astro-ph.EP - 地球与行星天体
    cond-mat.mtrl-sci - 材料科学
    cs.AI - 人工智能
    cs.CL - 计算与语言
    cs.CR - 加密与安全
    cs.CV - 机器视觉与模式识别
    cs.CY - 计算与社会
    cs.DB - 数据库
    cs.DC - 分布式、并行与集群计算
    cs.DL - 数字图书馆
    cs.DM - 离散数学
    cs.ET - 新兴技术
    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.SE - 软件工程
    cs.SI - 社交网络与信息网络
    econ.EM - 计量经济学
    eess.AS - 语音处理
    eess.IV - 图像与视频处理
    eess.SP - 信号处理
    hep-ph - 高能物理现象学
    math.MG -公制几何
    math.NA - 数值分析
    math.OC - 优化与控制
    math.ST - 统计理论
    physics.comp-ph - 计算物理学
    physics.flu-dyn - 流体动力学
    q-fin.MF - 数学金融
    q-fin.PR - 证券定价
    quant-ph - 量子物理
    stat.AP - 应用统计
    stat.ME - 统计方法论
    stat.ML - (统计)机器学习

    • [astro-ph.EP]Automation Of Transiting Exoplanet Detection, Identification and Habitability Assessment Using Machine Learning Approaches
    • [cond-mat.mtrl-sci]Grain segmentation in atomistic simulations using orientation-based iterative self-organizing data analysis
    • [cond-mat.mtrl-sci]Physics guided deep learning generative models for crystal materials discovery
    • [cs.AI]Neuro-Symbolic Inductive Logic Programming with Logical Neural Networks
    • [cs.CL]A pragmatic account of the weak evidence effect
    • [cs.CL]Adapting BERT for Continual Learning of a Sequence of Aspect Sentiment Classification Tasks
    • [cs.CL]Automated Story Generation as Question-Answering
    • [cs.CL]Dataset Geography: Mapping Language Data to Language Users
    • [cs.CL]GKS: Graph-based Knowledge Selector for Task-oriented Dialog System
    • [cs.CL]Ground-Truth, Whose Truth? — Examining the Challenges with Annotating Toxic Text Datasets
    • [cs.CL]Improving Neural Cross-Lingual Summarization via Employing Optimal Transport Distance for Knowledge Distillation
    • [cs.CL]Interpretable Privacy Preservation of Text Representations Using Vector Steganography
    • [cs.CL]JUSTICE: A Benchmark Dataset for Supreme Court’s Judgment Prediction
    • [cs.CL]Multi-speaker Emotional Text-to-speech Synthesizer
    • [cs.CL]Natural Answer Generation: From Factoid Answer to Full-length Answer using Grammar Correction
    • [cs.CL]Parsing with Pretrained Language Models, Multiple Datasets, and Dataset Embeddings
    • [cs.CL]Question Answering Survey: Directions, Challenges, Datasets, Evaluation Matrices
    • [cs.CL]Reducing Target Group Bias in Hate Speech Detectors
    • [cs.CL]UCD-CS at TREC 2021 Incident Streams Track
    • [cs.CL]UNITER-Based Situated Coreference Resolution with Rich Multimodal Input
    • [cs.CL]raceBERT — A Transformer-based Model for Predicting Race from Names
    • [cs.CR]Adversarial Machine Learning In Network Intrusion Detection Domain: A Systematic Review
    • [cs.CR]BDFA: A Blind Data Adversarial Bit-flip Attack on Deep Neural Networks
    • [cs.CR]BlockGC: A Joint Learning Framework for Account Identity Inference on Blockchain with Graph Contrast
    • [cs.CR]Blockchain Synchronous Trust Consensus Model
    • [cs.CR]Defending against Model Stealing via Verifying Embedded External Features
    • [cs.CR]Does Proprietary Software Still Offer Protection of Intellectual Property in the Age of Machine Learning? — A Case Study using Dual Energy CT Data
    • [cs.CR]Membership Inference Attacks From First Principles
    • [cs.CR]Test-Time Detection of Backdoor Triggers for Poisoned Deep Neural Networks
    • [cs.CV]A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion
    • [cs.CV]A Contrastive Distillation Approach for Incremental Semantic Segmentation in Aerial Images
    • [cs.CV]A Survey on Intrinsic Images: Delving Deep Into Lambert and Beyond
    • [cs.CV]ADD: Frequency Attention and Multi-View based Knowledge Distillation to Detect Low-Quality Compressed Deepfake Images
    • [cs.CV]Activation to Saliency: Forming High-Quality Labels for Unsupervised Salient Object Detection
    • [cs.CV]Bootstrapping ViTs: Towards Liberating Vision Transformers from Pre-training
    • [cs.CV]CG-NeRF: Conditional Generative Neural Radiance Fields
    • [cs.CV]CMA-CLIP: Cross-Modality Attention CLIP for Image-Text Classification
    • [cs.CV]Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Recognition
    • [cs.CV]DCAN: Improving Temporal Action Detection via Dual Context Aggregation
    • [cs.CV]Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal
    • [cs.CV]Deep Level Set for Box-supervised Instance Segmentation in Aerial Images
    • [cs.CV]Dense Depth Priors for Neural Radiance Fields from Sparse Input Views
    • [cs.CV]Dilated convolution with learnable spacings
    • [cs.CV]E今日学术视野(2021.12.9) - 图1(GO)MOTION: Motion Augmented Event Stream for Egocentric Action Recognition
    • [cs.CV]Flexible Networks for Learning Physical Dynamics of Deformable Objects
    • [cs.CV]GPU-Based Homotopy Continuation for Minimal Problems in Computer Vision
    • [cs.CV]GaTector: A Unified Framework for Gaze Object Prediction
    • [cs.CV]Gaussian map predictions for 3D surface feature localisation and counting
    • [cs.CV]Generation of Non-Deterministic Synthetic Face Datasets Guided by Identity Priors
    • [cs.CV]Gram-SLD: Automatic Self-labeling and Detection for Instance Objects
    • [cs.CV]Grounded Language-Image Pre-training
    • [cs.CV]Handwritten Mathematical Expression Recognition via Attention Aggregation based Bi-directional Mutual Learning
    • [cs.CV]Hybrid SNN-ANN: Energy-Efficient Classification and Object Detection for Event-Based Vision
    • [cs.CV]Label Hallucination for Few-Shot Classification
    • [cs.CV]Learning Connectivity with Graph Convolutional Networks for Skeleton-based Action Recognition
    • [cs.CV]Learning Instance and Task-Aware Dynamic Kernels for Few Shot Learning
    • [cs.CV]Learning to Solve Hard Minimal Problems
    • [cs.CV]Low-rank Tensor Decomposition for Compression of Convolutional Neural Networks Using Funnel Regularization
    • [cs.CV]MS-TCT: Multi-Scale Temporal ConvTransformer for Action Detection
    • [cs.CV]Parallel Discrete Convolutions on Adaptive Particle Representations of Images
    • [cs.CV]Polarimetric Pose Prediction
    • [cs.CV]Producing augmentation-invariant embeddings from real-life imagery
    • [cs.CV]Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields
    • [cs.CV]Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly Detection
    • [cs.CV]SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal
    • [cs.CV]STC-mix: Space, Time, Channel mixing for Self-supervised Video Representation
    • [cs.CV]SalFBNet: Learning Pseudo-Saliency Distribution via Feedback Convolutional Networks
    • [cs.CV]Saliency Diversified Deep Ensemble for Robustness to Adversaries
    • [cs.CV]Self-Supervised Camera Self-Calibration from Video
    • [cs.CV]Suppressing Static Visual Cues via Normalizing Flows for Self-Supervised Video Representation Learning
    • [cs.CV]TCGL: Temporal Contrastive Graph for Self-supervised Video Representation Learning
    • [cs.CV]Time-Equivariant Contrastive Video Representation Learning
    • [cs.CV]Traversing within the Gaussian Typical Set: Differentiable Gaussianization Layers for Inverse Problems Augmented by Normalizing Flows
    • [cs.CV]Unsupervised Learning of Compositional Scene Representations from Multiple Unspecified Viewpoints
    • [cs.CV]Variance-Aware Weight Initialization for Point Convolutional Neural Networks
    • [cs.CV]Vehicle trajectory prediction works, but not everywhere
    • [cs.CV]ViewCLR: Learning Self-supervised Video Representation for Unseen Viewpoints
    • [cs.CV]VizExtract: Automatic Relation Extraction from Data Visualizations
    • [cs.CV]Voxelized 3D Feature Aggregation for Multiview Detection
    • [cs.CV]Wild ToFu: Improving Range and Quality of Indirect Time-of-Flight Depth with RGB Fusion in Challenging Environments
    • [cs.CY]Datensouveränität für Verbraucher:innen: Technische Ansätze durch KI-basierte Transparenz und Auskunft im Kontext der DSGVO
    • [cs.CY]On Information Processing Limitations In Humans and Machines
    • [cs.CY]Stupid, Evil, or Both? Understanding the Smittestopp conflict
    • [cs.DB]Glue: Adaptively Merging Single Table Cardinality to Estimate Join Query Size
    • [cs.DC]Campaign Knowledge Network: Building Knowledge for Campaign Efficiency
    • [cs.DC]Phase Transition of the 3-Majority Dynamics with Uniform Communication Noise
    • [cs.DL]Change Summarization of Diachronic Scholarly Paper Collections by Semantic Evolution Analysis
    • [cs.DL]Disability and Library Services: Global Research Trend
    • [cs.DM]Multidimensional Assignment Problem for multipartite entity resolution
    • [cs.ET]Associative Memories Using Complex-Valued Hopfield Networks Based on Spin-Torque Oscillator Arrays
    • [cs.IR]A Sensitivity Analysis of the MSMARCO Passage Collection
    • [cs.IR]Cross-domain User Preference Learning for Cold-start Recommendation
    • [cs.IR]Long-Tail Session-based Recommendation from Calibration
    • [cs.IT]Gradient and Projection Free Distributed Online Min-Max Resource Optimization
    • [cs.IT]New Lower Bounds on the Capacity of Optical Fiber Channels via Optimized Shaping and Detection
    • [cs.IT]On a 2-relative entropy
    • [cs.IT]Semantic Coded Transmission: Architecture, Methodology, and Challenges
    • [cs.LG]A Continuous-time Stochastic Gradient Descent Method for Continuous Data
    • [cs.LG]A Generic Approach for Enhancing GANs by Regularized Latent Optimization
    • [cs.LG]A Novel Convergence Analysis for Algorithms of the Adam Family
    • [cs.LG]A Piece-wise Polynomial Filtering Approach for Graph Neural Networks
    • [cs.LG]A Unified Framework for Multi-distribution Density Ratio Estimation
    • [cs.LG]A coarse space acceleration of deep-DDM
    • [cs.LG]A deep language model to predict metabolic network equilibria
    • [cs.LG]Attention-Based Model and Deep Reinforcement Learning for Distribution of Event Processing Tasks
    • [cs.LG]Augment & Valuate : A Data Enhancement Pipeline for Data-Centric AI
    • [cs.LG]CCasGNN: Collaborative Cascade Prediction Based on Graph Neural Networks
    • [cs.LG]Cadence: A Practical Time-series Partitioning Algorithm for Unlabeled IoT Sensor Streams
    • [cs.LG]CapsProm: A Capsule Network For Promoter Prediction
    • [cs.LG]Combining Learning from Human Feedback and Knowledge Engineering to Solve Hierarchical Tasks in Minecraft
    • [cs.LG]Creating Multimodal Interactive Agents with Imitation and Self-Supervised Learning
    • [cs.LG]Differentiable Generalised Predictive Coding
    • [cs.LG]Disentangled Counterfactual Recurrent Networks for Treatment Effect Inference over Time
    • [cs.LG]Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates
    • [cs.LG]Domain Generalization via Progressive Layer-wise and Channel-wise Dropout
    • [cs.LG]Enhanced Exploration in Neural Feature Selection for Deep Click-Through Rate Prediction Models via Ensemble of Gating Layers
    • [cs.LG]Extrapolation Frameworks in Cognitive Psychology Suitable for Study of Image Classification Models
    • [cs.LG]Federated Causal Discovery
    • [cs.LG]Federated Deep Reinforcement Learning for the Distributed Control of NextG Wireless Networks
    • [cs.LG]First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach
    • [cs.LG]Generative Adversarial Networks for Labeled Data Creation for Structural Damage Detection
    • [cs.LG]Godot Reinforcement Learning Agents
    • [cs.LG]Graph Neural Controlled Differential Equations for Traffic Forecasting
    • [cs.LG]Graph Neural Networks Accelerated Molecular Dynamics
    • [cs.LG]GraphPAS: Parallel Architecture Search for Graph Neural Networks
    • [cs.LG]Graphical Models with Attention for Context-Specific Independence and an Application to Perceptual Grouping
    • [cs.LG]In-flight Novelty Detection with Convolutional Neural Networks
    • [cs.LG]Information is Power: Intrinsic Control via Information Capture
    • [cs.LG]Lattice-Based Methods Surpass Sum-of-Squares in Clustering
    • [cs.LG]Location Leakage in Federated Signal Maps
    • [cs.LG]MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance
    • [cs.LG]More layers! End-to-end regression and uncertainty on tabular data with deep learning
    • [cs.LG]Neural Networks for Infectious Diseases Detection: Prospects and Challenges
    • [cs.LG]Noether Networks: Meta-Learning Useful Conserved Quantities
    • [cs.LG]OOD-GNN: Out-of-Distribution Generalized Graph Neural Network
    • [cs.LG]On the Effectiveness of Mode Exploration in Bayesian Model Averaging for Neural Networks
    • [cs.LG]PTR-PPO: Proximal Policy Optimization with Prioritized Trajectory Replay
    • [cs.LG]Pairwise Learning for Neural Link Prediction
    • [cs.LG]Permutation Equivariant Generative Adversarial Networks for Graphs
    • [cs.LG]Predict and Optimize: Through the Lens of Learning to Rank
    • [cs.LG]Predicting the Travel Distance of Patients to Access Healthcare using Deep Neural Networks
    • [cs.LG]Scalable Geometric Deep Learning on Molecular Graphs
    • [cs.LG]Scaling Structured Inference with Randomization
    • [cs.LG]Self-Organized Polynomial-Time Coordination Graphs
    • [cs.LG]Shrub Ensembles for Online Classification
    • [cs.LG]Spectral Complexity-scaled Generalization Bound of Complex-valued Neural Networks
    • [cs.LG]State-of-the-art predictive and prescriptive analytics for IEEE CIS 3rd Technical Challenge
    • [cs.LG]Tell me why! — Explanations support learning of relational and causal structure
    • [cs.LG]Top-Down Deep Clustering with Multi-generator GANs
    • [cs.LG]Toward a Taxonomy of Trust for Probabilistic Machine Learning
    • [cs.LG]Towards Modeling and Resolving Singular Parameter Spaces using Stratifolds
    • [cs.LG]Towards a Shared Rubric for Dataset Annotation
    • [cs.LG]Universalizing Weak Supervision
    • [cs.LG]Virtual Replay Cache
    • [cs.MM]RFGAN: RF-Base
    12ef
    d Human Synthesis
    • [cs.NE]Deep Surrogate Assisted MAP-Elites for Automated Hearthstone Deckbuilding
    • [cs.NE]Genetic Algorithm for Constrained Molecular Inverse Design
    • [cs.NE]Hybrid Self-Attention NEAT: A novel evolutionary approach to improve the NEAT algorithm
    • [cs.RO]A Deep Learning Driven Algorithmic Pipeline for Autonomous Navigation in Row-Based Crops
    • [cs.RO]A low-cost wave-solar powered Unmanned Surface Vehicle
    • [cs.RO]Adaptive Mimic: Deep Reinforcement Learning of Parameterized Bipedal Walking from Infeasible References
    • [cs.RO]Bridging the Model-Reality Gap with Lipschitz Network Adaptation
    • [cs.RO]Causal Imitative Model for Autonomous Driving
    • [cs.RO]Combining optimal control and learning for autonomous aerial navigation in novel indoor environments
    • [cs.RO]Control Parameters Considered Harmful: Detecting Range Specification Bugs in Drone Configuration Modules via Learning-Guided Search
    • [cs.RO]Guided Imitation of Task and Motion Planning
    • [cs.RO]Hybrid Visual SLAM for Underwater Vehicle Manipulator Systems
    • [cs.RO]PRM path smoothening by circular arc fillet method for mobile robot navigation
    • [cs.RO]Policy Search for Model Predictive Control with Application to Agile Drone Flight
    • [cs.RO]Pragmatic Implementation of Reinforcement Algorithms For Path Finding On Raspberry Pi
    • [cs.RO]Reinforcement Learning for Navigation of Mobile Robot with LiDAR
    • [cs.RO]Socially acceptable route planning and trajectory behavior analysis of personal mobility device for mobility management with improved sensing
    • [cs.RO]Soft Robots Modeling: a Literature Unwinding
    • [cs.SD]Audio Deepfake Perceptions in College Going Populations
    • [cs.SE]A Survey of Verification, Validation and Testing Solutions for Smart Contracts
    • [cs.SE]Manas: Mining Software Repositories to Assist AutoML
    • [cs.SI]Characterizing Retweet Bots: The Case of Black Market Accounts
    • [cs.SI]Dense and well-connected subgraph detection in dual networks
    • [cs.SI]Hypergraph Ego-networks and Their Temporal Evolution
    • [cs.SI]Predicting peer-to-peer and collective social contagion from individual behaviour
    • [econ.EM]Nonparametric Treatment Effect Identification in School Choice
    • [eess.AS]A Time-domain Generalized Wiener Filter for Multi-channel Speech Separation
    • [eess.IV]Accurate parameter estimation using scan-specific unsupervised deep learning for relaxometry and MR fingerprinting
    • [eess.IV]Dynamic imaging using Motion-Compensated SmooThness Regularization on Manifolds (MoCo-SToRM)
    • [eess.IV]Evaluating Generic Auto-ML Tools for Computational Pathology
    • [eess.IV]Hybrid guiding: A multi-resolution refinement approach for semantic segmentation of gigapixel histopathological images
    • [eess.IV]Image Compressed Sensing Using Non-local Neural Network
    • [eess.IV]Image Enhancement via Bilateral Learning
    • [eess.IV]Noise Distribution Adaptive Self-Supervised Image Denoising using Tweedie Distribution and Score Matching
    • [eess.IV]Organ localisation using supervised and semi supervised approaches combining reinforcement learning with imitation learning
    • [eess.IV]Quality control for more reliable integration of deep learning-based image segmentation into medical workflows
    • [eess.IV]RSBNet: One-Shot Neural Architecture Search for A Backbone Network in Remote Sensing Image Recognition
    • [eess.SP]Constrained Resource Allocation Problems in Communications: An Information-assisted Approach
    • [hep-ph]Machine Learning in the Search for New Fundamental Physics
    • [math.MG]A Proof of the Simplex Mean Width Conjecture
    • [math.NA]Interpolating between BSDEs and PINNs — deep learning for elliptic and parabolic boundary value problems
    • [math.NA]Stochastic Optimized Schwarz Methods for the Gravity Equations on Graphics Processing Unit
    • [math.OC]Improving Dynamic Regret in Distributed Online Mirror Descent Using Primal and Dual Information
    • [math.ST]Bless and curse of smoothness and phase transitions in nonparametric regressions: a nonasymptotic perspective
    • [math.ST]On the computation of a non-parametric estimator by convex optimization
    • [physics.comp-ph]Explicitly antisymmetrized neural network layers for variational Monte Carlo simulation
    • [physics.flu-dyn]Emulating Spatio-Temporal Realizations of Three-Dimensional Isotropic Turbulence via Deep Sequence Learning Models
    • [q-fin.MF]A Bayesian take on option pricing with Gaussian processes
    • [q-fin.PR]EmTract: Investor Emotions and Market Behavior
    • [quant-ph]QKSA: Quantum Knowledge Seeking Agent — resource-optimized reinforcement learning using quantum process tomography
    • [stat.AP]A Comparison of Estimand and Estimation Strategies for Clinical Trials in Early Parkinson’s Disease
    • [stat.AP]Analyzing Highly Correlated Chemical Toxicants Associated with Time to Pregnancy Using Discrete Survival Frailty Modeling Via Elastic Net
    • [stat.AP]Piecewise survival models: a change-point analysis on herpes zoster associated pain data revisited and extended
    • [stat.ME]A Function-Based Approach to Model the Measurement Error in Wearable Devices
    • [stat.ME]A Unifying Bayesian Approach for Sample Size Determination Using Design and Analysis Priors
    • [stat.ME]Bayesian Structural Equation Modeling in Multiple Omics Data Integration with Application to Circadian Genes
    • [stat.ME]Change-point regression with a smooth additive disturbance
    • [stat.ME]Conformal Sensitivity Analysis for Individual Treatment Effects
    • [stat.ME]Mesh-Based Solutions for Nonparametric Penalized Regression
    • [stat.ME]Posterior Predictive Null Checks
    • [stat.ME]Using principal stratification in analysis of clinical trials
    • [stat.ML]A generalization gap estimation for overparameterized models via Langevin functional variance
    • [stat.ML]Private Robust Estimation by Stabilizing Convex Relaxations
    • [stat.ML]Training Deep Models to be Explained with Fewer Examples
    • [stat.ML]Understanding Square Loss in Training Overparametrized Neural Network Classifiers
    • [stat.ML]Using Image Transformations to Learn Network Structure

    ·····································

    • [astro-ph.EP]Automation Of Transiting Exoplanet Detection, Identification and Habitability Assessment Using Machine Learning Approaches
    Pawel Pratyush, Akshata Gangrade
    http://arxiv.org/abs/2112.03298v1

    • [cond-mat.mtrl-sci]Grain segmentation in atomistic simulations using orientation-based iterative self-organizing data analysis
    M. Vimal, S. Sandfeld, A. Prakash
    http://arxiv.org/abs/2112.03348v1

    • [cond-mat.mtrl-sci]Physics guided deep learning generative models for crystal materials discovery
    Yong Zhao, Edirisuriya MD Siriwardane, Jianjun Hu
    http://arxiv.org/abs/2112.03528v1

    • [cs.AI]Neuro-Symbolic Inductive Logic Programming with Logical Neural Networks
    Prithviraj Sen, Breno W. S. R. de Carvalho, Ryan Riegel, Alexander Gray
    http://arxiv.org/abs/2112.03324v1

    • [cs.CL]A pragmatic account of the weak evidence effect
    Samuel A. Barnett, Robert D. Hawkins, Thomas L. Griffiths
    http://arxiv.org/abs/2112.03799v1

    • [cs.CL]Adapting BERT for Continual Learning of a Sequence of Aspect Sentiment Classification Tasks
    Zixuan Ke, Hu Xu, Bing Liu
    http://arxiv.org/abs/2112.03271v1

    • [cs.CL]Automated Story Generation as Question-Answering
    Louis Castricato, Spencer Frazier, Jonathan Balloch, Nitya Tarakad, Mark Riedl
    http://arxiv.org/abs/2112.03808v1

    • [cs.CL]Dataset Geography: Mapping Language Data to Language Users
    Fahim Faisal, Yinkai Wang, Antonios Anastasopoulos
    http://arxiv.org/abs/2112.03497v1

    • [cs.CL]GKS: Graph-based Knowledge Selector for Task-oriented Dialog System
    Jen-Chieh Yang, Jia-Yan Wu, Sung-Ping Chang, Ya-Chieh Huang
    http://arxiv.org/abs/2112.03719v1

    • [cs.CL]Ground-Truth, Whose Truth? — Examining the Challenges with Annotating Toxic Text Datasets
    Kofi Arhin, Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Moninder Singh
    http://arxiv.org/abs/2112.03529v1

    • [cs.CL]Improving Neural Cross-Lingual Summarization via Employing Optimal Transport Distance for Knowledge Distillation
    Thong Nguyen, Luu Anh Tuan
    http://arxiv.org/abs/2112.03473v1

    • [cs.CL]Interpretable Privacy Preservation of Text Representations Using Vector Steganography
    Geetanjali Bihani
    http://arxiv.org/abs/2112.02557v2

    • [cs.CL]JUSTICE: A Benchmark Dataset for Supreme Court’s Judgment Prediction
    Mohammad Alali, Shaayan Syed, Mohammed Alsayed, Smit Patel, Hemanth Bodala
    http://arxiv.org/abs/2112.03414v1

    • [cs.CL]Multi-speaker Emotional Text-to-speech Synthesizer
    Sungjae Cho, Soo-Young Lee
    http://arxiv.org/abs/2112.03557v1

    • [cs.CL]Natural Answer Generation: From Factoid Answer to Full-length Answer using Grammar Correction
    Manas Jain, Sriparna Saha, Pushpak Bhattacharyya, Gladvin Chinnadurai, Manish Kumar Vatsa
    http://arxiv.org/abs/2112.03849v1

    • [cs.CL]Parsing with Pretrained Language Models, Multiple Datasets, and Dataset Embeddings
    Rob van der Goot, Miryam de Lhoneux
    http://arxiv.org/abs/2112.03625v1

    • [cs.CL]Question Answering Survey: Directions, Challenges, Datasets, Evaluation Matrices
    Hariom A. Pandya, Brijesh S. Bhatt
    http://arxiv.org/abs/2112.03572v1

    • [cs.CL]Reducing Target Group Bias in Hate Speech Detectors
    Darsh J Shah, Sinong Wang, Han Fang, Hao Ma, Luke Zettlemoyer
    http://arxiv.org/abs/2112.03858v1

    • [cs.CL]UCD-CS at TREC 2021 Incident Streams Track
    Congcong Wang, David Lillis
    http://arxiv.org/abs/2112.03737v1

    • [cs.CL]UNITER-Based Situated Coreference Resolution with Rich Multimodal Input
    Yichen Huang, Yuchen Wang, Yik-Cheung Tam
    http://arxiv.org/abs/2112.03521v1

    • [cs.CL]raceBERT — A Transformer-based Model for Predicting Race from Names
    Prasanna Parasurama
    http://arxiv.org/abs/2112.03807v1

    • [cs.CR]Adversarial Machine Learning In Network Intrusion Detection Domain: A Systematic Review
    Huda Ali Alatwi, Charles Morisset
    http://arxiv.org/abs/2112.03315v1

    • [cs.CR]BDFA: A Blind Data Adversarial Bit-flip Attack on Deep Neural Networks
    Behnam Ghavami, Mani Sadati, Mohammad Shahidzadeh, Zhenman Fang, Lesley Shannon
    http://arxiv.org/abs/2112.03477v1

    • [cs.CR]BlockGC: A Joint Learning Framework for Account Identity Inference on Blockchain with Graph Contrast
    Jiajun Zhou, Chenkai Hu, Shenbo Gong, Jiaying Xu, Jie Shen, Qi Xuan
    http://arxiv.org/abs/2112.03659v1

    • [cs.CR]Blockchain Synchronous Trust Consensus Model
    Christopher Gorog, Terrance E. Boult
    http://arxiv.org/abs/2112.03692v1

    • [cs.CR]Defending against Model Stealing via Verifying Embedded External Features
    Yiming Li, Linghui Zhu, Xiaojun Jia, Yong Jiang, Shu-Tao Xia, Xiaochun Cao
    http://arxiv.org/abs/2112.03476v1

    • [cs.CR]Does Proprietary Software Still Offer Protection of Intellectual Property in the Age of Machine Learning? — A Case Study using Dual Energy CT Data
    Andreas Maier, Seung Hee Yang, Farhad Maleki, Nikesh Muthukrishnan, Reza Forghani
    http://arxiv.org/abs/2112.03678v1

    • [cs.CR]Membership Inference Attacks From First Principles
    Nicholas Carlini, Steve Chien, Milad Nasr, Shuang Song, Andreas Terzis, Florian Tramer
    http://arxiv.org/abs/2112.03570v1

    • [cs.CR]Test-Time Detection of Backdoor Triggers for Poisoned Deep Neural Networks
    Xi Li, Zhen Xiang, David J. Miller, George Kesidis
    http://arxiv.org/abs/2112.03350v1

    • [cs.CV]A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion
    Zhaoyang Lyu, Zhifeng Kong, Xudong Xu, Liang Pan, Dahua Lin
    http://arxiv.org/abs/2112.03530v1

    • [cs.CV]A Contrastive Distillation Approach for Incremental Semantic Segmentation in Aerial Images
    Edoardo Arnaudo, Fabio Cermelli, Antonio Tavera, Claudio Rossi, Barbara Caputo
    http://arxiv.org/abs/2112.03814v1

    • [cs.CV]A Survey on Intrinsic Images: Delving Deep Into Lambert and Beyond
    Elena Garces, Carlos Rodriguez-Pardo, Dan Casas, Jorge Lopez-Moreno
    http://arxiv.org/abs/2112.03842v1

    • [cs.CV]ADD: Frequency Attention and Multi-View based Knowledge Distillation to Detect Low-Quality Compressed Deepfake Images
    Binh M. Le, Simon S. Woo
    http://arxiv.org/abs/2112.03553v1

    • [cs.CV]Activation to Saliency: Forming High-Quality Labels for Unsupervised Salient Object Detection
    Huajun Zhou, Peijia Chen, Lingxiao Yang, Jianhuang Lai, Xiaohua Xie
    http://arxiv.org/abs/2112.03650v1

    • [cs.CV]Bootstrapping ViTs: Towards Liberating Vision Transformers from Pre-training
    Haofei Zhang, Jiarui Duan, Mengqi Xue, Jie Song, Li Sun, Mingli Song
    http://arxiv.org/abs/2112.03552v1

    • [cs.CV]CG-NeRF: Conditional Generative Neural Radiance Fields
    Kyungmin Jo, Gyumin Shim, Sanghun Jung, Soyoung Yang, Jaegul Choo
    http://arxiv.org/abs/2112.03517v1

    • [cs.CV]CMA-CLIP: Cross-Modality Attention CLIP for Image-Text Classification
    Huidong Liu, Shaoyuan Xu, Jinmiao Fu, Yang Liu, Ning Xie, Chien-chih Wang, Bryan Wang, Yi Sun
    http://arxiv.org/abs/2112.03562v1

    • [cs.CV]Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Recognition
    Tianyu Guo, Hong Liu, Zhan Chen, Mengyuan Liu, Tao Wang, Runwei Ding
    http://arxiv.org/abs/2112.03590v1

    • [cs.CV]DCAN: Improving Temporal Action Detection via Dual Context Aggregation
    Guo Chen, Yin-Dong Zheng, Limin Wang, Tong Lu
    http://arxiv.org/abs/2112.03612v1

    • [cs.CV]Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal
    Yucheng Shi, Yahong Han
    http://arxiv.org/abs/2112.03492v1

    • [cs.CV]Deep Level Set for Box-supervised Instance Segmentation in Aerial Images
    Wentong Li, Yijie Chen, Wenyu Liu, Jianke Zhu
    http://arxiv.org/abs/2112.03451v1

    • [cs.CV]Dense Depth Priors for Neural Radiance Fields from Sparse Input Views
    Barbara Roessle, Jonathan T. Barron, Ben Mildenhall, Pratul P. Srinivasan, Matthias Nießner
    http://arxiv.org/abs/2112.03288v1

    • [cs.CV]Dilated convolution with learnable spacings
    Ismail Khalfaoui Hassani, Thomas Pellegrini, Timothée Masquelier
    http://arxiv.org/abs/2112.03740v1

    • [cs.CV]E今日学术视野(2021.12.9) - 图2(GO)MOTION: Motion Augmented Event Stream for Egocentric Action Recognition
    Chiara Plizzari, Mirco Planamente, Gabriele Goletto, Marco Cannici, Emanuele Gusso, Matteo Matteucci, Barbara Caputo
    http://arxiv.org/abs/2112.03596v1

    • [cs.CV]Flexible Networks for Learning Physical Dynamics of Deformable Objects
    Jinhyung Park, DoHae Lee, In-Kwon Lee
    http://arxiv.org/abs/2112.03728v1

    • [cs.CV]GPU-Based Homotopy Continuation for Minimal Problems in Computer Vision
    Chiang-Heng Chien, Hongyi Fan, Ahmad Abdelfattah, Elias Tsigaridas, Stanimire Tomov, Benjamin Kimia
    http://arxiv.org/abs/2112.03444v1

    • [cs.CV]GaTector: A Unified Framework for Gaze Object Prediction
    Binglu Wang, Tao Hu, Baoshan Li, Xiaojuan Chen, Zhijie Zhang
    http://arxiv.org/abs/2112.03549v1

    • [cs.CV]Gaussian map predictions for 3D surface feature localisation and counting
    Justin Le Louëdec, Grzegorz Cielniak
    http://arxiv.org/abs/2112.03736v1

    • [cs.CV]Generation of Non-Deterministic Synthetic Face Datasets Guided by Identity Priors
    Marcel Grimmer, Haoyu Zhang, Raghavendra Ramachandra, Kiran Raja, Christoph Busch
    http://arxiv.org/abs/2112.03632v1

    • [cs.CV]Gram-SLD: Automatic Self-labeling and Detection for Instance Objects
    Rui Wang, Chengtun Wu, Jiawen Xin, Liang Zhang
    http://arxiv.org/abs/2112.03641v1

    • [cs.CV]Grounded Language-Image Pre-training
    Liunian Harold Li, Pengchuan Zhang, Haotian Zhang, Jianwei Yang, Chunyuan Li, Yiwu Zhong, Lijuan Wang, Lu Yuan, Lei Zhang, Jenq-Neng Hwang, Kai-Wei Chang, Jianfeng Gao
    http://arxiv.org/abs/2112.03857v1

    • [cs.CV]Handwritten Mathematical Expression Recognition via Attention Aggregation based Bi-directional Mutual Learning
    Xiaohang Bian, Bo Qin, Xiaozhe Xin, Jianwu Li, Xuefeng Su, Yanfeng Wang
    http://arxiv.org/abs/2112.03603v1

    • [cs.CV]Hybrid SNN-ANN: Energy-Efficient Classification and Object Detection for Event-Based Vision
    Alexander Kugele, Thomas Pfeil, Michael Pfeiffer, Elisabetta Chicca
    http://arxiv.org/abs/2112.03423v1

    • [cs.CV]Label Hallucination for Few-Shot Classification
    Yiren Jian, Lorenzo Torresani
    http://arxiv.org/abs/2112.03340v1

    • [cs.CV]Learning Connectivity with Graph Convolutional Networks for Skeleton-based Action Recognition
    Hichem Sahbi
    http://arxiv.org/abs/2112.03328v1

    • [cs.CV]Learning Instance and Task-Aware Dynamic Kernels for Few Shot Learning
    Rongkai Ma, Pengfei Fang, Gil Avraham, Yan Zuo, Tom Drummond, Mehrtash Harandi
    http://arxiv.org/abs/2112.03494v1

    • [cs.CV]Learning to Solve Hard Minimal Problems
    Petr Hruby, Timothy Duff, Anton Leykin, Tomas Pajdla
    http://arxiv.org/abs/2112.03424v1

    • [cs.CV]Low-rank Tensor Decomposition for Compression of Convolutional Neural Networks Using Funnel Regularization
    Bo-Shiuan Chu, Che-Rung Lee
    http://arxiv.org/abs/2112.03690v1

    • [cs.CV]MS-TCT: Multi-Scale Temporal ConvTransformer for Action Detection
    Rui Dai, Srijan Das, Kumara Kahatapitiya, Michael S. Ryoo, Francois Bremond
    http://arxiv.org/abs/2112.03902v1

    • [cs.CV]Parallel Discrete Convolutions on Adaptive Particle Representations of Images
    Joel Jonsson, Bevan L. Cheeseman, Suryanarayana Maddu, Krzysztof Gonciarz, Ivo F. Sbalzarini
    http://arxiv.org/abs/2112.03592v1

    • [cs.CV]Polarimetric Pose Prediction
    Daoyi Gao, Yitong Li, Patrick Ruhkamp, Iuliia Skobleva, Magdalena Wysock, HyunJun Jung, Pengyuan Wang, Arturo Guridi, Nassir Navab, Benjamin Busam
    http://arxiv.org/abs/2112.03810v1

    • [cs.CV]Producing augmentation-invariant embeddings from real-life imagery
    Sergio Manuel Papadakis, Sanjay Addicam
    http://arxiv.org/abs/2112.03415v1

    • [cs.CV]Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields
    Dor Verbin, Peter Hedman, Ben Mildenhall, Todd Zickler, Jonathan T. Barron, Pratul P. Srinivasan
    http://arxiv.org/abs/2112.03907v1

    • [cs.CV]Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly Detection
    Shoubin Yu, Zhongyin Zhao, Haoshu Fang, Andong Deng, Haisheng Su, Dongliang Wang, Weihao Gan, Cewu Lu, Wei Wu
    http://arxiv.org/abs/2112.03649v1

    • [cs.CV]SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal
    Zhaoyang Sun, Yaxiong Chen, Shengwu Xiong
    http://arxiv.org/abs/2112.03631v1

    • [cs.CV]STC-mix: Space, Time, Channel mixing for Self-supervised Video Representation
    Srijan Das, Michael S. Ryoo
    http://arxiv.org/abs/2112.03906v1

    • [cs.CV]SalFBNet: Learning Pseudo-Saliency Distribution via Feedback Convolutional Networks
    Guanqun Ding, Nevrez Imamouglu, Ali Caglayan, Masahiro Murakawa, Ryosuke Nakamura
    http://arxiv.org/abs/2112.03731v1

    • [cs.CV]Saliency Diversified Deep Ensemble for Robustness to Adversaries
    Alex Bogun, Dimche Kostadinov, Damian Borth
    http://arxiv.org/abs/2112.03615v1

    • [cs.CV]Self-Supervised Camera Self-Calibration from Video
    Jiading Fang, Igor Vasiljevic, Vitor Guizilini, Rares Ambrus, Greg Shakhnarovich, Adrien Gaidon, Matthew R. Walter
    http://arxiv.org/abs/2112.03325v1

    • [cs.CV]Suppressing Static Visual Cues via Normalizing Flows for Self-Supervised Video Representation Learning
    Manlin Zhang, Jinpeng Wang, Andy J. Ma
    http://arxiv.org/abs/2112.03803v1

    • [cs.CV]TCGL: Temporal Contrastive Graph for Self-supervised Video Representation Learning
    Yang Liu, Keze Wang, Lingbo Liu, Haoyuan Lan, Liang Lin
    http://arxiv.org/abs/2112.03587v1

    • [cs.CV]Time-Equivariant Contrastive Video Representation Learning
    Simon Jenni, Hailin Jin
    http://arxiv.org/abs/2112.03624v1

    • [cs.CV]Traversing within the Gaussian Typical Set: Differentiable Gaussianization Layers for Inverse Problems Augmented by Normalizing Flows
    Dongzhuo Li, Huseyin Denli
    http://arxiv.org/abs/2112.03860v1

    • [cs.CV]Unsupervised Learning of Compositional Scene Representations from Multiple Unspecified Viewpoints
    Jinyang Yuan, Bin Li, Xiangyang Xue
    http://arxiv.org/abs/2112.03568v1

    • [cs.CV]Variance-Aware Weight Initialization for Point Convolutional Neural Networks
    Pedro Hermosilla, Michael Schelling, Tobias Ritschel, Timo Ropinski
    http://arxiv.org/abs/2112.03777v1

    • [cs.CV]Vehicle trajectory prediction works, but not everywhere
    Mohammadhossein Bahari, Saeed Saadatnejad, Ahmad Rahimi, Mohammad Shaverdikondori, Mohammad Shahidzadeh, Seyed-Mohsen Moosavi-Dezfooli, Alexandre Alahi
    http://arxiv.org/abs/2112.03909v1

    • [cs.CV]ViewCLR: Learning Self-supervised Video Representation for Unseen Viewpoints
    Srijan Das, Michael S. Ryoo
    http://arxiv.org/abs/2112.03905v1

    • [cs.CV]VizExtract: Automatic Relation Extraction from Data Visualizations
    Dale Decatur, Sanjay Krishnan
    http://arxiv.org/abs/2112.03485v1

    • [cs.CV]Voxelized 3D Feature Aggregation for Multiview Detection
    Jiahao Ma, Jinguang Tong, Shan Wang, Wei Zhao, Liang Zheng, Chuong Nguyen
    http://arxiv.org/abs/2112.03471v1

    • [cs.CV]Wild ToFu: Improving Range and Quality of Indirect Time-of-Flight Depth with RGB Fusion in Challenging Environments
    HyunJun Jung, Nikolas Brasch, Ales Leonardis, Nassir Navab, Benjamin Busam
    http://arxiv.org/abs/2112.03750v1

    • [cs.CY]Datensouveränität für Verbraucher:innen: Technische Ansätze durch KI-basierte Transparenz und Auskunft im Kontext der DSGVO
    Elias Grünewald, Frank Pallas
    http://arxiv.org/abs/2112.03879v1

    • [cs.CY]On Information Processing Limitations In Humans and Machines
    Birgitta Dresp-Langley
    http://arxiv.org/abs/2112.03669v1

    • [cs.CY]Stupid, Evil, or Both? Understanding the Smittestopp conflict
    Hans Heum
    http://arxiv.org/abs/2112.03839v1

    • [cs.DB]Glue: Adaptively Merging Single Table Cardinality to Estimate Join Query Size
    Rong Zhu, Tianjing Zeng, Andreas Pfadler, Wei Chen, Bolin Ding, Jingren Zhou
    http://arxiv.org/abs/2112.03458v1

    • [cs.DC]Campaign Knowledge Network: Building Knowledge for Campaign Efficiency
    Sachith Withana, Kshitij Mehta, Matthew Wolf, Beth Plale
    http://arxiv.org/abs/2112.03435v1

    • [cs.DC]Phase Transition of the 3-Majority Dynamics with Uniform Communication Noise
    Francesco d’Amore, Isabella Ziccardi
    http://arxiv.org/abs/2112.03543v1

    • [cs.DL]Change Summarization of Diachronic Scholarly Paper Collections by Semantic Evolution Analysis
    Naman Paharia, Muhammad Syafiq Mohd Pozi, Adam Jatowt
    http://arxiv.org/abs/2112.03634v1

    • [cs.DL]Disability and Library Services: Global Research Trend
    Swapan Kumar Patra
    http://arxiv.org/abs/2112.03580v1

    • [cs.DM]Multidimensional Assignment Problem for multipartite entity resolution
    Alla Kammerdiner, Alexander Semenov, Eduardo Pasiliao
    http://arxiv.org/abs/2112.03346v1

    • [cs.ET]Associative Memories Using Complex-Valued Hopfield Networks Based on Spin-Torque Oscillator Arrays
    Nitin Prasad, Prashansa Mukim, Advait Madhavan, Mark D. Stiles
    http://arxiv.org/abs/2112.03358v1

    • [cs.IR]A Sensitivity Analysis of the MSMARCO Passage Collection
    Joel Mackenzie, Matthias Petri, Alistair Moffat
    http://arxiv.org/abs/2112.03396v1

    • [cs.IR]Cross-domain User Preference Learning for Cold-start Recommendation
    Huiling Zhou, Jie Liu, Zhikang Li, Jin Yu, Hongxia Yang
    http://arxiv.org/abs/2112.03667v1

    • [cs.IR]Long-Tail Session-based Recommendation from Calibration
    Jiayi Chen, Wen Wu, Wei Zheng, Liang He
    http://arxiv.org/abs/2112.02581v2

    • [cs.IT]Gradient and Projection Free Distributed Online Min-Max Resource Optimization
    Jingrong Wang, Ben Liang
    http://arxiv.org/abs/2112.03896v1

    • [cs.IT]New Lower Bounds on the Capacity of Optical Fiber Channels via Optimized Shaping and Detection
    Marco Secondini, Stella Civelli, Enrico Forestieri, Lareb Zar Khan
    http://arxiv.org/abs/2112.03796v1

    • [cs.IT]On a 2-relative entropy
    James Fullwood
    http://arxiv.org/abs/2112.03582v1

    • [cs.IT]Semantic Coded Transmission: Architecture, Methodology, and Challenges
    Jincheng Dai, Ping Zhang, Kai Niu, Sixian Wang, Zhongwei Si, Xiaoqi Qin
    http://arxiv.org/abs/2112.03093v2

    • [cs.LG]A Continuous-time Stochastic Gradient Descent Method for Continuous Data
    Kexin Jin, Jonas Latz, Chenguang Liu, Carola-Bibiane Schönlieb
    http://arxiv.org/abs/2112.03754v1

    • [cs.LG]A Generic Approach for Enhancing GANs by Regularized Latent Optimization
    Yufan Zhou, Chunyuan Li, Changyou Chen, Jinhui Xu
    http://arxiv.org/abs/2112.03502v1

    • [cs.LG]A Novel Convergence Analysis for Algorithms of the Adam Family
    Zhishuai Guo, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang
    http://arxiv.org/abs/2112.03459v1

    • [cs.LG]A Piece-wise Polynomial Filtering Approach for Graph Neural Networks
    Vijay Lingam, Chanakya Ekbote, Manan Sharma, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam
    http://arxiv.org/abs/2112.03499v1

    • [cs.LG]A Unified Framework for Multi-distribution Density Ratio Estimation
    Lantao Yu, Yujia Jin, Stefano Ermon
    http://arxiv.org/abs/2112.03440v1

    • [cs.LG]A coarse space acceleration of deep-DDM
    Valentin Mercier, Serge Gratton, Pierre Boudier
    http://arxiv.org/abs/2112.03732v1

    • [cs.LG]A deep language model to predict metabolic network equilibria
    François Charton, Amaury Hayat, Sean T. McQuade, Nathaniel J. Merrill, Benedetto Piccoli
    http://arxiv.org/abs/2112.03588v1

    • [cs.LG]Attention-Based Model and Deep Reinforcement Learning for Distribution of Event Processing Tasks
    A. Mazayev, F. Al-Tam, N. Correia
    http://arxiv.org/abs/2112.03835v1

    • [cs.LG]Augment & Valuate : A Data Enhancement Pipeline for Data-Centric AI
    Youngjune Lee, Oh Joon Kwon, Haeju Lee, Joonyoung Kim, Kangwook Lee, Kee-Eung Kim
    http://arxiv.org/abs/2112.03837v1

    • [cs.LG]CCasGNN: Collaborative Cascade Prediction Based on Graph Neural Networks
    Yansong Wang, Xiaomeng Wang, Tao Jia
    http://arxiv.org/abs/2112.03644v1

    • [cs.LG]Cadence: A Practical Time-series Partitioning Algorithm for Unlabeled IoT Sensor Streams
    Tahiya Chowdhury, Murtadha Aldeer, Shantanu Laghate, Jorge Ortiz
    http://arxiv.org/abs/2112.03360v1

    • [cs.LG]CapsProm: A Capsule Network For Promoter Prediction
    Lauro Moraes, Pedro Silva, Eduardo Luz, Gladston Moreira
    http://arxiv.org/abs/2112.03710v1

    • [cs.LG]Combining Learning from Human Feedback and Knowledge Engineering to Solve Hierarchical Tasks in Minecraft
    Vinicius G. Goecks, Nicholas Waytowich, David Watkins, Bharat Prakash
    http://arxiv.org/abs/2112.03482v1

    • [cs.LG]Creating Multimodal Interactive Agents with Imitation and Self-Supervised Learning
    DeepMind Interactive Agents Team, Josh Abramson, Arun Ahuja, Arthur Brussee, Federico Carnevale, Mary Cassin, Felix Fischer, Petko Georgiev, Alex Goldin, Tim Harley, Felix Hill, Peter C Humphreys, Alden Hung, Jessica Landon, Timothy Lillicrap, Hamza Merzic, Alistair Muldal, Adam Santoro, Guy Scully, Tamara von Glehn
    1000, Greg Wayne, Nathaniel Wong, Chen Yan, Rui Zhu
    http://arxiv.org/abs/2112.03763v1

    • [cs.LG]Differentiable Generalised Predictive Coding
    André Ofner, Sebastian Stober
    http://arxiv.org/abs/2112.03378v1

    • [cs.LG]Disentangled Counterfactual Recurrent Networks for Treatment Effect Inference over Time
    Jeroen Berrevoets, Alicia Curth, Ioana Bica, Eoin McKinney, Mihaela van der Schaar
    http://arxiv.org/abs/2112.03811v1

    • [cs.LG]Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates
    Dan Ley, Umang Bhatt, Adrian Weller
    http://arxiv.org/abs/2112.02646v2

    • [cs.LG]Domain Generalization via Progressive Layer-wise and Channel-wise Dropout
    Jintao Guo, Lei Qi, Yinghuan Shi, Yang Gao
    http://arxiv.org/abs/2112.03676v1

    • [cs.LG]Enhanced Exploration in Neural Feature Selection for Deep Click-Through Rate Prediction Models via Ensemble of Gating Layers
    Lin Guan, Xia Xiao, Ming Chen, Youlong Cheng
    http://arxiv.org/abs/2112.03487v1

    • [cs.LG]Extrapolation Frameworks in Cognitive Psychology Suitable for Study of Image Classification Models
    Roozbeh Yousefzadeh, Jessica A. Mollick
    http://arxiv.org/abs/2112.03411v1

    • [cs.LG]Federated Causal Discovery
    Erdun Gao, Junjia Chen, Li Shen, Tongliang Liu, Mingming Gong, Howard Bondell
    http://arxiv.org/abs/2112.03555v1

    • [cs.LG]Federated Deep Reinforcement Learning for the Distributed Control of NextG Wireless Networks
    Peyman Tehrani, Francesco Restuccia, Marco Levorato
    http://arxiv.org/abs/2112.03465v1

    • [cs.LG]First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach
    Andrew Wagenmaker, Yifang Chen, Max Simchowitz, Simon S. Du, Kevin Jamieson
    http://arxiv.org/abs/2112.03432v1

    • [cs.LG]Generative Adversarial Networks for Labeled Data Creation for Structural Damage Detection
    Furkan Luleci, F. Necati Catbas, Onur Avci
    http://arxiv.org/abs/2112.03478v1

    • [cs.LG]Godot Reinforcement Learning Agents
    Edward Beeching, Jilles Debangoye, Olivier Simonin, Christian Wolf
    http://arxiv.org/abs/2112.03636v1

    • [cs.LG]Graph Neural Controlled Differential Equations for Traffic Forecasting
    Jeongwhan Choi, Hwangyong Choi, Jeehyun Hwang, Noseong Park
    http://arxiv.org/abs/2112.03558v1

    • [cs.LG]Graph Neural Networks Accelerated Molecular Dynamics
    Zijie Li, Kazem Meidani, Prakarsh Yadav, Amir Barati Farimani
    http://arxiv.org/abs/2112.03383v1

    • [cs.LG]GraphPAS: Parallel Architecture Search for Graph Neural Networks
    Jiamin Chen, Jianliang Gao, Yibo Chen, Oloulade Babatounde Moctard, Tengfei Lyu, Zhao Li
    http://arxiv.org/abs/2112.03461v1

    • [cs.LG]Graphical Models with Attention for Context-Specific Independence and an Application to Perceptual Grouping
    Guangyao Zhou, Wolfgang Lehrach, Antoine Dedieu, Miguel Lázaro-Gredilla, Dileep George
    http://arxiv.org/abs/2112.03371v1

    • [cs.LG]In-flight Novelty Detection with Convolutional Neural Networks
    Adam Hartwell, Felipe Montana, Will Jacobs, Visakan Kadirkamanathan, Andrew R Mills, Tom Clark
    http://arxiv.org/abs/2112.03765v1

    • [cs.LG]Information is Power: Intrinsic Control via Information Capture
    Nicholas Rhinehart, Jenny Wang, Glen Berseth, John D. Co-Reyes, Danijar Hafner, Chelsea Finn, Sergey Levine
    http://arxiv.org/abs/2112.03899v1

    • [cs.LG]Lattice-Based Methods Surpass Sum-of-Squares in Clustering
    Ilias Zadik, Min Jae Song, Alexander S. Wein, Joan Bruna
    http://arxiv.org/abs/2112.03898v1

    • [cs.LG]Location Leakage in Federated Signal Maps
    Evita Bakopoulou, Jiang Zhang, Justin Ley, Konstantinos Psounis, Athina Markopoulou
    http://arxiv.org/abs/2112.03452v1

    • [cs.LG]MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance
    Michael Luo, Ashwin Balakrishna, Brijen Thananjeyan, Suraj Nair, Julian Ibarz, Jie Tan, Chelsea Finn, Ion Stoica, Ken Goldberg
    http://arxiv.org/abs/2112.03575v1

    • [cs.LG]More layers! End-to-end regression and uncertainty on tabular data with deep learning
    Ivan Bondarenko
    http://arxiv.org/abs/2112.03566v1

    • [cs.LG]Neural Networks for Infectious Diseases Detection: Prospects and Challenges
    Muhammad Azeem, Shumaila Javaid, Hamza Fahim, Nasir Saeed
    http://arxiv.org/abs/2112.03571v1

    • [cs.LG]Noether Networks: Meta-Learning Useful Conserved Quantities
    Ferran Alet, Dylan Doblar, Allan Zhou, Joshua Tenenbaum, Kenji Kawaguchi, Chelsea Finn
    http://arxiv.org/abs/2112.03321v1

    • [cs.LG]OOD-GNN: Out-of-Distribution Generalized Graph Neural Network
    Haoyang Li, Xin Wang, Ziwei Zhang, Wenwu Zhu
    http://arxiv.org/abs/2112.03806v1

    • [cs.LG]On the Effectiveness of Mode Exploration in Bayesian Model Averaging for Neural Networks
    John T. Holodnak, Allan B. Wollaber
    http://arxiv.org/abs/2112.03773v1

    • [cs.LG]PTR-PPO: Proximal Policy Optimization with Prioritized Trajectory Replay
    Xingxing Liang, Yang Ma, Yanghe Feng, Zhong Liu
    http://arxiv.org/abs/2112.03798v1

    • [cs.LG]Pairwise Learning for Neural Link Prediction
    Zhitao Wang, Yong Zhou, Litao Hong, Yuanhang Zou, Hanjing Su
    http://arxiv.org/abs/2112.02936v2

    • [cs.LG]Permutation Equivariant Generative Adversarial Networks for Graphs
    Yoann Boget, Magda Gregorova, Alexandros Kalousis
    http://arxiv.org/abs/2112.03621v1

    • [cs.LG]Predict and Optimize: Through the Lens of Learning to Rank
    Jayanta Mandi, Víctor Bucarey, Maxime Mulamba, Tias Guns
    http://arxiv.org/abs/2112.03609v1

    • [cs.LG]Predicting the Travel Distance of Patients to Access Healthcare using Deep Neural Networks
    Li-Chin Chen, Ji-Tian Sheu, Yuh-Jue Chuang, Yu Tsao
    http://arxiv.org/abs/2112.03541v1

    • [cs.LG]Scalable Geometric Deep Learning on Molecular Graphs
    Nathan C. Frey, Siddharth Samsi, Joseph McDonald, Lin Li, Connor W. Coley, Vijay Gadepally
    http://arxiv.org/abs/2112.03364v1

    • [cs.LG]Scaling Structured Inference with Randomization
    Yao Fu, Mirella Lapata
    http://arxiv.org/abs/2112.03638v1

    • [cs.LG]Self-Organized Polynomial-Time Coordination Graphs
    Qianlan Yang, Weijun Dong, Zhizhou Ren, Jianhao Wang, Tonghan Wang, Chongjie Zhang
    http://arxiv.org/abs/2112.03547v1

    • [cs.LG]Shrub Ensembles for Online Classification
    Sebastian Buschjäger, Sibylle Hess, Katharina Morik
    http://arxiv.org/abs/2112.03723v1

    • [cs.LG]Spectral Complexity-scaled Generalization Bound of Complex-valued Neural Networks
    Haowen Chen, Fengxiang He, Shiye Lei, Dacheng Tao
    http://arxiv.org/abs/2112.03467v1

    • [cs.LG]State-of-the-art predictive and prescriptive analytics for IEEE CIS 3rd Technical Challenge
    Mahdi Abolghasemi, Rasul Esmaeilbeigi
    http://arxiv.org/abs/2112.03595v1

    • [cs.LG]Tell me why! — Explanations support learning of relational and causal structure
    Andrew K. Lampinen, Nicholas A. Roy, Ishita Dasgupta, Stephanie C. Y. Chan, Allison C. Tam, James L. McClelland, Chen Yan, Adam Santoro, Neil C. Rabinowitz, Jane X. Wang, Felix Hill
    http://arxiv.org/abs/2112.03753v1

    • [cs.LG]Top-Down Deep Clustering with Multi-generator GANs
    Daniel de Mello, Renato Assunção, Fabricio Murai
    http://arxiv.org/abs/2112.03398v1

    • [cs.LG]Toward a Taxonomy of Trust for Probabilistic Machine Learning
    Tamara Broderick, Andrew Gelman, Rachael Meager, Anna L. Smith, Tian Zheng
    http://arxiv.org/abs/2112.03270v1

    • [cs.LG]Towards Modeling and Resolving Singular Parameter Spaces using Stratifolds
    Pascal Mattia Esser, Frank Nielsen
    http://arxiv.org/abs/2112.03734v1

    • [cs.LG]Towards a Shared Rubric for Dataset Annotation
    Andrew Marc Greene
    http://arxiv.org/abs/2112.03867v1

    • [cs.LG]Universalizing Weak Supervision
    Changho Shin, Winfred Li, Harit Vishwakarma, Nicholas Roberts, Frederic Sala
    http://arxiv.org/abs/2112.03865v1

    • [cs.LG]Virtual Replay Cache
    Brett Daley, Christopher Amato
    http://arxiv.org/abs/2112.03421v1

    • [cs.MM]RFGAN: RF-Base
    12ef
    d Human Synthesis
    Cong Yu, Zhi Wu, Dongheng Zhang, Zhi Lu, Yang Hu, Yan Chen
    http://arxiv.org/abs/2112.03727v1

    • [cs.NE]Deep Surrogate Assisted MAP-Elites for Automated Hearthstone Deckbuilding
    Yulun Zhang, Matthew C. Fontaine, Amy K. Hoover, Stefanos Nikolaidis
    http://arxiv.org/abs/2112.03534v1

    • [cs.NE]Genetic Algorithm for Constrained Molecular Inverse Design
    Yurim Lee, Gydam Choi, Minsug Yoon, Cheongwon Kim
    http://arxiv.org/abs/2112.03518v1

    • [cs.NE]Hybrid Self-Attention NEAT: A novel evolutionary approach to improve the NEAT algorithm
    Saman Khamesian, Hamed Malek
    http://arxiv.org/abs/2112.03670v1

    • [cs.RO]A Deep Learning Driven Algorithmic Pipeline for Autonomous Navigation in Row-Based Crops
    Simone Cerrato, Vittorio Mazzia, Francesco Salvetti, Marcello Chiaberge
    http://arxiv.org/abs/2112.03816v1

    • [cs.RO]A low-cost wave-solar powered Unmanned Surface Vehicle
    Moustafa Elkolali, Ahmed Al-Tawil, Lennard Much, Ryan Schrader, Olivier Masset, Marina Sayols, Andrew Jenkins, Sara Alonso, Alfredo Carella, Alex Alcocer
    http://arxiv.org/abs/2112.03685v1

    • [cs.RO]Adaptive Mimic: Deep Reinforcement Learning of Parameterized Bipedal Walking from Infeasible References
    Chong Zhang, Qi Wu, Liqian Ma, Hongyuan Su
    http://arxiv.org/abs/2112.03735v1

    • [cs.RO]Bridging the Model-Reality Gap with Lipschitz Network Adaptation
    Siqi Zhou, Karime Pereida, Wenda Zhao, Angela P. Schoellig
    http://arxiv.org/abs/2112.03756v1

    • [cs.RO]Causal Imitative Model for Autonomous Driving
    Mohammad Reza Samsami, Mohammadhossein Bahari, Saber Salehkaleybar, Alexandre Alahi
    http://arxiv.org/abs/2112.03908v1

    • [cs.RO]Combining optimal control and learning for autonomous aerial navigation in novel indoor environments
    Kevin Lin, Brian Huo, Megan Hu
    http://arxiv.org/abs/2112.03554v1

    • [cs.RO]Control Parameters Considered Harmful: Detecting Range Specification Bugs in Drone Configuration Modules via Learning-Guided Search
    Ruidong Han, Chao Yang, Siqi Ma, JiangFeng Ma, Cong Sun, Juanru Li, Elisa Bertino
    http://arxiv.org/abs/2112.03511v1

    • [cs.RO]Guided Imitation of Task and Motion Planning
    Michael James McDonald, Dylan Hadfield-Menell
    http://arxiv.org/abs/2112.03386v1

    • [cs.RO]Hybrid Visual SLAM for Underwater Vehicle Manipulator Systems
    Gideon Billings, Richard Camilli, Matthew Johnson-Roberson
    http://arxiv.org/abs/2112.03826v1

    • [cs.RO]PRM path smoothening by circular arc fillet method for mobile robot navigation
    Meral Kılıçarslan Ouach, Tolga Eren, Evrencan Özcan
    http://arxiv.org/abs/2112.03604v1

    • [cs.RO]Policy Search for Model Predictive Control with Application to Agile Drone Flight
    Yunlong Song, Davide Scaramuzza
    http://arxiv.org/abs/2112.03850v1

    • [cs.RO]Pragmatic Implementation of Reinforcement Algorithms For Path Finding On Raspberry Pi
    Serena Raju, Sherin Shibu, Riya Mol Raji, Joel Thomas
    http://arxiv.org/abs/2112.03577v1

    • [cs.RO]Reinforcement Learning for Navigation of Mobile Robot with LiDAR
    Inhwan Kim, Sarvar Hussain Nengroo, Dongsoo Har
    http://arxiv.org/abs/2112.02954v2

    • [cs.RO]Socially acceptable route planning and trajectory behavior analysis of personal mobility device for mobility management with improved sensing
    Sumit Mishra, Praveen Kumar Rajendran, Dongsoo Har
    http://arxiv.org/abs/2112.03526v1

    • [cs.RO]Soft Robots Modeling: a Literature Unwinding
    Costanza Armanini, Conor Messer, Anup Teejo Mathew, Frédéric Boyer, Christian Duriez, Federico Renda
    http://arxiv.org/abs/2112.03645v1

    • [cs.SD]Audio Deepfake Perceptions in College Going Populations
    Gabrielle Watson, Zahra Khanjani, Vandana P. Janeja
    http://arxiv.org/abs/2112.03351v1

    • [cs.SE]A Survey of Verification, Validation and Testing Solutions for Smart Contracts
    Chaïmaa Benabbou, Önder Gürcan
    http://arxiv.org/abs/2112.03426v1

    • [cs.SE]Manas: Mining Software Repositories to Assist AutoML
    Giang Nguyen, Johir Islam, Rangeet Pan, Hridesh Rajan
    http://arxiv.org/abs/2112.03395v1

    • [cs.SI]Characterizing Retweet Bots: The Case of Black Market Accounts
    Tuğrulcan Elmas, Rebekah Overdorf, Karl Aberer
    http://arxiv.org/abs/2112.02366v2

    • [cs.SI]Dense and well-connected subgraph detection in dual networks
    Tianyi Chen, Francesco Bonchi, David Garcia-Soriano, Atsushi Miyauchi, Charalampos E. Tsourakakis
    http://arxiv.org/abs/2112.03337v1

    • [cs.SI]Hypergraph Ego-networks and Their Temporal Evolution
    Cazamere Comrie, Jon Kleinberg
    http://arxiv.org/abs/2112.03498v1

    • [cs.SI]Predicting peer-to-peer and collective social contagion from individual behaviour
    Fang Zhou, Linyuan Lü, Jianguo Liu, Manuel Sebastian Mariani
    http://arxiv.org/abs/2112.03546v1

    • [econ.EM]Nonparametric Treatment Effect Identification in School Choice
    Jiafeng Chen
    http://arxiv.org/abs/2112.03872v1

    • [eess.AS]A Time-domain Generalized Wiener Filter for Multi-channel Speech Separation
    Yi Luo
    http://arxiv.org/abs/2112.03533v1

    • [eess.IV]Accurate parameter estimation using scan-specific unsupervised deep learning for relaxometry and MR fingerprinting
    Mengze Gao, Huihui Ye, Tae Hyung Kim, Zijing Zhang, Seohee So, Berkin Bilgic
    http://arxiv.org/abs/2112.03815v1

    • [eess.IV]Dynamic imaging using Motion-Compensated SmooThness Regularization on Manifolds (MoCo-SToRM)
    Qing Zou, Luis A. Torres, Sean B. Fain, Nara S. Higano, Alister J. Bates, Mathews Jacob
    http://arxiv.org/abs/2112.03380v1

    • [eess.IV]Evaluating Generic Auto-ML Tools for Computational Pathology
    Lars Ole Schwen, Daniela Schacherer, Christian Geißler, André Homeyer
    http://arxiv.org/abs/2112.03622v1

    • [eess.IV]Hybrid guiding: A multi-resolution refinement approach for semantic segmentation of gigapixel histopathological images
    André Pedersen, Erik Smistad, Tor V. Rise, Vibeke G. Dale, Henrik S. Pettersen, Tor-Arne S. Nordmo, David Bouget, Ingerid Reinertsen, Marit Valla
    http://arxiv.org/abs/2112.03455v1

    • [eess.IV]Image Compressed Sensing Using Non-local Neural Network
    Wenxue Cui, Shaohui Liu, Feng Jiang, Debin Zhao
    http://arxiv.org/abs/2112.03712v1

    • [eess.IV]Image Enhancement via Bilateral Learning
    Saeedeh Rezaee, Nezam Mahdavi-Amiri
    http://arxiv.org/abs/2112.03888v1

    • [eess.IV]Noise Distribution Adaptive Self-Supervised Image Denoising using Tweedie Distribution and Score Matching
    Kwanyoung Kim, Taesung Kwon, Jong Chul Ye
    http://arxiv.org/abs/2112.03696v1

    • [eess.IV]Organ localisation using supervised and semi supervised approaches combining reinforcement learning with imitation learning
    Sankaran Iyer, Alan Blair, Laugh
    1000
    lin Dawes, Daniel Moses, Christopher White, Arcot Sowmya
    http://arxiv.org/abs/2112.03276v1

    • [eess.IV]Quality control for more reliable integration of deep learning-based image segmentation into medical workflows
    Elena Williams, Sebastian Niehaus, Janis Reinelt, Alberto Merola, Paul Glad Mihai, Ingo Roeder, Nico Scherf, Maria del C. Valdés Hernández
    http://arxiv.org/abs/2112.03277v1

    • [eess.IV]RSBNet: One-Shot Neural Architecture Search for A Backbone Network in Remote Sensing Image Recognition
    Cheng Peng, Yangyang Li, Ronghua Shang, Licheng Jiao
    http://arxiv.org/abs/2112.03456v1

    • [eess.SP]Constrained Resource Allocation Problems in Communications: An Information-assisted Approach
    I. Zakir Ahmed, Hamid Sadjadpour, Shahram Yousefi
    http://arxiv.org/abs/2112.03512v1

    • [hep-ph]Machine Learning in the Search for New Fundamental Physics
    Georgia Karagiorgi, Gregor Kasieczka, Scott Kravitz, Benjamin Nachman, David Shih
    http://arxiv.org/abs/2112.03769v1

    • [math.MG]A Proof of the Simplex Mean Width Conjecture
    Aaron Goldsmith
    http://arxiv.org/abs/2112.03393v1

    • [math.NA]Interpolating between BSDEs and PINNs — deep learning for elliptic and parabolic boundary value problems
    Nikolas Nüsken, Lorenz Richter
    http://arxiv.org/abs/2112.03749v1

    • [math.NA]Stochastic Optimized Schwarz Methods for the Gravity Equations on Graphics Processing Unit
    Abal-Kassim Cheik Ahamed, Frederic Magoules
    http://arxiv.org/abs/2112.03851v1

    • [math.OC]Improving Dynamic Regret in Distributed Online Mirror Descent Using Primal and Dual Information
    Nima Eshraghi, Ben Liang
    http://arxiv.org/abs/2112.03504v1

    • [math.ST]Bless and curse of smoothness and phase transitions in nonparametric regressions: a nonasymptotic perspective
    Ying Zhu
    http://arxiv.org/abs/2112.03626v1

    • [math.ST]On the computation of a non-parametric estimator by convex optimization
    Akshay Seshadri, Stephen Becker
    http://arxiv.org/abs/2112.03390v1

    • [physics.comp-ph]Explicitly antisymmetrized neural network layers for variational Monte Carlo simulation
    Jeffmin Lin, Gil Goldshlager, Lin Lin
    http://arxiv.org/abs/2112.03491v1

    • [physics.flu-dyn]Emulating Spatio-Temporal Realizations of Three-Dimensional Isotropic Turbulence via Deep Sequence Learning Models
    Mohammadreza Momenifar, Enmao Diao, Vahid Tarokh, Andrew D. Bragg
    http://arxiv.org/abs/2112.03469v1

    • [q-fin.MF]A Bayesian take on option pricing with Gaussian processes
    Martin Tegner, Stephen Roberts
    http://arxiv.org/abs/2112.03718v1

    • [q-fin.PR]EmTract: Investor Emotions and Market Behavior
    Domonkos Vamossy, Rolf Skog
    http://arxiv.org/abs/2112.03868v1

    • [quant-ph]QKSA: Quantum Knowledge Seeking Agent — resource-optimized reinforcement learning using quantum process tomography
    Aritra Sarkar, Zaid Al-Ars, Harshitta Gandhi, Koen Bertels
    http://arxiv.org/abs/2112.03643v1

    • [stat.AP]A Comparison of Estimand and Estimation Strategies for Clinical Trials in Early Parkinson’s Disease
    Alessandro Noci, Marcel Wolbers, Markus Abt, Corine Baayen, Hans Ulrich Burger, Man Jin, Weining Zhao Robieson
    http://arxiv.org/abs/2112.03700v1

    • [stat.AP]Analyzing Highly Correlated Chemical Toxicants Associated with Time to Pregnancy Using Discrete Survival Frailty Modeling Via Elastic Net
    Abhisek Saha, Rajeshwari Sundaram
    http://arxiv.org/abs/2112.03762v1

    • [stat.AP]Piecewise survival models: a change-point analysis on herpes zoster associated pain data revisited and extended
    Dimitra Eleftheriou, Dimitris Karlis
    http://arxiv.org/abs/2112.03688v1

    • [stat.ME]A Function-Based Approach to Model the Measurement Error in Wearable Devices
    Sneha Jadhav, Carmen D. Tekwe, Yuanyuan Luan
    http://arxiv.org/abs/2112.03539v1

    • [stat.ME]A Unifying Bayesian Approach for Sample Size Determination Using Design and Analysis Priors
    Jane Pan, Sudipto Banerjee
    http://arxiv.org/abs/2112.03509v1

    • [stat.ME]Bayesian Structural Equation Modeling in Multiple Omics Data Integration with Application to Circadian Genes
    Arnab Kumar Maity, Sang Chan Lee, Bani K. Mallick, Tapasree Roy Sarkar
    http://arxiv.org/abs/2112.03330v1

    • [stat.ME]Change-point regression with a smooth additive disturbance
    Florian Pein
    http://arxiv.org/abs/2112.03878v1

    • [stat.ME]Conformal Sensitivity Analysis for Individual Treatment Effects
    Mingz
    5278
    hang Yin, Claudia Shi, Yixin Wang, David M. Blei
    http://arxiv.org/abs/2112.03493v1

    • [stat.ME]Mesh-Based Solutions for Nonparametric Penalized Regression
    Brayan Ortiz, Noah Simon
    http://arxiv.org/abs/2112.03428v1

    • [stat.ME]Posterior Predictive Null Checks
    Gemma E. Moran, John P. Cunningham, David M. Blei
    http://arxiv.org/abs/2112.03333v1

    • [stat.ME]Using principal stratification in analysis of clinical trials
    Ilya Lipkovich, Bohdana Ratitch, Yongming Qu, Xiang Zhang, Mingyang Shan, Craig Mallinckrodt
    http://arxiv.org/abs/2112.03352v1

    • [stat.ML]A generalization gap estimation for overparameterized models via Langevin functional variance
    Akifumi Okuno, Keisuke Yano
    http://arxiv.org/abs/2112.03660v1

    • [stat.ML]Private Robust Estimation by Stabilizing Convex Relaxations
    Pravesh K. Kothari, Pasin Manurangsi, Ameya Velingker
    http://arxiv.org/abs/2112.03548v1

    • [stat.ML]Training Deep Models to be Explained with Fewer Examples
    Tomoharu Iwata, Yuya Yoshikawa
    http://arxiv.org/abs/2112.03508v1

    • [stat.ML]Understanding Square Loss in Training Overparametrized Neural Network Classifiers
    Tianyang Hu, Jun Wang, Wenjia Wang, Zhenguo Li
    http://arxiv.org/abs/2112.03657v1

    • [stat.ML]Using Image Transformations to Learn Network Structure
    Brayan Ortiz, Amitabh Sinha
    http://arxiv.org/abs/2112.03419v1