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.DC - 分布式、并行与集群计算 cs.DS - 数据结构与算法 cs.GR - 计算机图形学 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.PL - 编程语言 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.CO - 组合数学 math.NA - 数值分析 math.PR - 概率 math.ST - 统计理论 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cs.AI]Completion Reasoning Emulation for the Description Logic EL+
• [cs.AI]Fuzzy Rule Interpolation Toolbox for the GNU Open-Source OCTAVE
• [cs.AI]Learning to Request Guidance in Emergent Communication
• [cs.AI]Neural-Symbolic Descriptive Action Model from Images: The Search for STRIPS
• [cs.AI]UCT-ADP Progressive Bias Algorithm for Solving Gomoku
• [cs.AI]What Can Learned Intrinsic Rewards Capture?
• [cs.CL]A Collaborative Ecosystem for Digital Coptic Studies
• [cs.CL]An Ensemble Method for Producing Word Representations for the Greek Language
• [cs.CL]Automatic Spanish Translation of the SQuAD Dataset for Multilingual Question Answering
• [cs.CL]BERT has a Moral Compass: Improvements of ethical and moral values of machines
• [cs.CL]CoSimLex: A Resource for Evaluating Graded Word Similarity in Context
• [cs.CL]FlauBERT: Unsupervised Language Model Pre-training for French
• [cs.CL]Improving Neural Protein-Protein Interaction Extraction with Knowledge Selection
• [cs.CL]Medication Regimen Extraction From Clinical Conversations
• [cs.CL]MetaMT,a MetaLearning Method Leveraging Multiple Domain Data for Low Resource Machine Translation
• [cs.CL]Neural Module Networks for Reasoning over Text
• [cs.CL]Quality of syntactic implication of RL-based sentence summarization
• [cs.CL]Two Birds with One Stone: Investigating Invertible Neural Networks for Inverse Problems in Morphology
• [cs.CL]Unsupervised Neural Dialect Translation with Commonality and Diversity Modeling
• [cs.CR]A Code-specific Conservative Model for the Failure Rate of Bit-flipping Decoding of LDPC Codes with Cryptographic Applications
• [cs.CV]$\mathbf{G^{3}AN}$: This video does not exist. Disentangling motion and appearance for video generation
• [cs.CV]A Variational-Sequential Graph Autoencoder for Neural Architecture Performance Prediction
• [cs.CV]An Efficient Approach for Using Expectation Maximization Algorithm in Capsule Networks
• [cs.CV]Associative Alignment for Few-shot Image Classification
• [cs.CV]AugFPN: Improving Multi-scale Feature Learning for Object Detection
• [cs.CV]Automatic Analysis of Sewer Pipes Based on Unrolled Monocular Fisheye Images
• [cs.CV]Automatic quality assessment for 2D fetal sonographic standard plane based on multi-task learning
• [cs.CV]BioNet: Infusing Biomarker Prior into Global-to-Local Network for Choroid Segmentation in Optical Coherence Tomography Images
• [cs.CV]Bipartite Conditional Random Fields for Panoptic Segmentation
• [cs.CV]Bottleneck detection by slope difference distribution: a robust approach for separating overlapped cells
• [cs.CV]Boundary-Aware Salient Object Detection via Recurrent Two-Stream Guided Refinement Network
• [cs.CV]Deep Adaptive Wavelet Network
• [cs.CV]Deep Direct Visual Odometry
• [cs.CV]DeepMeshFlow: Content Adaptive Mesh Deformation for Robust Image Registration
• [cs.CV]Fine-grained Classification of Rowing teams
• [cs.CV]FootAndBall: Integrated player and ball detector
• [cs.CV]GLU-Net: Global-Local Universal Network for Dense Flow and Correspondences
• [cs.CV]Graph-based Multi-view Binary Learning for Image Clustering
• [cs.CV]HistoNet: Predicting size histograms of object instances
• [cs.CV]HyperCon: Image-To-Video Model Transfer for Video-To-Video Translation Tasks
• [cs.CV]IoU-uniform R-CNN: Breaking Through the Limitations of RPN
• [cs.CV]Lane Detection For Prototype Autonomous Vehicle
• [cs.CV]Learning Domain Adaptive Features with Unlabeled Domain Bridges
• [cs.CV]Learning from Noisy Anchors for One-stage Object Detection
• [cs.CV]Lifelong learning for text retrieval and recognition in historical handwritten document collections
• [cs.CV]MineGAN: effective knowledge transfer from GANs to target domains with few images
• [cs.CV]Multimodal Self-Supervised Learning for Medical Image Analysis
• [cs.CV]Parting with Illusions about Deep Active Learning
• [cs.CV]Pillar in Pillar: Multi-Scale and Dynamic Feature Extraction for 3D Object Detection in Point Clouds
• [cs.CV]PuckNet: Estimating hockey puck location from broadcast video
• [cs.CV]RDSNet: A New Deep Architecture for Reciprocal Object Detection and Instance Segmentation
• [cs.CV]SKD: Unsupervised Keypoint Detecting for Point Clouds using Embedded Saliency Estimation
• [cs.CV]Scalability in Perception for Autonomous Driving: An Open Dataset Benchmark
• [cs.CV]Self-Driving Car Steering Angle Prediction Based on Image Recognition
• [cs.CV]SiamMan: Siamese Motion-aware Network for Visual Tracking
• [cs.CV]SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization
• [cs.CV]TANet: Robust 3D Object Detection from Point Clouds with Triple Attention
• [cs.CV]Towards Unsupervised Learning of Generative Models for 3D Controllable Image Synthesis
• [cs.CV]Training Deep SLAM on Single Frames
• [cs.CV]Vectorizing World Buildings: Planar Graph Reconstruction by Primitive Detection and Relationship Classification
• [cs.CV]What You See is What You Get: Exploiting Visibility for 3D Object Detection
• [cs.CV]Why Can’t I Dance in the Mall? Learning to Mitigate Scene Bias in Action Recognition
• [cs.CY]A Stable Nuclear Future? The Impact of Autonomous Systems and Artificial Intelligence
• [cs.CY]Dynamic Algorithmic Service Agreements Perspective
• [cs.CY]Female Librarians and Male Computer Programmers? Gender Bias in Occupational Images on Digital Media Platforms
• [cs.CY]Measurement and Fairness
• [cs.CY]Minority report detection in refugee-authored community-driven journalism using RBMs
• [cs.CY]The Hidden Assumptions Behind Counterfactual Explanations and Principal Reasons
• [cs.DC]DGEMM performance is data-dependent
• [cs.DC]Energy-aware Scheduling of Jobs in Heterogeneous Cluster Systems Using Deep Reinforcement Learning
• [cs.DC]Performance Analysis of the Libra Blockchain: An Experimental Study
• [cs.DC]Simulation of the Bitcoin Network Considering Compact Block Relay and Internet Improvements
• [cs.DS]Graph Sparsification for Derandomizing Massively Parallel Computation with Low Space
• [cs.GR]Modelling curvature of a bent paper leaf
• [cs.HC]Efficient crowdsourcing of crowd-generated microtasks
• [cs.IR]Character 3-gram Mover’s Distance: An Effective Method for Detecting Near-duplicate Japanese-language Recipes
• [cs.IR]It Runs in the Family: Searching for Similar Names using Digitized Family Trees
• [cs.IT]A Cooperative Spectrum Sensing Scheme Based on Compressive Sensing for Cognitive Radio Networks
• [cs.IT]Beyond Dirty Paper Coding for Multi-Antenna Broadcast Channel with Partial CSIT: A Rate-Splitting Approach
• [cs.IT]Concept and Experimental Demonstration of Optical IM/DD End-to-End System Optimization using a Generative Model
• [cs.IT]Constructions of quasi-twisted quantum codes
• [cs.IT]Distance Distributions of Cyclic Orbit Codes
• [cs.IT]Mutual Information in Community Detection with Covariate Information and Correlated Networks
• [cs.IT]Reconfigurable Intelligent Surfaces: Bridging the gap between scattering and reflection
• [cs.LG]A Two-Stage Approach to Few-Shot Learning for Image Recognition
• [cs.LG]Advances and Open Problems in Federated Learning
• [cs.LG]Almost Uniform Sampling From Neural Networks
• [cs.LG]An Improving Framework of regularization for Network Compression
• [cs.LG]Before we can find a model, we must forget about perfection
• [cs.LG]Deep Relevance Regularization: Interpretable and Robust Tumor Typing of Imaging Mass Spectrometry Data
• [cs.LG]Detecting and Correcting Adversarial Images Using Image Processing Operations and Convolutional Neural Networks
• [cs.LG]Doubly Robust Off-Policy Actor-Critic Algorithms for Reinforcement Learning
• [cs.LG]Efficient and Robust Reinforcement Learning with Uncertainty-based Value Expansion
• [cs.LG]Entropy Regularization with Discounted Future State Distribution in Policy Gradient Methods
• [cs.LG]Event Outcome Prediction using Sentiment Analysis and Crowd Wisdom in Microblog Feeds
• [cs.LG]Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approaches
• [cs.LG]Identifying Mislabeled Instances in Classification Datasets
• [cs.LG]Image Classification with Deep Learning in the Presence of Noisy Labels: A Survey
• [cs.LG]Imitation Learning via Off-Policy Distribution Matching
• [cs.LG]Is Feature Diversity Necessary in Neural Network Initialization?
• [cs.LG]Just Add Functions: A Neural-Symbolic Language Model
• [cs.LG]Marginalized State Distribution Entropy Regularization in Policy Optimization
• [cs.LG]Multimodal Generative Models for Compositional Representation Learning
• [cs.LG]On Neural Learnability of Chaotic Dynamics
• [cs.LG]Recurrent Transform Learning
• [cs.LG]SMAUG: End-to-End Full-Stack Simulation Infrastructure for Deep Learning Workloads
• [cs.LG]SMiRL: Surprise Minimizing RL in Dynamic Environments
• [cs.LG]Towards Better Forecasting by Fusing Near and Distant Future Visions
• [cs.LG]Unsupervised Feature Selection based on Adaptive Similarity Learning and Subspace Clustering
• [cs.LG]Unsupervised Transfer Learning via BERT Neuron Selection
• [cs.LG]Value-of-Information based Arbitration between Model-based and Model-free Control
• [cs.LG]Variational Learning with Disentanglement-PyTorch
• [cs.MA]Jason-RS, a Collaboration between Agents and an IoT Platform
• [cs.NE]Efficacy of Modern Neuro-Evolutionary Strategies for Continuous Control Optimization
• [cs.NI]Blockchain for 5G and Beyond Networks: A State of the Art Survey
• [cs.PL]Array Languages Make Neural Networks Fast
• [cs.RO]Efficient Robotic Task Generalization Using Deep Model Fusion Reinforcement Learning
• [cs.RO]Learning to Optimally Segment Point Clouds
• [cs.RO]RoboCoDraw: Robotic Avatar Drawing with GAN-based Style Transfer and Time-efficient Path Optimization
• [cs.RO]Zero-shot generalization using cascaded system-representations
• [cs.SD]Small-footprint Keyword Spotting with Graph Convolutional Network
• [cs.SD]Voice Conversion for Whispered Speech Synthesis
• [cs.SE]A Reference Architecture and Modelling Principles for Architectural Stability based on Self-Awareness: Case of Cloud Architectures
• [cs.SE]Datamorphic Testing: A Methodology for Testing AI Applications
• [cs.SI]Beyond Node Embedding: A Direct Unsupervised Edge Representation Framework for Homogeneous Networks
• [cs.SI]Collective Identity Formation on Instagram — Investigating the Social Movement Fridays for Future
• [eess.AS]Advances in Online Audio-Visual Meeting Transcription
• [eess.AS]Audiogmenter: a MATLAB Toolbox for Audio Data Augmentation
• [eess.AS]SpecAugment on Large Scale Datasets
• [eess.IV]$Σ$-net: Ensembled Iterative Deep Neural Networks for Accelerated Parallel MR Image Reconstruction
• [eess.IV]BINet: a binary inpainting network for deep patch-based image compression
• [eess.IV]Deep Learning-based Denoising of Mammographic Images using Physics-driven Data Augmentation
• [eess.IV]Deep motion estimation for parallel inter-frame prediction in video compression
• [eess.IV]Feeding the zombies: Synthesizing brain volumes using a 3D progressive growing GAN
• [eess.IV]Memory-efficient Learning for Large-scale Computational Imaging
• [eess.IV]Multi-Dimension Modulation for Image Restoration with Dynamic Controllable Residual Learning
• [eess.IV]Phase Retrieval using Conditional Generative Adversarial Networks
• [eess.IV]U-Net with spatial pyramid pooling for drusen segmentation in optical coherence tomography
• [eess.IV]UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation
• [eess.IV]Variable Rate Deep Image Compression with Modulated Autoencoder
• [eess.IV]Wide-Area Land Cover Mapping with Sentinel-1 Imagery using Deep Learning Semantic Segmentation Models
• [eess.SP]Low-Complexity LSTM-Assisted Bit-Flipping Algorithm for Successive Cancellation List Polar Decoder
• [eess.SP]Neural Memory Networks for Robust Classification of Seizure Type
• [eess.SP]SenseNet: Deep Learning based Wideband spectrum sensing and modulation classification network
• [eess.SP]Severity Detection Tool for Patients with Infectious Disease
• [eess.SP]Sparse Joint Transmission for Cell-Free Massive MIMO: A Sparse PCA Approach
• [eess.SY]Event Detection in Micro-PMU Data: A Generative Adversarial Network Scoring Method
• [math.CO]Integer Partitions Probability Distributions
• [math.NA]Tensor Completion via Gaussian Process Based Initialization
• [math.PR]Mean-Field Neural ODEs via Relaxed Optimal Control
• [math.PR]Quantitative Universality for the Largest Eigenvalue of Sample Covariance Matrices
• [math.ST]Analysis of the rate of convergence of neural network regression estimates which are easy to implement
• [math.ST]Frequentist Consistency of Generalized Variational Inference
• [math.ST]Testing Independence with the Binary Expansion Randomized Ensemble Test
• [stat.AP]Bayesian Framework for Simultaneous Registration and Estimation of Noisy, Sparse and Fragmented Functional Data
• [stat.AP]European banks’ business models and their credit risk: A cluster analysis in a high-dimensional context
• [stat.AP]Measuring Spatial Allocative Efficiency in Basketball
• [stat.AP]Robust joint modelling of longitudinal and survival data with a time-varying degrees-of-freedom parameter
• [stat.ME]Asymptotic based bootstrap approach for matched pairs with missingness in a single-arm
• [stat.ME]Bayesian Copula Density Deconvolution for Zero-Inflated Data in Nutritional Epidemiology
• [stat.ME]Center-outward quantiles and the measurement of multivariate risk
• [stat.ME]Integrative Generalized Convex Clustering Optimization and Feature Selection for Mixed Multi-View Data
• [stat.ME]More for less: Predicting and maximizing genetic variant discovery via Bayesian nonparametrics
• [stat.ME]Nonparametric Universal Copula Modeling
• [stat.ME]Sample Size Estimation using a Latent Variable Model for Mixed Outcome Co-Primary, Multiple Primary and Composite Endpoints
• [stat.ML]A Closer Look at Disentangling in $β$-VAE
• [stat.ML]Fenton-Wilkinson Order Statistics and German Tanks: A Case Study of an Orienteering Relay Race
• [stat.ML]Representational Rényi heterogeneity
• [stat.ML]Sampling for Bayesian Mixture Models: MCMC with Polynomial-Time Mixing
• [stat.ML]Statistically Robust Neural Network Classification
• [stat.ML]The Wasserstein-Fourier Distance for Stationary Time Series
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• [cs.AI]Completion Reasoning Emulation for the Description Logic EL+
Aaron Eberhart, Monireh Ebrahimi, Lu Zhou, Cogan Shimizu, Pascal Hitzler
http://arxiv.org/abs/1912.05063v1
• [cs.AI]Fuzzy Rule Interpolation Toolbox for the GNU Open-Source OCTAVE
Maen Alzubi, Mohammad Almseidin, Mohd Aaqib Lone, Szilveszter Kovacs
http://arxiv.org/abs/1912.04999v1
• [cs.AI]Learning to Request Guidance in Emergent Communication
Benjamin Kolb, Leon Lang, Henning Bartsch, Arwin Gansekoele, Raymond Koopmanschap, Leonardo Romor, David Speck, Mathijs Mul, Elia Bruni
http://arxiv.org/abs/1912.05525v1
• [cs.AI]Neural-Symbolic Descriptive Action Model from Images: The Search for STRIPS
Masataro Asai
http://arxiv.org/abs/1912.05492v1
• [cs.AI]UCT-ADP Progressive Bias Algorithm for Solving Gomoku
Xu Cao, Yanghao Lin
http://arxiv.org/abs/1912.05407v1
• [cs.AI]What Can Learned Intrinsic Rewards Capture?
Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado van Hasselt, David Silver, Satinder Singh
http://arxiv.org/abs/1912.05500v1
• [cs.CL]A Collaborative Ecosystem for Digital Coptic Studies
Caroline T. Schroeder, Amir Zeldes
http://arxiv.org/abs/1912.05082v1
• [cs.CL]An Ensemble Method for Producing Word Representations for the Greek Language
Michalis Lioudakis, Stamatis Outsios, Michalis Vazirgiannis
http://arxiv.org/abs/1912.04965v1
• [cs.CL]Automatic Spanish Translation of the SQuAD Dataset for Multilingual Question Answering
Casimiro Pio Carrino, Marta Ruiz Costa-jussà, José Adrián Rodríguez Fonollosa
http://arxiv.org/abs/1912.05200v1
• [cs.CL]BERT has a Moral Compass: Improvements of ethical and moral values of machines
Patrick Schramowski, Cigdem Turan, Sophie Jentzsch, Constantin Rothkopf, Kristian Kersting
http://arxiv.org/abs/1912.05238v1
• [cs.CL]CoSimLex: A Resource for Evaluating Graded Word Similarity in Context
Carlos Santos Armendariz, Matthew Purver, Matej Ulčar, Senja Pollak, Nikola Ljubešić, Mark Granroth-Wilding, Kristiina Vaik
http://arxiv.org/abs/1912.05320v1
• [cs.CL]FlauBERT: Unsupervised Language Model Pre-training for French
Hang Le, Loïc Vial, Jibril Frej, Vincent Segonne, Maximin Coavoux, Benjamin Lecouteux, Alexandre Allauzen, Benoît Crabbé, Laurent Besacier, Didier Schwab
http://arxiv.org/abs/1912.05372v1
• [cs.CL]Improving Neural Protein-Protein Interaction Extraction with Knowledge Selection
Huiwei Zhou, Xuefei Li, Weihong Yao, Zhuang Liu, Shixian Ning, Chengkun Lang, Lei Du
http://arxiv.org/abs/1912.05147v1
• [cs.CL]Medication Regimen Extraction From Clinical Conversations
Sai P. Selvaraj, Sandeep Konam
http://arxiv.org/abs/1912.04961v1
• [cs.CL]MetaMT,a MetaLearning Method Leveraging Multiple Domain Data for Low Resource Machine Translation
Rumeng Li, Xun Wang, Hong Yu
http://arxiv.org/abs/1912.05467v1
• [cs.CL]Neural Module Networks for Reasoning over Text
Nitish Gupta, Kevin Lin, Dan Roth, Sameer Singh, Matt Gardner
http://arxiv.org/abs/1912.04971v1
• [cs.CL]Quality of syntactic implication of RL-based sentence summarization
Hoa T. Le, Christophe Cerisara, Claire Gardent
http://arxiv.org/abs/1912.05493v1
• [cs.CL]Two Birds with One Stone: Investigating Invertible Neural Networks for Inverse Problems in Morphology
Gözde Gül Şahin, Iryna Gurevych
http://arxiv.org/abs/1912.05274v1
• [cs.CL]Unsupervised Neural Dialect Translation with Commonality and Diversity Modeling
Yu Wan, Baosong Yang, Derek F. Wong, Lidia S. Chao, Haihua Du, Ben C. H. Ao
http://arxiv.org/abs/1912.05134v1
• [cs.CR]A Code-specific Conservative Model for the Failure Rate of Bit-flipping Decoding of LDPC Codes with Cryptographic Applications
Paolo Santini, Alessandro Barenghi, Gerardo Pelosi, Marco Baldi, Franco Chiaraluce
http://arxiv.org/abs/1912.05182v1
• [cs.CV]$\mathbf{G^{3}AN}$: This video does not exist. Disentangling motion and appearance for video generation
Yaohui Wang, Piotr Bilinski, Francois Bremond, Antitza Dantcheva
http://arxiv.org/abs/1912.05523v1
• [cs.CV]A Variational-Sequential Graph Autoencoder for Neural Architecture Performance Prediction
David Friede, Jovita Lukasik, Heiner Stuckenschmidt, Margret Keuper
http://arxiv.org/abs/1912.05317v1
• [cs.CV]An Efficient Approach for Using Expectation Maximization Algorithm in Capsule Networks
Moein Hasani, Amin Nasim Saravi, Hassan Khotanlou
http://arxiv.org/abs/1912.05333v1
• [cs.CV]Associative Alignment for Few-shot Image Classification
Arman Afrasiyabi, Jean-François Lalonde, Christian Gagné
http://arxiv.org/abs/1912.05094v1
• [cs.CV]AugFPN: Improving Multi-scale Feature Learning for Object Detection
Chaoxu Guo, Bin Fan, Qian Zhang, Shiming Xiang, Chunhong Pan
http://arxiv.org/abs/1912.05384v1
• [cs.CV]Automatic Analysis of Sewer Pipes Based on Unrolled Monocular Fisheye Images
Johannes Künzel, Thomas Werner, Ronja Möller, Peter Eisert, Jan Waschnewski, Ralf Hilpert
http://arxiv.org/abs/1912.05222v1
• [cs.CV]Automatic quality assessment for 2D fetal sonographic standard plane based on multi-task learning
Hong Luo, Han Liu, Kejun Li, Bo Zhang
http://arxiv.org/abs/1912.05260v1
• [cs.CV]BioNet: Infusing Biomarker Prior into Global-to-Local Network for Choroid Segmentation in Optical Coherence Tomography Images
Huihong Zhang, Jianlong Yang, Kang Zhou, Zhenjie Chai, Jun Cheng, Shenghua Gao, Jiang Liu
http://arxiv.org/abs/1912.05090v1
• [cs.CV]Bipartite Conditional Random Fields for Panoptic Segmentation
Sadeep Jayasumana, Kanchana Ranasinghe, Mayuka Jayawardhana, Sahan Liyanaarachchi, Harsha Ranasinghe
http://arxiv.org/abs/1912.05307v1
• [cs.CV]Bottleneck detection by slope difference distribution: a robust approach for separating overlapped cells
ZhenZhou Wang
http://arxiv.org/abs/1912.05096v1
• [cs.CV]Boundary-Aware Salient Object Detection via Recurrent Two-Stream Guided Refinement Network
Fangting Lin, Chao Yang, Huizhou Li, Bin Jiang
http://arxiv.org/abs/1912.05236v1
• [cs.CV]Deep Adaptive Wavelet Network
Maria Ximena Bastidas Rodriguez, Adrien Gruson, Luisa F. Polania, Shin Fujieda, Flavio Prieto Ortiz, Kohei Takayama, Toshiya Hachisuka
http://arxiv.org/abs/1912.05035v1
• [cs.CV]Deep Direct Visual Odometry
Chaoqiang Zhao, Yang Tang, Qiyu Sun
http://arxiv.org/abs/1912.05101v1
• [cs.CV]DeepMeshFlow: Content Adaptive Mesh Deformation for Robust Image Registration
Nianjin Ye, Chuan Wang, Shuaicheng Liu, Lanpeng Jia, Jue Wang, Yongqing Cui
http://arxiv.org/abs/1912.05131v1
• [cs.CV]Fine-grained Classification of Rowing teams
M. J. A. van Wezel, L. J. Hamburger, Y. Napolean
http://arxiv.org/abs/1912.05393v1
• [cs.CV]FootAndBall: Integrated player and ball detector
Jacek Komorowski, Grzegorz Kurzejamski, Grzegorz Sarwas
http://arxiv.org/abs/1912.05445v1
• [cs.CV]GLU-Net: Global-Local Universal Network for Dense Flow and Correspondences
Prune Truong, Martin Danelljan, Radu Timofte
http://arxiv.org/abs/1912.05524v1
• [cs.CV]Graph-based Multi-view Binary Learning for Image Clustering
Guangqi Jiang, Huibing Wang, Jinjia Peng, Dongyan Chen, Xianping Fu
http://arxiv.org/abs/1912.05159v1
• [cs.CV]HistoNet: Predicting size histograms of object instances
Kishan Sharma, Moritz Gold, Christian Zurbruegg, Laura Leal-Taixé, Jan Dirk Wegner
http://arxiv.org/abs/1912.05227v1
• [cs.CV]HyperCon: Image-To-Video Model Transfer for Video-To-Video Translation Tasks
Ryan Szeto, Mostafa El-Khamy, Jungwon Lee, Jason J. Corso
http://arxiv.org/abs/1912.04950v1
• [cs.CV]IoU-uniform R-CNN: Breaking Through the Limitations of RPN
Li Zhu, Zihao Xie, Liman Liu, Bo Tao, Wenbing Tao
http://arxiv.org/abs/1912.05190v1
• [cs.CV]Lane Detection For Prototype Autonomous Vehicle
Sertap Kamçı, Dogukan Aksu, Muhammed Ali Aydin
http://arxiv.org/abs/1912.05220v1
• [cs.CV]Learning Domain Adaptive Features with Unlabeled Domain Bridges
Yichen Li, Xingchao Peng
http://arxiv.org/abs/1912.05004v1
• [cs.CV]Learning from Noisy Anchors for One-stage Object Detection
Hengduo Li, Zuxuan Wu, Chen Zhu, Caiming Xiong, Richard Socher, Larry S. Davis
http://arxiv.org/abs/1912.05086v1
• [cs.CV]Lifelong learning for text retrieval and recognition in historical handwritten document collections
Lambert Schomaker
http://arxiv.org/abs/1912.05156v1
• [cs.CV]MineGAN: effective knowledge transfer from GANs to target domains with few images
Yaxing Wang, Abel Gonzalez-Garcia, David Berga, Luis Herranz, Fahad Shahbaz Khan, Joost van de Weijer
http://arxiv.org/abs/1912.05270v1
• [cs.CV]Multimodal Self-Supervised Learning for Medical Image Analysis
Aiham Taleb, Christoph Lippert, Tassilo Klein, Moin Nabi
http://arxiv.org/abs/1912.05396v1
• [cs.CV]Parting with Illusions about Deep Active Learning
Sudhanshu Mittal, Maxim Tatarchenko, Özgün Çiçek, Thomas Brox
http://arxiv.org/abs/1912.05361v1
• [cs.CV]Pillar in Pillar: Multi-Scale and Dynamic Feature Extraction for 3D Object Detection in Point Clouds
Yonglin Tian, Lichao Huang, Xuesong Li, Yuan Li, Zilei Wang, Fei-Yue Wang
http://arxiv.org/abs/1912.04775v2
• [cs.CV]PuckNet: Estimating hockey puck location from broadcast video
Kanav Vats, William McNally, Chris Dulhanty, Zhong Qiu Lin, David A. Clausi, John Zelek
http://arxiv.org/abs/1912.05107v1
• [cs.CV]RDSNet: A New Deep Architecture for Reciprocal Object Detection and Instance Segmentation
Shaoru Wang, Yongchao Gong, Junliang Xing, Lichao Huang, Chang Huang, Weiming Hu
http://arxiv.org/abs/1912.05070v1
• [cs.CV]SKD: Unsupervised Keypoint Detecting for Point Clouds using Embedded Saliency Estimation
Georgi Tinchev, Adrian Penate-Sanchez, Maurice Fallon
http://arxiv.org/abs/1912.04943v1
• [cs.CV]Scalability in Perception for Autonomous Driving: An Open Dataset Benchmark
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Yu Zhang, Jon Shlens, Zhifeng Chen, Dragomir Anguelov
http://arxiv.org/abs/1912.04838v2
• [cs.CV]Self-Driving Car Steering Angle Prediction Based on Image Recognition
Shuyang Du, Haoli Guo, Andrew Simpson
http://arxiv.org/abs/1912.05440v1
• [cs.CV]SiamMan: Siamese Motion-aware Network for Visual Tracking
Wenzhang Zhou, Longyin Wen, Libo Zhang, Dawei Du, Tiejian Luo, Yanjun Wu
http://arxiv.org/abs/1912.05515v1
• [cs.CV]SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization
Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Golnaz Ghiasi, Mingxing Tan, Yin Cui, Quoc V. Le, Xiaodan Song
http://arxiv.org/abs/1912.05027v1
• [cs.CV]TANet: Robust 3D Object Detection from Point Clouds with Triple Attention
Zhe Liu, Xin Zhao, Tengteng Huang, Ruolan Hu, Yu Zhou, Xiang Bai
http://arxiv.org/abs/1912.05163v1
• [cs.CV]Towards Unsupervised Learning of Generative Models for 3D Controllable Image Synthesis
Yiyi Liao, Katja Schwarz, Lars Mescheder, Andreas Geiger
http://arxiv.org/abs/1912.05237v1
• [cs.CV]Training Deep SLAM on Single Frames
Igor Slinko, Anna Vorontsova, Dmitry Zhukov, Olga Barinova, Anton Konushin
http://arxiv.org/abs/1912.05405v1
• [cs.CV]Vectorizing World Buildings: Planar Graph Reconstruction by Primitive Detection and Relationship Classification
Nelson Nauata, Yasutaka Furukawa
http://arxiv.org/abs/1912.05135v1
• [cs.CV]What You See is What You Get: Exploiting Visibility for 3D Object Detection
Peiyun Hu, Jason Ziglar, David Held, Deva Ramanan
http://arxiv.org/abs/1912.04986v1
• [cs.CV]Why Can’t I Dance in the Mall? Learning to Mitigate Scene Bias in Action Recognition
Jinwoo Choi, Chen Gao, Joseph C. E. Messou, Jia-Bin Huang
http://arxiv.org/abs/1912.05534v1
• [cs.CY]A Stable Nuclear Future? The Impact of Autonomous Systems and Artificial Intelligence
Michael C. Horowitz, Paul Scharre, Alexander Velez-Green
http://arxiv.org/abs/1912.05291v1
• [cs.CY]Dynamic Algorithmic Service Agreements Perspective
Bogdana Rakova, Laura Kahn
http://arxiv.org/abs/1912.04947v1
• [cs.CY]Female Librarians and Male Computer Programmers? Gender Bias in Occupational Images on Digital Media Platforms
Vivek Singh, Mary Chayko, Raj Inamdar, Diana Floegel
http://arxiv.org/abs/1912.05474v1
• [cs.CY]Measurement and Fairness
Abigail Z. Jacobs, Hanna Wallach
http://arxiv.org/abs/1912.05511v1
• [cs.CY]Minority report detection in refugee-authored community-driven journalism using RBMs
Bogdana Rakova, Nick DePalma
http://arxiv.org/abs/1912.04953v1
• [cs.CY]The Hidden Assumptions Behind Counterfactual Explanations and Principal Reasons
Solon Barocas, Andrew D. Selbst, Manish Raghavan
http://arxiv.org/abs/1912.04930v1
• [cs.DC]DGEMM performance is data-dependent
Tom Cornebize, Arnaud Legrand
http://arxiv.org/abs/1912.05381v1
• [cs.DC]Energy-aware Scheduling of Jobs in Heterogeneous Cluster Systems Using Deep Reinforcement Learning
Amirhossein Esmaili, Massoud Pedram
http://arxiv.org/abs/1912.05160v1
• [cs.DC]Performance Analysis of the Libra Blockchain: An Experimental Study
Jiashuo Zhang, Jianbo Gao, Zhenhao Wu, Wentian Yan, Qize Wu, Qingshan Li, Zhong Chen
http://arxiv.org/abs/1912.05241v1
• [cs.DC]Simulation of the Bitcoin Network Considering Compact Block Relay and Internet Improvements
Ryunosuke Nagayama, Kazuyuki Shudo, Ryohei Banno
http://arxiv.org/abs/1912.05208v1
• [cs.DS]Graph Sparsification for Derandomizing Massively Parallel Computation with Low Space
Artur Czumaj, Peter Davies, Merav Parter
http://arxiv.org/abs/1912.05390v1
• [cs.GR]Modelling curvature of a bent paper leaf
Sasikanth Raghava Goteti
http://arxiv.org/abs/1912.04898v1
• [cs.HC]Efficient crowdsourcing of crowd-generated microtasks
Abigail Hotaling, James P. Bagrow
http://arxiv.org/abs/1912.05045v1
• [cs.IR]Character 3-gram Mover’s Distance: An Effective Method for Detecting Near-duplicate Japanese-language Recipes
Masaki Oguni, Yohei Seki, Yu Hirate
http://arxiv.org/abs/1912.05171v1
• [cs.IR]It Runs in the Family: Searching for Similar Names using Digitized Family Trees
Aviad Elyashar, Rami Puzis, Michael Fire
http://arxiv.org/abs/1912.04003v2
• [cs.IT]A Cooperative Spectrum Sensing Scheme Based on Compressive Sensing for Cognitive Radio Networks
Fatima Salahdine, Elias Ghribi, Naima Kaabouch
http://arxiv.org/abs/1912.04935v1
• [cs.IT]Beyond Dirty Paper Coding for Multi-Antenna Broadcast Channel with Partial CSIT: A Rate-Splitting Approach
Yijie Mao, Bruno Clerckx
http://arxiv.org/abs/1912.05409v1
• [cs.IT]Concept and Experimental Demonstration of Optical IM/DD End-to-End System Optimization using a Generative Model
Boris Karanov, Mathieu Chagnon, Vahid Aref, Domaniç Lavery, Polina Bayvel, Laurent Schmalen
http://arxiv.org/abs/1912.05146v1
• [cs.IT]Constructions of quasi-twisted quantum codes
Jingjie Lv, Ruihu Li, Junli Wang
http://arxiv.org/abs/1912.05142v1
• [cs.IT]Distance Distributions of Cyclic Orbit Codes
Heide Gluesing-Luerssen, Hunter Lehmann
http://arxiv.org/abs/1912.05522v1
• [cs.IT]Mutual Information in Community Detection with Covariate Information and Correlated Networks
Vaishakhi Mayya, Galen Reeves
http://arxiv.org/abs/1912.05375v1
• [cs.IT]Reconfigurable Intelligent Surfaces: Bridging the gap between scattering and reflection
J. Bucheli Garcia, A. Sibille, M. Kamoun
http://arxiv.org/abs/1912.05344v1
• [cs.LG]A Two-Stage Approach to Few-Shot Learning for Image Recognition
Debasmit Das, C. S. George Lee
http://arxiv.org/abs/1912.04973v1
• [cs.LG]Advances and Open Problems in Federated Learning
Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Keith Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D’Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaid Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konečný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao
http://arxiv.org/abs/1912.04977v1
• [cs.LG]Almost Uniform Sampling From Neural Networks
Changlong Wu, Narayana Prasad Santhanam
http://arxiv.org/abs/1912.04994v1
• [cs.LG]An Improving Framework of regularization for Network Compression
E Zhenqian, Gao Weiguo
http://arxiv.org/abs/1912.05078v1
• [cs.LG]Before we can find a model, we must forget about perfection
Dimiter Dobrev
http://arxiv.org/abs/1912.04964v1
• [cs.LG]Deep Relevance Regularization: Interpretable and Robust Tumor Typing of Imaging Mass Spectrometry Data
Christian Etmann, Maximilian Schmidt, Jens Behrmann, Tobias Boskamp, Lena Hauberg-Lotte, Annette Peter, Rita Casadonte, Jörg Kriegsmann, Peter Maass
http://arxiv.org/abs/1912.05459v1
• [cs.LG]Detecting and Correcting Adversarial Images Using Image Processing Operations and Convolutional Neural Networks
Huy H. Nguyen, Minoru Kuribayashi, Junichi Yamagishi, Isao Echizen
http://arxiv.org/abs/1912.05391v1
• [cs.LG]Doubly Robust Off-Policy Actor-Critic Algorithms for Reinforcement Learning
Riashat Islam, Raihan Seraj, Samin Yeasar Arnob, Doina Precup
http://arxiv.org/abs/1912.05109v1
• [cs.LG]Efficient and Robust Reinforcement Learning with Uncertainty-based Value Expansion
Bo Zhou, Hongsheng Zeng, Fan Wang, Yunxiang Li, Hao Tian
http://arxiv.org/abs/1912.05328v1
• [cs.LG]Entropy Regularization with Discounted Future State Distribution in Policy Gradient Methods
Riashat Islam, Raihan Seraj, Pierre-Luc Bacon, Doina Precup
http://arxiv.org/abs/1912.05104v1
• [cs.LG]Event Outcome Prediction using Sentiment Analysis and Crowd Wisdom in Microblog Feeds
Rahul Radhakrishnan Iyer, Ronghuo Zheng, Yuezhang Li, Katia Sycara
http://arxiv.org/abs/1912.05066v1
• [cs.LG]Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approaches
Kacper Sokol, Peter Flach
http://arxiv.org/abs/1912.05100v1
• [cs.LG]Identifying Mislabeled Instances in Classification Datasets
Nicolas Michael Müller, Karla Markert
http://arxiv.org/abs/1912.05283v1
• [cs.LG]Image Classification with Deep Learning in the Presence of Noisy Labels: A Survey
Görkem Algan, Ilkay Ulusoy
http://arxiv.org/abs/1912.05170v1
• [cs.LG]Imitation Learning via Off-Policy Distribution Matching
Ilya Kostrikov, Ofir Nachum, Jonathan Tompson
http://arxiv.org/abs/1912.05032v1
• [cs.LG]Is Feature Diversity Necessary in Neural Network Initialization?
Yaniv Blumenfeld, Dar Gilboda, Daniel Soudry
http://arxiv.org/abs/1912.05137v1
• [cs.LG]Just Add Functions: A Neural-Symbolic Language Model
David Demeter, Doug Downey
http://arxiv.org/abs/1912.05421v1
• [cs.LG]Marginalized State Distribution Entropy Regularization in Policy Optimization
Riashat Islam, Zafarali Ahmed, Doina Precup
http://arxiv.org/abs/1912.05128v1
• [cs.LG]Multimodal Generative Models for Compositional Representation Learning
Mike Wu, Noah Goodman
http://arxiv.org/abs/1912.05075v1
• [cs.LG]On Neural Learnability of Chaotic Dynamics
Ziwei Li, Sai Ravela
http://arxiv.org/abs/1912.05081v1
• [cs.LG]Recurrent Transform Learning
Megha Gupta, Angshul Majumdar
http://arxiv.org/abs/1912.05198v1
• [cs.LG]SMAUG: End-to-End Full-Stack Simulation Infrastructure for Deep Learning Workloads
Sam Likun Xi, Yuan Yao, Kshitij Bhardwaj, Paul Whatmough, Gu-Yeon Wei, David Brooks
http://arxiv.org/abs/1912.04481v2
• [cs.LG]SMiRL: Surprise Minimizing RL in Dynamic Environments
Glen Berseth, Daniel Geng, Coline Devin, Chelsea Finn, Dinesh Jayaraman, Sergey Levine
http://arxiv.org/abs/1912.05510v1
• [cs.LG]Towards Better Forecasting by Fusing Near and Distant Future Visions
Jiezhu Cheng, Kaizhu Huang, Zibin Zheng
http://arxiv.org/abs/1912.05122v1
• [cs.LG]Unsupervised Feature Selection based on Adaptive Similarity Learning and Subspace Clustering
Mohsen Ghassemi Parsa, Hadi Zare, Mehdi Ghatee
http://arxiv.org/abs/1912.05458v1
• [cs.LG]Unsupervised Transfer Learning via BERT Neuron Selection
Mehrdad Valipour, En-Shiun Annie Lee, Jaime R. Jamacaro, Carolina Bessega
http://arxiv.org/abs/1912.05308v1
• [cs.LG]Value-of-Information based Arbitration between Model-based and Model-free Control
Krishn Bera, Yash Mandilwar, Bapi Raju
http://arxiv.org/abs/1912.05453v1
• [cs.LG]Variational Learning with Disentanglement-PyTorch
Amir H. Abdi, Purang Abolmaesumi, Sidney Fels
http://arxiv.org/abs/1912.05184v1
• [cs.MA]Jason-RS, a Collaboration between Agents and an IoT Platform
Hantanirina Felixie, Jean Razafindramintsa, Sylvain Cherrier, Thomas Mahatody, Laurent George, Victor Manantsoa
http://arxiv.org/abs/1912.05362v1
• [cs.NE]Efficacy of Modern Neuro-Evolutionary Strategies for Continuous Control Optimization
Paolo Pagliuca, Nicola Milano, Stefano Nolfi
http://arxiv.org/abs/1912.05239v1
• [cs.NI]Blockchain for 5G and Beyond Networks: A State of the Art Survey
Dinh C Nguyen, Pubudu N Pathirana, Ming Ding, Aruna Seneviratne
http://arxiv.org/abs/1912.05062v1
• [cs.PL]Array Languages Make Neural Networks Fast
Artjoms Šinkarovs, Hans-Nikolai Vießmann, Sven-Bodo Scholz
http://arxiv.org/abs/1912.05234v1
• [cs.RO]Efficient Robotic Task Generalization Using Deep Model Fusion Reinforcement Learning
Tianying Wang, Hao Zhang, Wei Qi Toh, Hongyuan Zhu, Cheston Tan, Yan Wu, Yong Liu, Wei Jing
http://arxiv.org/abs/1912.05205v1
• [cs.RO]Learning to Optimally Segment Point Clouds
Peiyun Hu, David Held, Deva Ramanan
http://arxiv.org/abs/1912.04976v1
• [cs.RO]RoboCoDraw: Robotic Avatar Drawing with GAN-based Style Transfer and Time-efficient Path Optimization
Tianying Wang, Wei Qi Toh, Hao Zhang, Xiuchao Sui, Shaohua Li, Yong Liu, Wei Jing
http://arxiv.org/abs/1912.05099v1
• [cs.RO]Zero-shot generalization using cascaded system-representations
Ashish Malik
http://arxiv.org/abs/1912.05501v1
• [cs.SD]Small-footprint Keyword Spotting with Graph Convolutional Network
Xi Chen, Shouyi Yin, Dandan Song, Peng Ouyang, Leibo Liu, Shaojun Wei
http://arxiv.org/abs/1912.05124v1
• [cs.SD]Voice Conversion for Whispered Speech Synthesis
Marius Cotescu, Thomas Drugman, Goeric Huybrechts, Jaime Lorenzo-Trueba, Alexis Moinet
http://arxiv.org/abs/1912.05289v1
• [cs.SE]A Reference Architecture and Modelling Principles for Architectural Stability based on Self-Awareness: Case of Cloud Architectures
Maria Salama, Rami Bahsoon, Rajkumar Buyya
http://arxiv.org/abs/1912.05517v1
• [cs.SE]Datamorphic Testing: A Methodology for Testing AI Applications
Hong Zhu, Dongmei Liu, Ian Bayley, Rachel Harrison, Fabio Cuzzolin
http://arxiv.org/abs/1912.04900v1
• [cs.SI]Beyond Node Embedding: A Direct Unsupervised Edge Representation Framework for Homogeneous Networks
Sambaran Bandyopadhyay, Anirban Biswas, M. N. Murty, Ramasuri Narayanam
http://arxiv.org/abs/1912.05140v1
• [cs.SI]Collective Identity Formation on Instagram — Investigating the Social Movement Fridays for Future
Felix Brünker, Fabian Deitelhoff, Milad Mirbabaie
http://arxiv.org/abs/1912.05123v1
• [eess.AS]Advances in Online Audio-Visual Meeting Transcription
Takuya Yoshioka, Igor Abramovski, Cem Aksoylar, Zhuo Chen, Moshe David, Dimitrios Dimitriadis, Yifan Gong, Ilya Gurvich, Xuedong Huang, Yan Huang, Aviv Hurvitz, Li Jiang, Sharon Koubi, Eyal Krupka, Ido Leichter, Changliang Liu, Partha Parthasarathy, Alon Vinnikov, Lingfeng Wu, Xiong Xiao, Wayne Xiong, Huaming Wang, Zhenghao Wang, Jun Zhang, Yong Zhao, Tianyan Zhou
http://arxiv.org/abs/1912.04979v1
• [eess.AS]Audiogmenter: a MATLAB Toolbox for Audio Data Augmentation
Gianluca Maguolo, Michelangelo Paci, Loris Nanni, Ludovico Bonan
http://arxiv.org/abs/1912.05472v1
• [eess.AS]SpecAugment on Large Scale Datasets
Daniel S. Park, Yu Zhang, Chung-Cheng Chiu, Youzheng Chen, Bo Li, William Chan, Quoc V. Le, Yonghui Wu
http://arxiv.org/abs/1912.05533v1
• [eess.IV]$Σ$-net: Ensembled Iterative Deep Neural Networks for Accelerated Parallel MR Image Reconstruction
Jo Schlemper, Chen Qin, Jinming Duan, Ronald M. Summers, Kerstin Hammernik
http://arxiv.org/abs/1912.05480v1
• [eess.IV]BINet: a binary inpainting network for deep patch-based image compression
André Nortje, Willie Brink, Herman A. Engelbrecht, Herman Kamper
http://arxiv.org/abs/1912.05189v1
• [eess.IV]Deep Learning-based Denoising of Mammographic Images using Physics-driven Data Augmentation
Dominik Eckert, Sulaiman Vesal, Ludwig Ritschl, Steffen Kappler, Andreas Maier
http://arxiv.org/abs/1912.05240v1
• [eess.IV]Deep motion estimation for parallel inter-frame prediction in video compression
André Nortje, Herman A. Engelbrecht, Herman Kamper
http://arxiv.org/abs/1912.05193v1
• [eess.IV]Feeding the zombies: Synthesizing brain volumes using a 3D progressive growing GAN
Anders Eklund
http://arxiv.org/abs/1912.05357v1
• [eess.IV]Memory-efficient Learning for Large-scale Computational Imaging
Michael Kellman, Jon Tamir, Emrah Boston, Michael Lustig, Laura Waller
http://arxiv.org/abs/1912.05098v1
• [eess.IV]Multi-Dimension Modulation for Image Restoration with Dynamic Controllable Residual Learning
Jingwen He, Chao Dong, Yu Qiao
http://arxiv.org/abs/1912.05293v1
• [eess.IV]Phase Retrieval using Conditional Generative Adversarial Networks
Tobias Uelwer, Alexander Oberstraß, Stefan Harmeling
http://arxiv.org/abs/1912.04981v1
• [eess.IV]U-Net with spatial pyramid pooling for drusen segmentation in optical coherence tomography
Rhona Asgari, Sebastian Waldstein, Ferdinand Schlanitz, Magdalena Baratsits, Ursula Schmidt-Erfurth, Hrvoje Bogunović
http://arxiv.org/abs/1912.05404v1
• [eess.IV]UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation
Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, Jianming Liang
http://arxiv.org/abs/1912.05074v1
• [eess.IV]Variable Rate Deep Image Compression with Modulated Autoencoder
Fei Yang, Luis Herranz, Joost van de Weijer, José A. Iglesias Guitián, Antonio López, Mikhail Mozerov
http://arxiv.org/abs/1912.05526v1
• [eess.IV]Wide-Area Land Cover Mapping with Sentinel-1 Imagery using Deep Learning Semantic Segmentation Models
Sanja Šćepanović, Oleg Antropov, Pekka Laurila, Vladimir Ignatenko, Jaan Praks
http://arxiv.org/abs/1912.05067v1
• [eess.SP]Low-Complexity LSTM-Assisted Bit-Flipping Algorithm for Successive Cancellation List Polar Decoder
Chun-Hsiang Chen, Chieh-Fang Teng, An-Yeu Wu
http://arxiv.org/abs/1912.05158v1
• [eess.SP]Neural Memory Networks for Robust Classification of Seizure Type
David Ahmedt-Aristizabal, Tharindu Fernando, Simon Denman, Lars Petersson, Matthew J. Aburn, Clinton Fookes
http://arxiv.org/abs/1912.04968v1
• [eess.SP]SenseNet: Deep Learning based Wideband spectrum sensing and modulation classification network
Shivam Chandhok, Himani Joshi, A V Subramanyam, Sumit J. Darak
http://arxiv.org/abs/1912.05255v1
• [eess.SP]Severity Detection Tool for Patients with Infectious Disease
Girmaw Abebe Tadesse, Tingting Zhu, Nhan Le Nguyen Thanh, Nguyen Thanh Hung, Ha Thi Hai Duong, Truong Huu Khanh, Pham Van Quang, Duc Duong Tran, LamMinh Yen, H Rogier Van Doorn, Nguyen Van Hao, John Prince, Hamza Javed, DaniKiyasseh, Le Van Tan, Louise Thwaites, David A. Clifton
http://arxiv.org/abs/1912.05345v1
• [eess.SP]Sparse Joint Transmission for Cell-Free Massive MIMO: A Sparse PCA Approach
Deokhwan Han, Jeonghun Park, Namyoon Lee
http://arxiv.org/abs/1912.05231v1
• [eess.SY]Event Detection in Micro-PMU Data: A Generative Adversarial Network Scoring Method
Armin Aligholian, Alireza Shahsavari, Ed Cortez, Emma Stewart, Hamed Mohsenian-Rad
http://arxiv.org/abs/1912.05103v1
• [math.CO]Integer Partitions Probability Distributions
Andrew V. Sills
http://arxiv.org/abs/1912.05306v1
• [math.NA]Tensor Completion via Gaussian Process Based Initialization
Yermek Kapushev, Ivan Oseledets, Evgeny Burnaev
http://arxiv.org/abs/1912.05179v1
• [math.PR]Mean-Field Neural ODEs via Relaxed Optimal Control
Jean-François Jabir, David Šiška, Łukasz Szpruch
http://arxiv.org/abs/1912.05475v1
• [math.PR]Quantitative Universality for the Largest Eigenvalue of Sample Covariance Matrices
Haoyu Wang
http://arxiv.org/abs/1912.05473v1
• [math.ST]Analysis of the rate of convergence of neural network regression estimates which are easy to implement
Alina Braun, Michael Kohler, Adam Krzyzak
http://arxiv.org/abs/1912.05436v1
• [math.ST]Frequentist Consistency of Generalized Variational Inference
Jeremias Knoblauch
http://arxiv.org/abs/1912.04946v1
• [math.ST]Testing Independence with the Binary Expansion Randomized Ensemble Test
Duyeol Lee, Kai Zhang, Michael R. Kosorok
http://arxiv.org/abs/1912.03662v2
• [stat.AP]Bayesian Framework for Simultaneous Registration and Estimation of Noisy, Sparse and Fragmented Functional Data
James Matuk, Karthik Bharath, Oksana Chkrebtii, Sebastian Kurtek
http://arxiv.org/abs/1912.05125v1
• [stat.AP]European banks’ business models and their credit risk: A cluster analysis in a high-dimensional context
Matteo Farnè, Angelos T. Vouldis
http://arxiv.org/abs/1912.05025v1
• [stat.AP]Measuring Spatial Allocative Efficiency in Basketball
Nathan Sandholtz, Jacob Mortensen, Luke Bornn
http://arxiv.org/abs/1912.05129v1
• [stat.AP]Robust joint modelling of longitudinal and survival data with a time-varying degrees-of-freedom parameter
Lisa McFetridge, Ozgur Asar, Jonas Wallin
http://arxiv.org/abs/1912.05133v1
• [stat.ME]Asymptotic based bootstrap approach for matched pairs with missingness in a single-arm
Lubna Amro, Markus Pauly, Burim Ramosaj
http://arxiv.org/abs/1912.04902v1
• [stat.ME]Bayesian Copula Density Deconvolution for Zero-Inflated Data in Nutritional Epidemiology
Abhra Sarkar, Debdeep Pati, Bani K. Mallick, Raymond J. Carroll
http://arxiv.org/abs/1912.05084v1
• [stat.ME]Center-outward quantiles and the measurement of multivariate risk
Jan Beirlant, Sven Buitendag, Eustasio del Bario, Marc Hallin
http://arxiv.org/abs/1912.04924v1
• [stat.ME]Integrative Generalized Convex Clustering Optimization and Feature Selection for Mixed Multi-View Data
Minjie Wang, Genevera I. Allen
http://arxiv.org/abs/1912.05449v1
• [stat.ME]More for less: Predicting and maximizing genetic variant discovery via Bayesian nonparametrics
Lorenzo Masoero, Federico Camerlenghi, Stefano Favaro, Tamara Broderick
http://arxiv.org/abs/1912.05516v1
• [stat.ME]Nonparametric Universal Copula Modeling
Subhadeep Mukhopadhyay, Emanuel Parzen
http://arxiv.org/abs/1912.05503v1
• [stat.ME]Sample Size Estimation using a Latent Variable Model for Mixed Outcome Co-Primary, Multiple Primary and Composite Endpoints
Martina McMenamin, Jessica K. Barrett, Anna Berglind, James M. S. Wason
http://arxiv.org/abs/1912.05258v1
• [stat.ML]A Closer Look at Disentangling in $β$-VAE
Harshvardhan Sikka, Weishun Zhong, Jun Yin, Cengiz Pehlevan
http://arxiv.org/abs/1912.05127v1
• [stat.ML]Fenton-Wilkinson Order Statistics and German Tanks: A Case Study of an Orienteering Relay Race
Joonas Pääkkönen
http://arxiv.org/abs/1912.05034v1
• [stat.ML]Representational Rényi heterogeneity
Abraham Nunes, Martin Alda, Timothy Bardouille, Thomas Trappenberg
http://arxiv.org/abs/1912.05031v1
• [stat.ML]Sampling for Bayesian Mixture Models: MCMC with Polynomial-Time Mixing
Wenlong Mou, Nhat Ho, Martin J. Wainwright, Peter L. Bartlett, Michael I. Jordan
http://arxiv.org/abs/1912.05153v1
• [stat.ML]Statistically Robust Neural Network Classification
Benjie Wang, Stefan Webb, Tom Rainforth
http://arxiv.org/abs/1912.04884v2
• [stat.ML]The Wasserstein-Fourier Distance for Stationary Time Series
Elsa Cazelles, Arnaud Robert, Felipe Tobar
http://arxiv.org/abs/1912.05509v1