tohka
    http://arxiv.org/abs/1908.08771v1

    • [cs.LG]Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms
    Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nezihe Merve Gurel, Bo Li, Ce Zhang, Costas J. Spanos, Dawn Song
    http://arxiv.org/abs/1908.08619v1

    • [cs.LG]Fairness in Deep Learning: A Computational Perspective
    Mengnan Du, Fan Yang, Na Zou, Xia Hu
    http://arxiv.org/abs/1908.08843v1

    • [cs.LG]Feedbackward Decoding for Semantic Segmentation
    Beinan Wang, John Glossner, Daniel Iancu, Georgi N. Gaydadjiev
    http://arxiv.org/abs/1908.08584v1

    • [cs.LG]Interpretable Cognitive Diagnosis with Neural Network for Intelligent Educational Systems
    Fei Wang, Qi Liu, Enhong Chen, Zhenya Huang
    http://arxiv.org/abs/1908.08733v1

    • [cs.LG]Lukthung Classification Using Neural Networks on Lyrics and Audios
    Kawisorn Kamtue, Kasina Euchukanonchai, Dittaya Wanvarie, Naruemon Pratanwanich
    http://arxiv.org/abs/1908.08769v1

    • [cs.LG]MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation
    Abhay Kumar, Nishant Jain, Suraj Tripathi, Chirag Singh, Kamal Krishna
    http://arxiv.org/abs/1908.08652v1

    • [cs.LG]Mish: A Self Regularized Non-Monotonic Neural Activation Function
    Diganta Misra
    http://arxiv.org/abs/1908.08681v1

    • [cs.LG]Quadratic Surface Support Vector Machine with L1 Norm Regularization
    Seyedahmad Mousavi, Zheming Gao, Lanshan Han, Alvin Lim
    http://arxiv.org/abs/1908.08616v1

    • [cs.LG]QuicK-means: Acceleration of K-means by learning a fast transform
    Luc Giffon, Valentin Emiya, Liva Ralaivola, Hachem Kadri
    http://arxiv.org/abs/1908.08713v1

    • [cs.LG]Reinforcement Learning in Healthcare: A Survey
    Chao Yu, Jiming Liu, Shamim Nemati
    http://arxiv.org/abs/1908.08796v1

    • [cs.LG]Tiered Graph Autoencoders with PyTorch Geometric for Molecular Graphs
    Daniel T. Chang
    http://arxiv.org/abs/1908.08612v1

    • [cs.LG]Viability of machine learning to reduce workload in systematic review screenings in the health sciences: a working paper
    Muhammad Maaz
    http://arxiv.org/abs/1908.08610v1

    • [cs.MA]Immediate Observation in Mediated Population Protocols
    Tobias Prehn, Myron Rotter
    http://arxiv.org/abs/1908.08637v1

    • [cs.MA]Semantic Structures for Spatially-Distributed Multi-Agent Systems
    Frank Valencia
    http://arxiv.org/abs/1908.08634v1

    • [cs.NE]Runtime Analysis of Fitness-Proportionate Selection on Linear Functions
    Duc-Cuong Dang, Anton Eremeev, Per Kristian Lehre
    http://arxiv.org/abs/1908.08686v1

    • [cs.NE]Spiking Neural Predictive Coding for Continual Learning from Data Streams
    Alexander Ororbia
    http://arxiv.org/abs/1908.08655v1

    • [cs.NI]Multiple D2D Multicasts in Underlay Cellular Networks
    Ajay Bhardwaj, Samar Agnihotri
    http://arxiv.org/abs/1908.08866v1

    • [cs.NI]Network-Accelerated Non-Contiguous Memory Transfers
    Salvatore Di Girolamo, Konstantin Taranov, Andreas Kurth, Michael Schaffner, Timo Schneider, Jakub Beránek, Maciej Besta, Luca Benini, Duncan Roweth, Torsten Hoefler
    http://arxiv.org/abs/1908.08590v1

    • [cs.RO]A Comparison of Action Spaces for Learning Manipulation Tasks
    Patrick Varin, Lev Grossman, Scott Kuindersma
    http://arxiv.org/abs/1908.08659v1

    • [cs.RO]A Robust Regression Approach for Robot Model Learning
    Francesco Cursi, Guang-Zhong Yang
    http://arxiv.org/abs/1908.08855v1

    • [cs.RO]Flexible Trinocular: Non-rigid Multi-Camera-IMU Dense Reconstruction for UAV Navigation and Mapping
    Timo Hinzmann, Cesar Cadena, Juan Nieto, Roland Siegwart
    http://arxiv.org/abs/1908.08891v1

    • [cs.RO]Object-RPE: Dense 3D Reconstruction and Pose Estimation with Convolutional Neural Networks for Warehouse Robots
    Dinh-Cuong Hoang, Todor Stoyanov, Achim J. Lilienthal
    http://arxiv.org/abs/1908.08601v1

    • [cs.RO]Robust Navigation of a Soft Growing Robot by Exploiting Contact with the Environment
    Joseph D. Greer, Laura H. Blumenschein, Ron Alterovitz, Elliot W. Hawkes, Allison M. Okamura
    http://arxiv.org/abs/1908.08645v1

    • [cs.SE]Automated Generation of Test Models from Semi-Structured Requirements
    Jannik Fischbach, Maximilian Junker, Andreas Vogelsang, Dietmar Freudenstein
    http://arxiv.org/abs/1908.08810v1

    • [cs.SI]Delivering Scientific Influence Analysis as a Service on Research Grants Repository
    Yuming Wang, Yanbo Long, Lai Tu, Ling Liu
    http://arxiv.org/abs/1908.08715v1

    • [cs.SI]From Community to Role-based Graph Embeddings
    Ryan A. Rossi, Di Jin, Sungchul Kim, Nesreen K. Ahmed, Danai Koutra, John Boaz Lee
    http://arxiv.org/abs/1908.08572v1

    • [cs.SI]Linear response theory for Google matrix
    Klaus M. Frahm, Dima L. Shepelyansky
    http://arxiv.org/abs/1908.08924v1

    • [cs.SI]On the Structural Properties of Social Networks and their Measurement-calibrated Synthetic Counterparts
    Marcell Nagy, Roland Molontay
    http://arxiv.org/abs/1908.08429v1

    • [cs.SI]Toward Maximizing the Visibility of Content in Social Media Brand Pages: A Temporal Analysis
    Nagendra Kumar, Gopi Ande, J. Shirish Kumar, Manish Singh
    http://arxiv.org/abs/1908.08622v1

    • [econ.GN]Economically rational sample-size choice and irreproducibility
    Oliver Braganza
    http://arxiv.org/abs/1908.08702v1

    • [eess.AS]Incremental Binarization On Recurrent Neural Networks For Single-Channel Source Separation
    Sunwoo Kim, Mrinmoy Maity, Minje Kim
    http://arxiv.org/abs/1908.08898v1

    • [eess.IV]A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs
    Antonio Garcia-Uceda Juarez, Raghavendra Selvan, Zaigham Saghir, Marleen de Bruijne
    http://arxiv.org/abs/1908.08588v1

    • [eess.IV]Assessing Knee OA Severity with CNN attention-based end-to-end architectures
    Marc Górriz, Joseph Antony, Kevin McGuinness, Xavier Giró-i-Nieto, Noel E. O’Connor
    http://arxiv.org/abs/1908.08856v1

    • [eess.IV]Automatic Rodent Brain MRI Lesion Segmentation with Fully Convolutional Networks
    Juan Miguel Valverde, Artem Shatillo, Riccardo de Feo, Olli Gröhn, Alejandra Sierra, Jussi Tohka
    http://arxiv.org/abs/1908.08746v1

    • [eess.IV]Predicting knee osteoarthritis severity: comparative modeling based on patient’s data and plain X-ray images
    Jaynal Abedin, Joseph Antony, Kevin McGuinness, Kieran Moran, Noel E O’Connor, Dietrich Rebholz-Schuhmann, John Newell
    http://arxiv.org/abs/1908.08873v1

    • [eess.IV]Topology-preserving augmentation for CNN-based segmentation of congenital heart defects from 3D paediatric CMR
    Nick Byrne, James R. Clough, Isra Valverde, Giovanni Montana, Andrew P. King
    http://arxiv.org/abs/1908.08870v1

    • [eess.SP]Gaussian implementation of the multi-Bernoulli mixture filter
    Ángel F. García-Fernández, Yuxuan Xia, Karl Granström, Lennart Svensson, Jason L. Williams
    http://arxiv.org/abs/1908.08819v1

    • [eess.SP]Reconfigurable Intelligent Surfaces vs. Relaying: Differences, Similarities, and Performance Comparison
    K. Ntontin, M. Di Renzo, J. Song, F. Lazarakis, J. de Rosny, D. -T. Phan-Huy, O. Simeone, R. Zhang, M. Debbah, G. Lerosey, M. Fink, S. Tretyakov, S. Shamai
    http://arxiv.org/abs/1908.08747v1

    • [eess.SP]Spooky effect in optimal OSPA estimation and how GOSPA solves it
    Ángel F. García-Fernández, Lennart Svensson
    http://arxiv.org/abs/1908.08815v1

    • [math.ST]Conformal prediction with localization
    Leying Guan
    http://arxiv.org/abs/1908.08558v1

    • [math.ST]Graphical Construction of Spatial Gibbs Random Graphs
    Andressa Cerqueira, Nancy L. Garcia
    http://arxiv.org/abs/1908.08880v1

    • [math.ST]On the asymptotic properties of SLOPE
    Michał Kos, Małgorzata Bogdan
    http://arxiv.org/abs/1908.08791v1

    • [math.ST]On the estimation of high-dimensional integrated covariance matrix based on high-frequency data with multiple transactions
    Moming Wang, Ningning Xia, You Zhou
    http://arxiv.org/abs/1908.08670v1

    • [math.ST]Sparse Additive Gaussian Process Regression
    Hengrui Luo, Giovanni Nattino, Matthew T. Pratola
    http://arxiv.org/abs/1908.08864v1

    • [physics.bio-ph]Image based cellular contractile force evaluation with small-world network inspired CNN: SW-UNet
    Li Honghan, Daiki Matsunaga, Tsubasa S. Matsui, Hiroki Aosaki, Shinji Deguchi
    http://arxiv.org/abs/1908.08631v1

    • [physics.chem-ph]Automated Fitting of Neural Network Potentials at Coupled Cluster Accuracy: Protonated Water Clusters as Testing Ground
    Christoph Schran, Jörg Behler, Dominik Marx
    http://arxiv.org/abs/1908.08734v1

    • [physics.soc-ph]Dissent and Rebellion in the House of Commons: A Social Network Analysis of Brexit-Related Divisions in the 57$^{ th}$ Parliament
    Carla Intal, Taha Yasseri
    http://arxiv.org/abs/1908.08859v1

    • [q-bio.QM]Exact inference under the perfect phylogeny model
    Surjyendu Ray, Bei Jia, Sam Safavi, Tim van Opijnen, Ralph Isberg, Jason Rosch, José Bento
    http://arxiv.org/abs/1908.08623v1

    • [quant-ph]Predicting Features of Quantum Systems using Classical Shadows
    Hsin-Yuan Huang, Richard Kueng
    http://arxiv.org/abs/1908.08909v1

    • [stat.AP]Peak Electricity Demand and Global Warming in the Industrial and Residential areas of Pune : An Extreme Value Approach
    Ayush Maheshwari, Kamal Kumar Murari, T. Jayaraman
    http://arxiv.org/abs/1908.08570v1

    • [stat.CO]Accelerating proximal Markov chain Monte Carlo by using explicit stabilised methods
    Luis Vargas, Marcelo Pereyra, Konstantinos C. Zygalakis
    http://arxiv.org/abs/1908.08845v1

    • [stat.ME]A relation between log-likelihood and cross-validation log-scores
    PierGianLuca Porta Mana
    http://arxiv.org/abs/1908.08741v1

    • [stat.ME]BdryGP: a new Gaussian process model for incorporating boundary information
    Liang Ding, Simon Mak, C. F. Jeff Wu
    http://arxiv.org/abs/1908.08868v1

    • [stat.ME]M-type penalized splines for functional linear regression
    Ioannis Kalogridis, Stefan Van Aelst
    http://arxiv.org/abs/1908.08760v1

    • [stat.ME]On Poisson-exponential-Tweedie models for ultra-overdispersed data
    Rahma Abid, Celestin C. Kokonendji, Afif Masmoudi
    http://arxiv.org/abs/1908.08764v1

    • [stat.ME]Regression Analysis of Unmeasured Confounding
    Brian Knaeble, Braxton Osting, Mark Abramson
    http://arxiv.org/abs/1908.08596v1

    • [stat.ML]Adversary-resilient Inference and Machine Learning: From Distributed to Decentralized
    Zhixiong Yang, Arpita Gang, Waheed U. Bajwa
    http://arxiv.org/abs/1908.08649v1

    • [stat.ML]Increasing the Generalisaton Capacity of Conditional VAEs
    Alexej Klushyn, Nutan Chen, Botond Cseke, Justin Bayer, Patrick van der Smagt
    http://arxiv.org/abs/1908.08750v1

    • [stat.ML]Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning
    Daniel Kuhn, Peyman Mohajerin Esfahani, Viet Anh Nguyen, Soroosh Shafieezadeh-Abadeh
    http://arxiv.org/abs/1908.08729v1