astro-ph.CO - 宇宙学和天体物理学
astro-ph.SR - 太阳和天体物理学恒星
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.HC - 人机接口
cs.IR - 信息检索
cs.IT - 信息论
cs.LG - 自动学习
cs.MM - 多媒体
cs.NE - 神经与进化计算
cs.RO - 机器人学
cs.SD - 声音处理
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
math.OC - 优化与控制
math.ST - 统计理论
physics.soc-ph - 物理学与社会
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
• [astro-ph.CO]Primordial non-Gaussianity from the Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey I: Catalogue Preparation and Systematic Mitigation
• [astro-ph.SR]Nonparametric monitoring of sunspot number observations: a case study
• [cs.AI]Dealing with Expert Bias in Collective Decision-Making
• [cs.CL]A Source-Criticism Debiasing Method for GloVe Embeddings
• [cs.CL]Adapt-and-Distill: Developing Small, Fast and Effective Pretrained Language Models for Domains
• [cs.CL]Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models
• [cs.CL]DeltaLM: Encoder-Decoder Pre-training for Language Generation and Translation by Augmenting Pretrained Multilingual Encoders
• [cs.CL]Exploring the Representation of Word Meanings in Context: A Case Study on Homonymy and Synonymy
• [cs.CL]JNLP Team: Deep Learning Approaches for Legal Processing Tasks in COLIEE 2021
• [cs.CL]Language Models are Good Translators
• [cs.CL]Learning to Sample Replacements for ELECTRA Pre-Training
• [cs.CL]Manually Annotated Spelling Error Corpus for Amharic
• [cs.CL]ParaLaw Nets — Cross-lingual Sentence-level Pretraining for Legal Text Processing
• [cs.CR]Vulnerability and Transaction behavior based detection of Malicious Smart Contracts
• [cs.CV]”Zero Shot” Point Cloud Upsampling
• [cs.CV]A Picture May Be Worth a Hundred Words for Visual Question Answering
• [cs.CV]Animatable Neural Radiance Fields from Monocular RGB Video
• [cs.CV]Building Intelligent Autonomous Navigation Agents
• [cs.CV]Connecting Sphere Manifolds Hierarchically for Regularization
• [cs.CV]Countering Adversarial Examples: Combining Input Transformation and Noisy Traini
146b
ng
• [cs.CV]Diversifying Semantic Image Synthesis and Editing via Class- and Layer-wise VAEs
• [cs.CV]DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrieval
• [cs.CV]Efficient Document Image Classification Using Region-Based Graph Neural Network
• [cs.CV]Generative Modeling for Multi-task Visual Learning
• [cs.CV]Graph Pattern Loss based Diversified Attention Network for Cross-Modal Retrieval
• [cs.CV]Hierarchical Object-oriented Spatio-Temporal Reasoning for Video Question Answering
• [cs.CV]Image-to-image Transformation with Auxiliary Condition
• [cs.CV]Interactive Multi-level Stroke Control for Neural Style Transfer
• [cs.CV]Interpreting Depression From Question-wise Long-term Video Recording of SDS Evaluation
• [cs.CV]NP-DRAW: A Non-Parametric Structured Latent Variable Modelfor Image Generation
• [cs.CV]On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy
• [cs.CV]PVTv2: Improved Baselines with Pyramid Vision Transformer
• [cs.CV]Partially fake it till you make it: mixing real and fake thermal images for improved object detection
• [cs.CV]Probing Inter-modality: Visual Parsing with Self-Attention for Vision-Language Pre-training
• [cs.CV]Projection-wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape Analysis
• [cs.CV]SRPN: similarity-based region proposal networks for nuclei and cells detection in histology images
• [cs.CV]Shape registration in the time of transformers
• [cs.CV]Single Image Texture Translation for Data Augmentation
• [cs.CV]Video Moment Retrieval with Text Query Considering Many-to-Many Correspondence Using Potentially Relevant Pair
• [cs.CV]Vision Transformer Architecture Search
• [cs.CY]Fairness Deconstructed: A Sociotechnical View of ‘Fair’ Algorithms in Criminal Justice
• [cs.CY]On Fairness and Interpretability
• [cs.CY]The Tale of Two Localization Technologies: Enabling Accurate Low-Overhead WiFi-based Localization for Low-end Phones
• [cs.DC]CEAZ: Accelerating Parallel I/O via Hardware-Algorithm Co-Design of Efficient and Adaptive Lossy Compression
• [cs.DC]Cost-efficient, QoS and Security aware Placement of Smart Farming IoT Applications in Cloud-Fog Infrastructure
• [cs.DC]FLASH 1.0: A Software Framework for Rapid Parallel Deployment and Enhancing Host Code Portability in Heterogeneous Computing
• [cs.DC]Introducing OpenMP Tasks into the HYDRO Benchmark
• [cs.DC]Overcoming barriers to scalability in variational quantum Monte Carlo
• [cs.DC]The Problem of Distributed Consensus: A Survey
• [cs.DS]The Price of Tolerance in Distribution Testing
• [cs.HC]Advancing Methodology for Social Science Research Using Alternate Reality Games: Proof-of-Concept Through Measuring Individual Differences and Adaptability and their impact on Team Performance
• [cs.IR]A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models
• [cs.IR]Balancing Accuracy and Fairness for Interactive Recommendation with Reinforcement Learning
• [cs.IR]Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature
• [cs.IR]Interactive query expansion for professional search applications
• [cs.IR]TableSense: Spreadsheet Table Detection with Convolutional Neural Networks
• [cs.IT]An Edge Computing Paradigm for Massive IoT Connectivity over High-Altitude Platform Networks
• [cs.IT]Beam Alignment in mmWave User-Centric Cell-Free Massive MIMO Systems
• [cs.IT]Doubly-Exponential Identification via Channels: Code Constructions and Bounds
• [cs.IT]Guessing Based on Compressed Side Information
• [cs.IT]Multi-player Multi-armed Bandits with Collision-Dependent Reward Distributions
• [cs.IT]Pilot Contamination Elimination for Channel Estimation with Complete Knowledge of Large-Scale Fading in Downlink Massive MIMO Systems
• [cs.LG]A hybrid model-based and learning-based approach for classification using limited number of training samples
• [cs.LG]A mechanistic-based data-driven approach to accelerate structural topology optimization through finite element convolutional neural network (FE-CNN)
• [cs.LG]Assessing Generalization of SGD via Disagreement
• [cs.LG]Assessing the Lockdown Effects on Air Quality during COVID-19 Era
• [cs.LG]Bayesian Inference in High-Dimensional Time-Serieswith the Orthogonal Stochastic Linear Mixing Model
• [cs.LG]Branch Prediction as a Reinforcement Learning Problem: Why, How and Case Studies
• [cs.LG]CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals
• [cs.LG]Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote
• [cs.LG]Conjugate Energy-Based Models
• [cs.LG]Data efficiency in graph networks through equivariance
• [cs.LG]Data-based Design of Inferential Sensors for Petrochemical Industry
• [cs.LG]Deep Interpretable Criminal Charge Prediction and Algorithmic Bias
• [cs.LG]DeepLoc: A Ubiquitous Accurate and Low-Overhead Outdoor Cellular Localization System
• [cs.LG]Federated Graph Classification over Non-IID Graphs
• [cs.LG]Federated Noisy Client Learning
• [cs.LG]Fine-grained Geolocation Prediction of Tweets with Human Machine Collaboration
• [cs.LG]Fostering Diversity in Spatial Evolutionary Generative Adversarial Networks
• [cs.LG]HyperNP: Interactive Visual Exploration of Multidimensional Projection Hyperparameters
• [cs.LG]Jitter:
8f0
Random Jittering Loss Function
• [cs.LG]Learning Gradual Argumentation Frameworks using Genetic Algorithms
• [cs.LG]Limitations of machine learning for building energy prediction: ASHRAE Great Energy Predictor III Kaggle competition error analysis
• [cs.LG]Littlestone Classes are Privately Online Learnable
• [cs.LG]Model-Based Reinforcement Learning via Latent-Space Collocation
• [cs.LG]Multi-Domain Active Learning: A Comparative Study
• [cs.LG]Multi-Goal Reinforcement Learning environments for simulated Franka Emika Panda robot
• [cs.LG]Multitask Learning for Citation Purpose Classification
• [cs.LG]On the (Un-)Avoidability of Adversarial Examples
• [cs.LG]Private Adaptive Gradient Methods for Convex Optimization
• [cs.LG]Privileged Zero-Shot AutoML
• [cs.LG]Proxy Convexity: A Unified Framework for the Analysis of Neural Networks Trained by Gradient Descent
• [cs.LG]Ranger21: a synergistic deep learning optimizer
• [cs.LG]Re-parameterizing VAEs for stability
• [cs.LG]Reliable Graph Neural Network Explanations Through Adversarial Training
• [cs.LG]Robust Matrix Factorization with Grouping Effect
• [cs.LG]Self-training Converts Weak Learners to Strong Learners in Mixture Models
• [cs.LG]Subgraph Federated Learning with Missing Neighbor Generation
• [cs.LG]Temporal Graph Signal Decomposition
• [cs.LG]Tensor-based framework for training flexible neural networks
• [cs.LG]Transient Stability Analysis with Physics-Informed Neural Networks
• [cs.LG]Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy
• [cs.LG]VEGN: Variant Effect Prediction with Graph Neural Networks
• [cs.LG]What will it take to generate fairness-preserving explanations?
• [cs.MM]Multiview Video Compression Using Advanced HEVC Screen Content Coding
• [cs.NE]A nonlinear hidden layer enables actor-critic agents to learn multiple paired association navigation
• [cs.RO]Active Learning in Robotics: A Review of Control Principles
• [cs.RO]Brax — A Differentiable Physics Engine for Large Scale Rigid Body Simulation
• [cs.RO]Collision Avoidance for Unmanned Aerial Vehicles in the Presence of Static and Moving Obstacles
• [cs.RO]Distributed IDA-PBC for a Class of Nonholonomic Mechanical Systems
• [cs.RO]Factor Graphs for Heterogeneous Bayesian Decentralized Data Fusion
• [cs.RO]Move Beyond Trajectories: Distribution Space Coupling for Crowd Navigation
• [cs.RO]Multi-Robot Deep Reinforcement Learning for Mobile Navigation
• [cs.RO]Navigating A Mobile Robot Using Switching Distributed Sensor Networks
• [cs.RO]Non-Parametric Neuro-Adaptive Control Subject to Task Specifications
• [cs.RO]Scalable Perception-Action-Communication Loops with Convolutional and Graph Neural Networks
• [cs.RO]Task-Driven Out-of-Distribution Detection with Statistical Guarantees for Robot Learning
• [cs.SD]Deep Residual Echo Suppression with A Tunable Tradeoff Between Signal Distortion and Echo Suppression
• [cs.SD]Evaluation of Deep-Learning-Based Voice Activity Detectors and Room Impulse Response Models in Reverberant Environments
• [cs.SD]Nonlinear Acoustic Echo Cancellation with Deep Learning
• [cs.SD]Phoneme-aware and Channel-wise Attentive Learning for Text DependentSpeaker Verification
• [cs.SD]Preliminary study on using vector quantization latent spaces for TTS/VC systems with consistent performance
• [cs.SD]Voice Activity Detection for Transient Noisy Environment Based on Diffusion Nets
• [cs.SI]Edge based stochastic block model statistical inference
• [cs.SI]Exposing individual differences through network topology
• [cs.SI]Graph space: using both geometric and probabilistic structure to evaluate statistical graph models
• [cs.SI]Louvain-like Methods for Community Detection in Multi-Layer Networks
• [cs.SI]Trends, Politics, Sentiments, and Misinformation: Understanding People’s Reactions to COVID-19 During its Early Stages
• [eess.AS]Online Self-Attentive Gated RNNs for Real-Time Speaker Separation
• [eess.IV]A Novel Self-Learning Framework for Bladder Cancer Grading Using Histopathological Images
• [eess.IV]Circumpapillary OCT-Focused Hybrid Learning for Glaucoma Grading Using Tailored Prototypical Neural Networks
• [eess.IV]Semantic annotation for computational pathology: Multidisciplinary experience and best practice recommendations
• [eess.SP]The Effect of Ground Truth Accuracy on the Evaluation of Localization Systems
• [math.OC]IPM-HLSP: An Efficient Interior-Point Method for Hierarchical Least-Squares Programs
• [math.OC]A proximal-proximal majorization-minimization algorithm for nonconvex tuning-free robust regression problems
• [math.OC]Binary Matrix Factorisation and Completion via Integer Programming
• [math.OC]Reinforcement Learning for Mean Field Games, with Applications to Economics
• [math.ST]On a Projection Estimator of the Regression Function Derivative
• [math.ST]Parameter Estimation for the McKean-Vlasov Stochastic Differential Equation
• [math.ST]Semi-supervised multiple testing
• [physics.soc-ph]Stochastic modeling of scientific impact
• [quant-ph]Temporal Modes of Light in Satellite-to-Earth Quantum Communications
• [stat.AP]Implementation of an alternative method for assessing competing risks: restricted mean time lost
• [stat.AP]Optimal Accelerated Degradation Testing Based on Bivariate Gamma Process with Dependent Components
• [stat.AP]Robust Real-Time Delay Predictions in a Network of High-Frequency Urban Buses
• [stat.AP]Uncertainty-aware Validation Benchmarks for Coupling Free Flow and Porous-Medium Flow
• [stat.CO]Accelerated Computation of a High Dimensional Kolmogorov-Smirnov Distance
• [stat.CO]MARS: A second-order reduction algorithm for high-dimensional sparse precision matrices estimation
• [stat.ME]A flexible Bayesian framework for individualized inference via dynamic borrowing
• [stat.ME]Extreme event propagation using counterfactual theory and vine copulas
• [stat.ME]Feature Grouping and Sparse Principal Component Analysis
• [stat.ME]Graph model selection by edge probability sequential inference
• [stat.ME]Multi-scale Poisson process approaches for differential expression analysis of high-throughput sequencing data
• [stat.ME]Posterior Covariance Information Criterion
• [stat.ML]Active Learning with Multifidelity Modeling for Efficient Rare Event Simulation
• [stat.ML]InteL-VAEs: Adding Inductive Biases to Variational Auto-Encoders via Intermediary Latents
• [stat.ML]Prediction of Hereditary Cancers Using Neural Networks
• [stat.ML]Tighter Analysis of Alternating Stochastic Gradient Method for Stochastic Nested Problems
·····································
• [astro-ph.CO]Primordial non-Gaussianity from the Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey I: Catalogue Preparation and Systematic Mitigation
Mehdi Rezaie, Ashley J. Ross, Hee-Jong Seo, Eva-Maria Mueller, Will J. Percival, Grant Merz, Reza Katebi, Razvan C. Bunescu, Julian Bautista, Joel R. Brownstein, Etienne Burtin, Kyle Dawson, Héctor Gil-Marín, Jiamin Hou, Eleanor B. Lyke, Axel de la Macorra, Graziano Rossi, Donald P. Schneider, Pauline Zarrouk, Gong-Bo Zhao
http://arxiv.org/abs/2106.13724v1
• [astro-ph.SR]Nonparametric monitoring of sunspot number observations: a case study
Sophie Mathieu, Laure Lefèvre, Rainer von Sachs, Véronique Delouille, Christian Ritter, Frédéric Clette
http://arxiv.org/abs/2106.13535v1
• [cs.AI]Dealing with Expert Bias in Collective Decision-Making
Axel Abels, Tom Lenaerts, Vito Trianni, Ann Nowé
http://arxiv.org/abs/2106.13539v1
• [cs.CL]A Source-Criticism Debiasing Method for GloVe Embeddings
Hope McGovern
http://arxiv.org/abs/2106.13382v1
• [cs.CL]Adapt-and-Distill: Developing Small, Fast and Effective Pretrained Language Models for Domains
Yunzhi Yao, Shaohan Huang, Wenhui Wang, Li Dong, Furu Wei
http://arxiv.org/abs/2106.13474v1
• [cs.CL]Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models
Robert L. Logan IV, Ivana Balažević, Eric Wallace, Fabio Petroni, Sameer Singh, Sebastian Riedel
http://arxiv.org/abs/2106.13353v1
• [cs.CL]DeltaLM: Encoder-Decoder Pre-training for Language Generation and Translation by Augmenting Pretrained Multilingual Encoders
Shuming Ma, Li Dong, Shaohan Huang, Dongdong Zhang, Alexandre Muzio, Saksham Singhal, Hany Hassan Awadalla, Xia Song, Furu Wei
http://arxiv.org/abs/2106.13736v1
• [cs.CL]Exploring the Representation of Word Meanings in Context: A Case Study on Homonymy and Synonymy
Marcos Garcia
http://arxiv.org/abs/2106.13553v1
• [cs.CL]JNLP Team: Deep Learning Approaches for Legal Processing Tasks in COLIEE 2021
Ha-Thanh Nguyen, Phuong Minh Nguyen, Thi-Hai-Yen Vuong, Quan Minh Bui, Chau Minh Nguyen, Binh Tran Dang, Vu Tran, Minh Le Nguyen, Ken Satoh
http://arxiv.org/abs/2106.13405v1
• [cs.CL]Language Models are Good Translators
Shuo Wang, Zhaopeng Tu, Zhixing Tan, Wenxuan Wang, Maosong Sun, Yang Liu
http://arxiv.org/abs/2106.13627v1
• [cs.CL]Learning to Sample Replacements for ELECTRA Pre-Training
Yaru Hao, Li Dong, Hangbo Bao, Ke Xu, Furu Wei
http://arxiv.org/abs/2106.13715v1
• [cs.CL]Manually Annotated Spelling Error Corpus for Amharic
Andargachew Mekonnen Gezmu, Tirufat Tesifaye Lema, Binyam Ephrem Seyoum, Andreas Nürnberger
http://arxiv.org/abs/2106.13521v1
• [cs.CL]ParaLaw Nets — Cross-lingual Sentence-level Pretraining for Legal Text Processing
Ha-Thanh Nguyen, Vu Tran, Phuong Minh Nguyen, Thi-Hai-Yen Vuong, Quan Minh Bui, Chau Minh Nguyen, Binh Tran Dang, Minh Le Nguyen, Ken Satoh
http://arxiv.org/abs/2106.13403v1
• [cs.CR]Vulnerability and Transaction behavior based detection of Malicious Smart Contracts
Rachit Agarwal, Tanmay Thapliyal, Sandeep Kumar Shukla
http://arxiv.org/abs/2106.13422v1
• [cs.CV]“Zero Shot” Point Cloud Upsampling
Kaiyue Zhou, Ming Dong, Suzan Arslanturk
http://arxiv.org/abs/2106.13765v1
• [cs.CV]A Picture May Be Worth a Hundred Words for Visual Question Answering
Yusuke Hirota, Noa Garcia, Mayu Otani, Chenhui Chu, Yuta Nakashima, Ittetsu Taniguchi, Takao Onoye
http://arxiv.org/abs/2106.13445v1
• [cs.CV]Animatable Neural Radiance Fields from Monocular RGB Video
Jianchuan Chen, Ying Zhang, Di Kang, Xuefei Zhe, Linchao Bao, Huchuan Lu
http://arxiv.org/abs/2106.13629v1
• [cs.CV]Building Intelligent Autonomous Navigation Agents
Devendra Singh Chaplot
http://arxiv.org/abs/2106.13415v1
• [cs.CV]Connecting Sphere Manifolds Hierarchically for Regularization
Damien Scieur, Youngsung Kim
http://arxiv.org/abs/2106.13549v1
• [cs.CV]Countering Adversarial Examples: Combining Input Transformation and Noisy Traini
146b
ng
Cheng Zhang, Pan Gao
http://arxiv.org/abs/2106.13394v1
• [cs.CV]Diversifying Semantic Image Synthesis and Editing via Class- and Layer-wise VAEs
Yuki Endo, Yoshihiro Kanamori
http://arxiv.org/abs/2106.13416v1
• [cs.CV]DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrieval
Giorgos Kordopatis-Zilos, Christos Tzelepis, Symeon Papadopoulos, Ioannis Kompatsiaris, Ioannis Patras
http://arxiv.org/abs/2106.13266v1
• [cs.CV]Efficient Document Image Classification Using Region-Based Graph Neural Network
Jaya Krishna Mandivarapu, Eric Bunch, Qian You, Glenn Fung
http://arxiv.org/abs/2106.13802v1
• [cs.CV]Generative Modeling for Multi-task Visual Learning
Zhipeng Bao, Martial Hebert, Yu-Xiong Wang
http://arxiv.org/abs/2106.13409v1
• [cs.CV]Graph Pattern Loss based Diversified Attention Network for Cross-Modal Retrieval
Xueying Chen, Rong Zhang, Yibing Zhan
http://arxiv.org/abs/2106.13552v1
• [cs.CV]Hierarchical Object-oriented Spatio-Temporal Reasoning for Video Question Answering
Long Hoang Dang, Thao Minh Le, Vuong Le, Truyen Tran
http://arxiv.org/abs/2106.13432v1
• [cs.CV]Image-to-image Transformation with Auxiliary Condition
Robert Leer, Hessi Roma, James Amelia
http://arxiv.org/abs/2106.13696v1
• [cs.CV]Interactive Multi-level Stroke Control for Neural Style Transfer
Max Reimann, Benito Buchheim, Amir Semmo, Jürgen Döllner, Matthias Trapp
http://arxiv.org/abs/2106.13787v1
• [cs.CV]Interpreting Depression From Question-wise Long-term Video Recording of SDS Evaluation
Wanqing Xie, Lizhong Liang, Yao Lu, Chen Wang, Jihong Shen, Hui Luo, Xiaofeng Liu
http://arxiv.org/abs/2106.13393v1
• [cs.CV]NP-DRAW: A Non-Parametric Structured Latent Variable Modelfor Image Generation
Xiaohui Zeng, Raquel Urtasun, Richard Zemel, Sanja Fidler, Renjie Liao
http://arxiv.org/abs/2106.13435v1
• [cs.CV]On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy
Vignesh Srinivasan, Nils Strodthoff, Jackie Ma, Alexander Binder, Klaus-Robert Müller, Wojciech Samek
http://arxiv.org/abs/2106.13497v1
• [cs.CV]PVTv2: Improved Baselines with Pyramid Vision Transformer
Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, Ling Shao
http://arxiv.org/abs/2106.13797v1
• [cs.CV]Partially fake it till you make it: mixing real and fake thermal images for improved object detection
Francesco Bongini, Lorenzo Berlincioni, Marco Bertini, Alberto Del Bimbo
http://arxiv.org/abs/2106.13603v1
• [cs.CV]Probing Inter-modality: Visual Parsing with Self-Attention for Vision-Language Pre-training
Hongwei Xue, Yupan Huang, Bei Liu, Houwen Peng, Jianlong Fu, Houqiang Li, Jiebo Luo
http://arxiv.org/abs/2106.13488v1
• [cs.CV]Projection-wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape Analysis
Xianjing Liu, Bo Li, Esther Bron, Wiro Niessen, Eppo Wolvius, Gennady Roshchupkin
http://arxiv.org/abs/2106.13734v1
• [cs.CV]SRPN: similarity-based region proposal networks for nuclei and cells detection in histology images
Yibao Sun, Xingru Huang, Huiyu Zhou, Qianni Zhang
http://arxiv.org/abs/2106.13556v1
• [cs.CV]Shape registration in the time of transformers
Giovanni Trappolini, Luca Cosmo, Luca Moschella, Riccardo Marin, Emanuele Rodolà
http://arxiv.org/abs/2106.13679v1
• [cs.CV]Single Image Texture Translation for Data Augmentation
Boyi Li, Yin Cui, Tsung-Yi Lin, Serge Belongie
http://arxiv.org/abs/2106.13804v1
• [cs.CV]Video Moment Retrieval with Text Query Considering Many-to-Many Correspondence Using Potentially Relevant Pair
Sho Maeoki, Yusuke Mukuta, Tatsuya Harada
http://arxiv.org/abs/2106.13566v1
• [cs.CV]Vision Transformer Architecture Search
Xiu Su, Shan You, Jiyang Xie, Mingkai Zheng, Fei Wang, Chen Qian, Changshui Zhang, Xiaogang Wang, Chang Xu
http://arxiv.org/abs/2106.13700v1
• [cs.CY]Fairness Deconstructed: A Sociotechnical View of ‘Fair’ Algorithms in Criminal Justice
Rajiv Movva
http://arxiv.org/abs/2106.13455v1
• [cs.CY]On Fairness and Interpretability
Deepak P, Sanil V, Joemon M. Jose
http://arxiv.org/abs/2106.13271v1
• [cs.CY]The Tale of Two Localization Technologies: Enabling Accurate Low-Overhead WiFi-based Localization for Low-end Phones
Ahmed Shokry, Moustafa Elhamshary, Moustafa Youssef
http://arxiv.org/abs/2106.13663v1
• [cs.DC]CEAZ: Accelerating Parallel I/O via Hardware-Algorithm Co-Design of Efficient and Adaptive Lossy Compression
Chengming Zhang, Sian Jin, Tong Geng, Jiannan Tian, Ang Li, Dingwen Tao
http://arxiv.org/abs/2106.13306v1
• [cs.DC]Cost-efficient, QoS and Security aware Placement of Smart Farming IoT Applications in Cloud-Fog Infrastructure
Jagruti Sahoo
http://arxiv.org/abs/2106.13524v1
• [cs.DC]FLASH 1.0: A Software Framework for Rapid Parallel Deployment and Enhancing Host Code Portability in Heterogeneous Computing
Michael Riera, Masudul Hassan Quraishi, Erfan Bank Tavakoli, Fengbo Ren
http://arxiv.org/abs/2106.13645v1
• [cs.DC]Introducing OpenMP Tasks into the HYDRO Benchmark
Jérémie Gaidamour, Dimitri Lecas, Pierre-François Lavallée
http://arxiv.org/abs/2106.13465v1
• [cs.DC]Overcoming barriers to scalability in variational quantum Monte Carlo
Tianchen Zhao, Saibal De, Brian Chen, James Stokes, Shravan Veerapaneni
http://arxiv.org/abs/2106.13308v1
• [cs.DC]The Problem of Distributed Consensus: A Survey
Stephen Wolfram
http://arxiv.org/abs/2106.13591v1
• [cs.DS]The Price of Tolerance in Distribution Testing
Clément L. Canonne, Ayush Jain, Gautam Kamath, Jerry Li
http://arxiv.org/abs/2106.13414v1
• [cs.HC]Advancing Methodology for Social Science Research Using Alternate Reality Games: Proof-of-Concept Through Measuring Individual Differences and Adaptability and their impact on Team Performance
Magy Seif El-Nasr, Casper Harteveld, Paul Fombelle, Truong-Huy Nguyen, Paola Rizzo, Dylan Schouten, Abdelrahman Madkour, Chaima Jemmali, Erica Kleinman, Nithesh Javvaji, Zhaoqing Teng, Extra Ludic Inc
http://arxiv.org/abs/2106.13740v1
• [cs.IR]A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models
Oleg Lesota, Navid Rekabsaz, Daniel Cohen, Klaus Antonius Grasserbauer, Carsten Eickhoff, Markus Schedl
http://arxiv.org/abs/2106.13618v1
• [cs.IR]Balancing Accuracy and Fairness for Interactive Recommendation with Reinforcement Learning
Weiwen Liu, Feng Liu, Ruiming Tang, Ben Liao, Guangyong Chen, Pheng Ann Heng
http://arxiv.org/abs/2106.13386v1
• [cs.IR]Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature
Yu Wang, Jinchao Li, Tristan Naumann, Chenyan Xiong, Hao Cheng, Robert Tinn, Cliff Wong, Naoto Usuyama, Richard Rogahn, Zhihong Shen, Yang Qin, Eric Horvitz, Paul N. Bennett, Jianfeng Gao, Hoifung Poon
http://arxiv.org/abs/2106.13375v1
• [cs.IR]Interactive query expansion for professional search applications
Tony Russell-Rose, Philip Gooch, Udo Kruschwitz
http://arxiv.org/abs/2106.13528v1
• [cs.IR]TableSense: Spreadsheet Table Detection with Convolutional Neural Networks
Haoyu Dong, Shijie Liu, Shi Han, Zhouyu Fu, Dongmei Zhang
http://arxiv.org/abs/2106.13500v1
• [cs.IT]An Edge Computing Paradigm for Massive IoT Connectivity over High-Altitude Platform Networks
Malong Ke, Zhen Gao, Yang Huang, Guoru Ding, Derrick Wing Kwan Ng, Qihui Wu, Jun Zhang
http://arxiv.org/abs/2106.13476v1
• [cs.IT]Beam Alignment in mmWave User-Centric Cell-Free Massive MIMO Systems
Stefano Buzzi, Carmen D’Andrea, Maria Fresia, Xiaofeng Wu
http://arxiv.org/abs/2106.13538v1
• [cs.IT]Doubly-Exponential Identification via Channels: Code Constructions and Bounds
Onur Günlü, Joerg Kliewer, Rafael F. Schaefer, Vladimir Sidorenko
http://arxiv.org/abs/2106.13495v1
• [cs.IT]Guessing Based on Compressed Side Information
Robert Graczyk, Amos Lapidoth, Neri Merhav, Christoph Pfister
http://arxiv.org/abs/2106.13341v1
• [cs.IT]Multi-player Multi-armed Bandits with Collision-Dependent Reward Distributions
Chengshuai Shi, Cong Shen
http://arxiv.org/abs/2106.13669v1
• [cs.IT]Pilot Contamination Elimination for Channel Estimation with Complete Knowledge of Large-Scale Fading in Downlink Massive MIMO Systems
Qazwan Abdullah, Norsaliza Abdullah, Adeb Salh, Lukman Audah, Nabil Farah, Abbas Ugurenver, Abdu Saif
http://arxiv.org/abs/2106.13507v1
• [cs.LG]A hybrid model-based and learning-based approach for classification using limited number of training samples
Alireza Nooraiepour, Waheed U. Bajwa, Narayan B. Mandayam
http://arxiv.org/abs/2106.13436v1
• [cs.LG]A mechanistic-based data-driven approach to accelerate structural topology optimization through finite element convolutional neural network (FE-CNN)
Tianle Yue, Hang Yang, Zongliang Du, Chang Liu, Khalil I. Elkhodary, Shan Tang, Xu Guo
http://arxiv.org/abs/2106.13652v1
• [cs.LG]Assessing Generalization of SGD via Disagreement
Yiding Jiang, Vaishnavh Nagarajan, Christina Baek, J. Zico Kolter
http://arxiv.org/abs/2106.13799v1
• [cs.LG]Assessing the Lockdown Effects on Air Quality during COVID-19 Era
Ioannis Kavouras, Eftychios Protopapadakis, Maria Kaselimia, Emmanuel Sardis, Nikolaos Doulamis
http://arxiv.org/abs/2106.13750v1
• [cs.LG]Bayesian Inference in High-Dimensional Time-Serieswith the Orthogonal Stochastic Linear Mixing Model
Rui Meng, Kristofer Bouchard
http://arxiv.org/abs/2106.13379v1
• [cs.LG]Branch Prediction as a Reinforcement Learning Problem: Why, How and Case Studies
Anastasios Zouzias, Kleovoulos Kalaitzidis, Boris Grot
http://arxiv.org/abs/2106.13429v1
• [cs.LG]CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals
Cédric Rommel, Thomas Moreau, Alexandre Gramfort
http://arxiv.org/abs/2106.13695v1
• [cs.LG]Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote
Yi-Shan Wu, Andrés R. Masegosa, Stephan S. Lorenzen, Christian Igel, Yevgeny Seldin
http://arxiv.org/abs/2106.13624v1
• [cs.LG]Conjugate Energy-Based Models
Hao Wu, Babak Esmaeili, Michael Wick, Jean-Baptiste Tristan, Jan-Willem van de Meent
http://arxiv.org/abs/2106.13798v1
• [cs.LG]Data efficiency in graph networks through equivariance
Francesco Farina, Emma Slade
http://arxiv.org/abs/2106.13786v1
• [cs.LG]Data-based Design of Inferential Sensors for Petrochemical Industry
Martin Mojto, Karol Ľubušký, Miroslav Fikar, Radoslav Paulen
http://arxiv.org/abs/2106.13503v1
• [cs.LG]Deep Interpretable Criminal Charge Prediction and Algorithmic Bias
Abdul Rafae Khan, Jia Xu, Peter Varsanyi, Rachit Pabreja
http://arxiv.org/abs/2106.13456v1
• [cs.LG]DeepLoc: A Ubiquitous Accurate and Low-Overhead Outdoor Cellular Localization System
Ahmed Shokry, Marwan Torki, Moustafa Youssef
http://arxiv.org/abs/2106.13632v1
• [cs.LG]Federated Graph Classification over Non-IID Graphs
Han Xie, Jing Ma, Li Xiong, Carl Yang
http://arxiv.org/abs/2106.13423v1
• [cs.LG]Federated Noisy Client Learning
Li Li, Huazhu Fu, Bo Han, Cheng-Zhong Xu, Ling Shao
http://arxiv.org/abs/2106.13239v1
• [cs.LG]Fine-grained Geolocation Prediction of Tweets with Human Machine Collaboration
Florina Dutt, Subhajit Das
http://arxiv.org/abs/2106.13411v1
• [cs.LG]Fostering Diversity in Spatial Evolutionary Generative Adversarial Networks
Jamal Toutouh, Erik Hemberg, Una-May O’Reilly
http://arxiv.org/abs/2106.13590v1
• [cs.LG]HyperNP: Interactive Visual Exploration of Multidimensional Projection Hyperparameters
Gabriel Appleby, Mateus Espadoto, Rui Chen, Samuel Goree, Alexandru Telea, Erik W Anderson, Remco Chang
http://arxiv.org/abs/2106.13777v1
• [cs.LG]Jitter:
8f0
Random Jittering Loss Function
Zhicheng Cai, Chenglei Peng, Sidan Du
http://arxiv.org/abs/2106.13749v1
• [cs.LG]Learning Gradual Argumentation Frameworks using Genetic Algorithms
Jonathan Spieler, Nico Potyka, Steffen Staab
http://arxiv.org/abs/2106.13585v1
• [cs.LG]Limitations of machine learning for building energy prediction: ASHRAE Great Energy Predictor III Kaggle competition error analysis
Clayton Miller, Bianca Picchetti, Chun Fu, Jovan Pantelic
http://arxiv.org/abs/2106.13475v1
• [cs.LG]Littlestone Classes are Privately Online Learnable
Noah Golowich, Roi Livni
http://arxiv.org/abs/2106.13513v1
• [cs.LG]Model-Based Reinforcement Learning via Latent-Space Collocation
Oleh Rybkin, Chuning Zhu, Anusha Nagabandi, Kostas Daniilidis, Igor Mordatch, Sergey Levine
http://arxiv.org/abs/2106.132
f9b
29v1
f9b
29v1)
• [cs.LG]Multi-Domain Active Learning: A Comparative Study
Rui He, Shan He, Ke Tang
http://arxiv.org/abs/2106.13516v1
• [cs.LG]Multi-Goal Reinforcement Learning environments for simulated Franka Emika Panda robot
Quentin Gallouédec, Nicolas Cazin, Emmanuel Dellandréa, Liming Chen
http://arxiv.org/abs/2106.13687v1
• [cs.LG]Multitask Learning for Citation Purpose Classification
Alex Oesterling, Angikar Ghosal, Haoyang Yu, Rui Xin, Yasa Baig, Lesia Semenova, Cynthia Rudin
http://arxiv.org/abs/2106.13275v1
• [cs.LG]On the (Un-)Avoidability of Adversarial Examples
Sadia Chowdhury, Ruth Urner
http://arxiv.org/abs/2106.13326v1
• [cs.LG]Private Adaptive Gradient Methods for Convex Optimization
Hilal Asi, John Duchi, Alireza Fallah, Omid Javidbakht, Kunal Talwar
http://arxiv.org/abs/2106.13756v1
• [cs.LG]Privileged Zero-Shot AutoML
Nikhil Singh, Brandon Kates, Jeff Mentch, Anant Kharkar, Madeleine Udell, Iddo Drori
http://arxiv.org/abs/2106.13743v1
• [cs.LG]Proxy Convexity: A Unified Framework for the Analysis of Neural Networks Trained by Gradient Descent
Spencer Frei, Quanquan Gu
http://arxiv.org/abs/2106.13792v1
• [cs.LG]Ranger21: a synergistic deep learning optimizer
Less Wright, Nestor Demeure
http://arxiv.org/abs/2106.13731v1
• [cs.LG]Re-parameterizing VAEs for stability
David Dehaene, Rémy Brossard
http://arxiv.org/abs/2106.13739v1
• [cs.LG]Reliable Graph Neural Network Explanations Through Adversarial Training
Donald Loveland, Shusen Liu, Bhavya Kailkhura, Anna Hiszpanski, Yong Han
http://arxiv.org/abs/2106.13427v1
• [cs.LG]Robust Matrix Factorization with Grouping Effect
Haiyan Jiang, Shuyu Li, Luwei Zhang, Haoyi Xiong, Dejing Dou
http://arxiv.org/abs/2106.13681v1
• [cs.LG]Self-training Converts Weak Learners to Strong Learners in Mixture Models
Spencer Frei, Difan Zou, Zixiang Chen, Quanquan Gu
http://arxiv.org/abs/2106.13805v1
• [cs.LG]Subgraph Federated Learning with Missing Neighbor Generation
Ke Zhang, Carl Yang, Xiaoxiao Li, Lichao Sun, Siu Ming Yiu
http://arxiv.org/abs/2106.13430v1
• [cs.LG]Temporal Graph Signal Decomposition
Maxwell McNeil, Lin Zhang, Petko Bogdanov
http://arxiv.org/abs/2106.13517v1
• [cs.LG]Tensor-based framework for training flexible neural networks
Yassine Zniyed, Konstantin Usevich, Sebastian Miron, David Brie
http://arxiv.org/abs/2106.13542v1
• [cs.LG]Transient Stability Analysis with Physics-Informed Neural Networks
Jochen Stiasny, Georgios S. Misyris, Spyros Chatzivasileiadis
http://arxiv.org/abs/2106.13638v1
• [cs.LG]Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy
Xinwei Zhang, Xiangyi Chen, Mingyi Hong, Zhiwei Steven Wu, Jinfeng Yi
http://arxiv.org/abs/2106.13673v1
• [cs.LG]VEGN: Variant Effect Prediction with Graph Neural Networks
Jun Cheng, Carolin Lawrence, Mathias Niepert
http://arxiv.org/abs/2106.13642v1
• [cs.LG]What will it take to generate fairness-preserving explanations?
Jessica Dai, Sohini Upadhyay, Stephen H. Bach, Himabindu Lakkaraju
http://arxiv.org/abs/2106.13346v1
• [cs.MM]Multiview Video Compression Using Advanced HEVC Screen Content Coding
Jarosław Samelak, Jarosław Samelak
http://arxiv.org/abs/2106.13574v1
• [cs.NE]A nonlinear hidden layer enables actor-critic agents to learn multiple paired association navigation
M Ganesh Kumar, Cheston Tan, Camilo Libedinsky, Shih-Cheng Yen, Andrew Yong-Yi Tan
http://arxiv.org/abs/2106.13541v1
• [cs.RO]Active Learning in Robotics: A Review of Control Principles
Annalisa T. Taylor, Thomas A. Berrueta, Todd D. Murphey
http://arxiv.org/abs/2106.13697v1
• [cs.RO]Brax — A Differentiable Physics Engine for Large Scale Rigid Body Simulation
C. Daniel Freeman, Erik Frey, Anton Raichuk, Sertan Girgin, Igor Mordatch, Olivier Bachem
http://arxiv.org/abs/2106.13281v1
• [cs.RO]Collision Avoidance for Unmanned Aerial Vehicles in the Presence of Static and Moving Obstacles
Andrei Marchidan, Efstathios Bakolas
http://arxiv.org/abs/2106.13451v1
• [cs.RO]Distributed IDA-PBC for a Class of Nonholonomic Mechanical Systems
Anastasios Tsolakis, Tamas Keviczky
http://arxiv.org/abs/2106.13338v1
• [cs.RO]Factor Graphs for Heterogeneous Bayesian Decentralized Data Fusion
Ofer Dagan, Nisar R. Ahmed
http://arxiv.org/abs/2106.13285v1
• [cs.RO]Move Beyond Trajectories: Distribution Space Coupling for Crowd Navigation
Muchen Sun, Francesca Baldini, Peter Trautman, Todd Murphey
http://arxiv.org/abs/2106.13667v1
• [cs.RO]Multi-Robot Deep Reinforcement Learning for Mobile Navigation
Katie Kang, Gregory Kahn, Sergey Levine
http://arxiv.org/abs/2106.13280v1
• [cs.RO]Navigating A Mobile Robot Using Switching Distributed Sensor Networks
Xingkang He, Ehsan Hashemi, Karl H. Johansson
http://arxiv.org/abs/2106.13529v1
• [cs.RO]Non-Parametric Neuro-Adaptive Control Subject to Task Specifications
Christos K. Verginis, Zhe Xu, Ufuk Topcu
http://arxiv.org/abs/2106.13498v1
• [cs.RO]Scalable Perception-Action-Communication Loops with Convolutional and Graph Neural Networks
Ting-Kuei Hu, Fernando Gama, Tianlong Chen, Wenqing Zheng, Zhangyang Wang, Alejandro Ribeiro, Brian M. Sadler
http://arxiv.org/abs/2106.13358v1
• [cs.RO]Task-Driven Out-of-Distribution Detection with Statistical Guarantees for Robot Learning
Alec Farid, Sushant Veer, Anirudha Majumdar
http://arxiv.org/abs/2106.13703v1
• [cs.SD]Deep Residual Echo Suppression with A Tunable Tradeoff Between Signal Distortion and Echo Suppression
Amir Ivry, Israel Cohen, Baruch Berdugo
http://arxiv.org/abs/2106.13531v1
• [cs.SD]Evaluation of Deep-Learning-Based Voice Activity Detectors and Room Impulse Response Models in Reverberant Environments
Amir Ivry, Israel Cohen, Baruch Berdugo
http://arxiv.org/abs/2106.13511v1
• [cs.SD]Nonlinear Acoustic Echo Cancellation with Deep Learning
Amir Ivry, Israel Cohen, Baruch Berdugo
http://arxiv.org/abs/2106.13754v1
• [cs.SD]Phoneme-aware and Channel-wise Attentive Learning for Text DependentSpeaker Verification
Yan Liu, Zheng Li, Lin Li, Qingyang Hong
http://arxiv.org/abs/2106.13514v1
• [cs.SD]Preliminary study on using vector quantization latent spaces for TTS/VC systems with consistent performance
Hieu-Thi Luong, Junichi Yamagishi
http://arxiv.org/abs/2106.13479v1
• [cs.SD]Voice Activity Detection for Transient Noisy Environment Based on Diffusion Nets
Amir Ivry, Baruch Berdugo, Israel Cohen
http://arxiv.org/abs/2106.13763v1
• [cs.SI]Edge based stochastic block model statistical inference
Louis Duvivier, Rémy Cazabet, Céline Robardet
http://arxiv.org/abs/2106.13571v1
• [cs.SI]Exposing individual differences through network topology
Yuval Samoilov-Katz, Yoram Louzoun, Lev Muchnik, Adam Zaidel
http://arxiv.org/abs/2106.13672v1
• [cs.SI]Graph space: using both geometric and probabilistic structure to evaluate statistical graph models
Louis Duvivier, Rémy Cazabet, Céline Robardet
http://arxiv.org/abs/2106.13587v1
• [cs.SI]Louvain-like Methods for Community Detection in Multi-Layer Networks
Sara Venturini, Andrea Cristofari, Francesco Rinaldi, Francesco Tudisco
http://arxiv.org/abs/2106.13543v1
• [cs.SI]Trends, Politics, Sentiments, and Misinformation: Understanding People’s Reactions to COVID-19 During its Early Stages
Omar Abdel Wahab, Ali Mustafa, André Bertrand Abisseck Bamatakina
http://arxiv.org/abs/2106.13385v1
• [eess.AS]Online Self-Attentive Gated RNNs for Real-Time Speaker Separation
Ori Kabeli, Yossi Adi, Zhenyu Tang, Buye Xu, Anurag Kumar
http://arxiv.org/abs/2106.13493v1
• [eess.IV]A Novel Self-Learning Framework for Bladder Cancer Grading Using Histopathological Images
Gabriel García, Anna Esteve, Adrián Colomer, David Ramos, Valery Naranjo
http://arxiv.org/abs/2106.13559v1
• [eess.IV]Circumpapillary OCT-Focused Hybrid Learning for Glaucoma Grading Using Tailored Prototypical Neural Networks
Gabriel García, Rocío del Amor, Adrián Colomer, Rafael Verdú-Monedero, Juan Morales-Sánchez, Valery Naranjo
http://arxiv.org/abs/2106.13551v1
• [eess.IV]Semantic annotation for computational pathology: Multidisciplinary experience and best practice recommendations
Noorul Wahab, Islam M Miligy, Katherine Dodd, Harvir Sahota, Michael Toss, Wenqi Lu, Mostafa Jahanifar, Mohsin Bilal, Simon Graham, Young Park, Giorgos Hadjigeorghiou, Abhir Bhalerao, Ayat Lashen, Asmaa Ibrahim, Ayaka Katayama, Henry O Ebili, Matthew Parkin, Tom Sorell, Shan E Ahmed Raza, Emily Hero, Hesham Eldaly, Yee Wah Tsang, Kishore Gopalakrishnan, David Snead, Emad Rakha, Nasir Rajpoot, Fayyaz Minhas
http://arxiv.org/abs/2106.13689v1
• [eess.SP]The Effect of Ground Truth Accuracy on the Evaluation of Localization Systems
Chen Gu, Ahmed Shokry, Moustafa Youssef
http://arxiv.org/abs/2106.13614v1
• [math.OC]IPM-HLSP: An Efficient Interior-Point Method for Hierarchical Least-Squares Programs
Kai Pfeiffer, Adrien Escande, Ludovic Righetti
http://arxiv.org/abs/2106.13602v1
• [math.OC]A proximal-proximal majorization-minimization algorithm for nonconvex tuning-free robust regression problems
Peipei Tang, Chengjing Wang, Bo Jiang
http://arxiv.org/abs/2106.13683v1
• [math.OC]Binary Matrix Factorisation and Completion via Integer Programming
Reka A. Kovacs, Oktay Gunluk, Raphael A. Hauser
http://arxiv.org/abs/2106.13434v1
• [math.OC]Reinforcement Learning for Mean Field Games, with Applications to Economics
Andrea Angiuli, Jean-Pierre Fouque, Mathieu Lauriere
http://arxiv.org/abs/2106.13755v1
• [math.ST]On a Projection Estimator of the Regression Function Derivative
Fabienne Comte, Nicolas Marie
http://arxiv.org/abs/2106.13293v1
• [math.ST]Parameter Estimation for the McKean-Vlasov Stochastic Differential Equation
Louis Sharrock, Nikolas Kantas, Panos Parpas, Grigorios A. Pavliotis
http://arxiv.org/abs/2106.13751v1
• [math.ST]Semi-supervised multiple testing
David Mary, Etienne Roquain
http://arxiv.org/abs/2106.13501v1
• [physics.soc-ph]Stochastic modeling of scientific impact
M. V. Simkin
http://arxiv.org/abs/2106.13295v1
• [quant-ph]Temporal Modes of Light in Satellite-to-Earth Quantum Communications
Ziqing Wang, Robert Malaney, Ryan Aguinaldo
http://arxiv.org/abs/2106.13693v1
• [stat.AP]Implementation of an alternative method for assessing competing risks: restricted mean time lost
Hongji Wu, Hao Yuan, Zijing Yang, Yawen Hou, Zheng Chen
http://arxiv.org/abs/2106.13390v1
• [stat.AP]Optimal Accelerated Degradation Testing Based on Bivariate Gamma Process with Dependent Components
Helmi Shat, Norbert Gaffke
http://arxiv.org/abs/2106.13540v1
• [stat.AP]Robust Real-Time Delay Predictions in a Network of High-Frequency Urban Buses
Hector Rodriguez-Deniz, Mattias Villani
http://arxiv.org/abs/2106.13576v1
• [stat.AP]Uncertainty-aware Validation Benchmarks for Coupling Free Flow and Porous-Medium Flow
Farid Mohammadi, Elissa Eggenweiler, Bernd Flemisch, Sergey Oladyshkin, Iryna Rybak, Martin Schneider, Kilian Weishaupt
http://arxiv.org/abs/2106.13639v1
• [stat.CO]Accelerated Computation of a High Dimensional Kolmogorov-Smirnov Distance
Alex Hagen, Shane Jackson, James Kahn, Jan Strube, Isabel Haide, Karl Pazdernik, Connor Hainje
http://arxiv.org/abs/2106.13706v1
• [stat.CO]MARS: A second-order reduction algorithm for high-dimensional sparse precision matrices estimation
Qian LI, Binyan Jiang, Defeng Sun
http://arxiv.org/abs/2106.13508v1
• [stat.ME]A flexible Bayesian framework for individualized inference via dynamic borrowing
Ziyu Ji, Julian Wolfson
http://arxiv.org/abs/2106.13431v1
• [stat.ME]Extreme event propagation using counterfactual theory and vine copulas
Valentin Courgeau, Almut E. D. Veraart
http://arxiv.org/abs/2106.13564v1
• [stat.ME]Feature Grouping and Sparse Principal Component Analysis
Haiyan Jiang, Shanshan Qin, Dejing Dou
http://arxiv.org/abs/2106.13685v1
• [stat.ME]Graph model selection by edge probability sequential inference
Louis Duvivier, Rémy Cazabet, Céline Robardet
http://arxiv.org/abs/2106.13579v1
• [stat.ME]Multi-scale Poisson process approaches for differential expression analysis of high-throughput sequencing data
Heejung Shim, Zhengrong Xing, Ester Pantaleo, Francesca Luca, Roger Pique-Regi, Matthew Stephens
http://arxiv.org/abs/2106.13634v1
• [stat.ME]Posterior Covariance Information Criterion
Yukito Iba, Keisuke Yano
http://arxiv.org/abs/2106.13694v1
• [stat.ML]Active Learning with Multifidelity Modeling for Efficient Rare Event Simulation
S. L. N. Dhulipala, M. D. Shields, B. W. Spencer, C. Bolisetti, A. E. Slaughter, V. M. Laboure, P. Chakroborty
http://arxiv.org/abs/2106.13790v1
• [stat.ML]InteL-VAEs: Adding Inductive Biases to Variational Auto-Encoders via Intermediary Latents
Ning Miao, Emile Mathieu, N. Siddharth, Yee Whye Teh, Tom Rainforth
http://arxiv.org/abs/2106.13746v1
• [stat.ML]Prediction of Hereditary Cancers Using Neural Networks
Zoe Guan, Giovanni Parmigiani, Danielle Braun, Lorenzo Trippa
http://arxiv.org/abs/2106.13682v1
• [stat.ML]Tighter Analysis of Alternating Stochastic Gradient Method for Stochastic Nested Problems
Tianyi Chen, Yuejiao Sun, Wotao Yin
http://arxiv.org/abs/2106.13781v1
若有收获，就点个赞吧
0 人点赞
