Machine Learning (stat)

Papers filed under stat.ML on arXiv, each one already summarized by Paperlayer. Open any of them to read the summary beside the original PDF, with every point linked to the line, figure, or table it came from.

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5,881 to 5,940 of 6,792

GPflow: A Gaussian process library using TensorFlow
Alexander G. de G. Matthews, Mark van der Wilk, Tom Nickson +5
stat.MLarXiv:1610.08733v12016
Tree of Attacks: Jailbreaking Black-Box LLMs Automatically
Anay Mehrotra, Manolis Zampetakis, Paul Kassianik +4
cs.LGcs.AIcs.CLarXiv:2312.02119v32023
Can You Really Backdoor Federated Learning?
Ziteng Sun, Peter Kairouz, Ananda Theertha Suresh +1
cs.LGcs.CRstat.MLarXiv:1911.07963v22019
Mish: A Self Regularized Non-Monotonic Activation Function
Diganta Misra
cs.LGcs.CVcs.NEarXiv:1908.08681v32019
A Tour of Reinforcement Learning: The View from Continuous Control
Benjamin Recht
math.OCcs.LGstat.MLarXiv:1806.09460v22018
Towards Fast Computation of Certified Robustness for ReLU Networks
Tsui-Wei Weng, Huan Zhang, Hongge Chen +5
stat.MLcs.CRcs.CVarXiv:1804.09699v42018
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Yanbin Liu, Juho Lee, Minseop Park +4
cs.LGcs.CVcs.NEarXiv:1805.10002v52018
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML
Aniruddh Raghu, Maithra Raghu, Samy Bengio +1
cs.LGstat.MLarXiv:1909.09157v22019
Less is more: sampling chemical space with active learning
Justin S. Smith, Ben Nebgen, Nicholas Lubbers +2
physics.comp-phcs.LGphysics.chem-pharXiv:1801.09319v22018
Joint Causal Structure and Cluster Discovery Using Variational Inference
Avni Rajpal, Anubhav Kumar, Rishabh Karnad +2
cs.LGcs.AIstat.MLarXiv:2608.22212v12026
Deep Learning COVID-19 Features on CXR using Limited Training Data Sets
Yujin Oh, Sangjoon Park, Jong Chul Ye
eess.IVcs.CVcs.LGarXiv:2004.05758v22020
Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech
Vadim Popov, Ivan Vovk, Vladimir Gogoryan +2
cs.LGcs.CLstat.MLarXiv:2105.06337v22021
RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment
Hanze Dong, Wei Xiong, Deepanshu Goyal +7
cs.LGcs.AIcs.CLarXiv:2304.06767v42023
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
Han Xu, Yao Ma, Haochen Liu +4
cs.LGcs.CRstat.MLarXiv:1909.08072v22019
Fairness in Machine Learning: A Survey
Simon Caton, Christian Haas
cs.LGstat.MLarXiv:2010.04053v12020
Assessing and tuning brain decoders: cross-validation, caveats, and guidelines
Gaël Varoquaux, Pradeep Reddy Raamana, Denis Engemann +3
stat.MLarXiv:1606.05201v22016
On the (Statistical) Detection of Adversarial Examples
Kathrin Grosse, Praveen Manoharan, Nicolas Papernot +2
cs.CRcs.LGstat.MLarXiv:1702.06280v22017
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling
Valentin De Bortoli, James Thornton, Jeremy Heng +1
stat.MLcs.LGmath.PRarXiv:2106.01357v52021
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients
Enmao Diao, Jie Ding, Vahid Tarokh
cs.LGstat.MLarXiv:2010.01264v32020
An Attentive Survey of Attention Models
Sneha Chaudhari, Varun Mithal, Gungor Polatkan +1
cs.LGstat.MLarXiv:1904.02874v32019
Emergent Tool Use From Multi-Agent Autocurricula
Bowen Baker, Ingmar Kanitscheider, Todor Markov +4
cs.LGcs.AIcs.MAarXiv:1909.07528v22019
Revisiting Small Batch Training for Deep Neural Networks
Dominic Masters, Carlo Luschi
cs.LGcs.CVstat.MLarXiv:1804.07612v12018
Interpretable AI with Local Distillation
Erin Craig, Yiling Huang, Snigdha Panigrahi
stat.MEcs.LGstat.MLarXiv:2608.23538v12026
Stochastic Gradient Descent as Approximate Bayesian Inference
Stephan Mandt, Matthew D. Hoffman, David M. Blei
stat.MLcs.LGarXiv:1704.04289v22017
Rigging the Lottery: Making All Tickets Winners
Utku Evci, Trevor Gale, Jacob Menick +2
cs.LGcs.CVstat.MLarXiv:1911.11134v32019
Three dimensional Deep Learning approach for remote sensing image classification
Amina Ben Hamida, A Benoit, Patrick Lambert +1
cs.CVcs.LGstat.MLarXiv:1806.05824v12018
SenTSR-Bench: Thinking with Injected Knowledge for Time-Series Reasoning
Zelin He, Boran Han, Xiyuan Zhang +10
cs.LGcs.AIcs.CLarXiv:2602.19455v12026
Expert Gate: Lifelong Learning with a Network of Experts
Rahaf Aljundi, Punarjay Chakravarty, Tinne Tuytelaars
cs.CVcs.AIstat.MLarXiv:1611.06194v22016
Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey
Sanmit Narvekar, Bei Peng, Matteo Leonetti +3
cs.LGcs.AIstat.MLarXiv:2003.04960v22020
Meta Pseudo Labels
Hieu Pham, Zihang Dai, Qizhe Xie +2
cs.LGstat.MLarXiv:2003.10580v42020
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
Zhisheng Xiao, Karsten Kreis, Arash Vahdat
cs.LGstat.MLarXiv:2112.07804v22021
Assessing Generative Models via Precision and Recall
Mehdi S. M. Sajjadi, Olivier Bachem, Mario Lucic +2
stat.MLcs.LGarXiv:1806.00035v22018
Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks
Jost Tobias Springenberg
stat.MLcs.LGarXiv:1511.06390v22015
Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data
Eunjeong Jeong, Seungeun Oh, Hyesung Kim +3
cs.LGcs.NIstat.MLarXiv:1811.11479v22018
Grid Search, Random Search, Genetic Algorithm: A Big Comparison for NAS
Petro Liashchynskyi, Pavlo Liashchynskyi
cs.LGcs.NEstat.MLarXiv:1912.06059v12019
Crop Yield Prediction Using Deep Neural Networks
Saeed Khaki, Lizhi Wang
cs.LGstat.APstat.MLarXiv:1902.02860v32019
Picking Winning Tickets Before Training by Preserving Gradient Flow
Chaoqi Wang, Guodong Zhang, Roger Grosse
cs.LGcs.CVstat.MLarXiv:2002.07376v22020
Large-Scale Study of Curiosity-Driven Learning
Yuri Burda, Harri Edwards, Deepak Pathak +3
cs.LGcs.AIcs.CVarXiv:1808.04355v12018
GRAM: Graph-based Attention Model for Healthcare Representation Learning
Edward Choi, Mohammad Taha Bahadori, Le Song +2
cs.LGstat.MLarXiv:1611.07012v32016
A Proximal Stochastic Gradient Method with Progressive Variance Reduction
Lin Xiao, Tong Zhang
math.OCstat.MLarXiv:1403.4699v12014
A Theoretical Analysis of Deep Q-Learning
Jianqing Fan, Zhaoran Wang, Yuchen Xie +1
cs.LGmath.OCstat.MLarXiv:1901.00137v32019
Federated learning with hierarchical clustering of local updates to improve training on non-IID data
Christopher Briggs, Zhong Fan, Peter Andras
cs.LGstat.MLarXiv:2004.11791v22020
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking
Aleksandar Bojchevski, Stephan Günnemann
stat.MLcs.LGcs.SIarXiv:1707.03815v42017
Variational Flow Maps: Make Some Noise for One-Step Conditional Generation
Abbas Mammadov, So Takao, Bohan Chen +4
cs.CVcs.LGstat.MLarXiv:2603.07276v12026
Deep Ensembles: A Loss Landscape Perspective
Stanislav Fort, Huiyi Hu, Balaji Lakshminarayanan
stat.MLcs.LGarXiv:1912.02757v22019
Low Data Drug Discovery with One-shot Learning
Han Altae-Tran, Bharath Ramsundar, Aneesh S. Pappu +1
cs.LGstat.MLarXiv:1611.03199v12016
ConvergeFlow: Language Flow with Provable Convergence to Token Embeddings
Na Li, Yuchen Jiao, Changxiao Cai +1
cs.CLcs.AIcs.LGarXiv:2608.23551v12026
Quantifying Generalization in Reinforcement Learning
Karl Cobbe, Oleg Klimov, Chris Hesse +2
cs.LGstat.MLarXiv:1812.02341v32018
Harmonic Networks: Deep Translation and Rotation Equivariance
Daniel E. Worrall, Stephan J. Garbin, Daniyar Turmukhambetov +1
cs.CVcs.LGstat.MLarXiv:1612.04642v22016
A General and Adaptive Robust Loss Function
Jonathan T. Barron
cs.CVcs.LGstat.MLarXiv:1701.03077v102017
Generalized Discrete Diffusion from Snapshots
Oussama Zekri, Théo Uscidda, Nicolas Boullé +1
stat.MLcs.AIcs.CLarXiv:2603.21342v12026
Solving Inverse Problems in Medical Imaging with Score-Based Generative Models
Yang Song, Liyue Shen, Lei Xing +1
eess.IVcs.CVcs.LGarXiv:2111.08005v22021
BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning
Andreas Kirsch, Joost van Amersfoort, Yarin Gal
cs.LGstat.MLarXiv:1906.08158v22019
Efficient Content-Based Sparse Attention with Routing Transformers
Aurko Roy, Mohammad Saffar, Ashish Vaswani +1
cs.LGeess.ASstat.MLarXiv:2003.05997v52020
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems
Jared Willard, Xiaowei Jia, Shaoming Xu +2
physics.comp-phcs.LGstat.MLarXiv:2003.04919v62020
Neural Controlled Differential Equations for Irregular Time Series
Patrick Kidger, James Morrill, James Foster +1
cs.LGstat.MLarXiv:2005.08926v22020
Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks
Zhi-Qin John Xu, Yaoyu Zhang, Tao Luo +2
cs.LGstat.MLarXiv:1901.06523v72019
Traceable Spectral Inference via Influence Functions: Efficient Data Attribution and Error Proxies for the Ariel Mission
Nikki Grens, Luís F. Simões, Kai Hou Yip +1
cs.LGastro-ph.IMstat.MLarXiv:2608.23458v12026
Augmented Neural ODEs
Emilien Dupont, Arnaud Doucet, Yee Whye Teh
stat.MLcs.LGarXiv:1904.01681v32019
SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities
Zhen Li, Deqing Zou, Shouhuai Xu +3
cs.LGcs.AIcs.CRarXiv:1807.06756v32018

Machine Learning (stat)

GPflow: A Gaussian process library using TensorFlow

Tree of Attacks: Jailbreaking Black-Box LLMs Automatically

Can You Really Backdoor Federated Learning?

Mish: A Self Regularized Non-Monotonic Activation Function

A Tour of Reinforcement Learning: The View from Continuous Control

Towards Fast Computation of Certified Robustness for ReLU Networks

Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning

Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML

Less is more: sampling chemical space with active learning

Joint Causal Structure and Cluster Discovery Using Variational Inference

Deep Learning COVID-19 Features on CXR using Limited Training Data Sets

Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech

RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment

Adversarial Attacks and Defenses in Images, Graphs and Text: A Review

Fairness in Machine Learning: A Survey

Assessing and tuning brain decoders: cross-validation, caveats, and guidelines

On the (Statistical) Detection of Adversarial Examples

Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling

HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients

An Attentive Survey of Attention Models

Emergent Tool Use From Multi-Agent Autocurricula

Revisiting Small Batch Training for Deep Neural Networks

Interpretable AI with Local Distillation

Stochastic Gradient Descent as Approximate Bayesian Inference

Rigging the Lottery: Making All Tickets Winners

Three dimensional Deep Learning approach for remote sensing image classification

SenTSR-Bench: Thinking with Injected Knowledge for Time-Series Reasoning

Expert Gate: Lifelong Learning with a Network of Experts

Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey

Meta Pseudo Labels

Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Assessing Generative Models via Precision and Recall

Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks

Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data

Grid Search, Random Search, Genetic Algorithm: A Big Comparison for NAS

Crop Yield Prediction Using Deep Neural Networks

Picking Winning Tickets Before Training by Preserving Gradient Flow

Large-Scale Study of Curiosity-Driven Learning

GRAM: Graph-based Attention Model for Healthcare Representation Learning

A Proximal Stochastic Gradient Method with Progressive Variance Reduction

A Theoretical Analysis of Deep Q-Learning

Federated learning with hierarchical clustering of local updates to improve training on non-IID data

Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking

Variational Flow Maps: Make Some Noise for One-Step Conditional Generation

Deep Ensembles: A Loss Landscape Perspective

Low Data Drug Discovery with One-shot Learning

ConvergeFlow: Language Flow with Provable Convergence to Token Embeddings

Quantifying Generalization in Reinforcement Learning

Harmonic Networks: Deep Translation and Rotation Equivariance

A General and Adaptive Robust Loss Function

Generalized Discrete Diffusion from Snapshots

Solving Inverse Problems in Medical Imaging with Score-Based Generative Models

BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning

Efficient Content-Based Sparse Attention with Routing Transformers

Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems

Neural Controlled Differential Equations for Irregular Time Series

Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks

Traceable Spectral Inference via Influence Functions: Efficient Data Attribution and Error Proxies for the Ariel Mission

Augmented Neural ODEs

SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities