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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8,881 to 8,940 of 9,674

Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
cs.CLcs.LGstat.MLarXiv:2305.19187v32023
A Unified Framework for Structured Graph Learning via Spectral Constraints
Sandeep Kumar, Jiaxi Ying, José Vinícius de M. Cardoso +1
stat.MLcs.LGcs.SIarXiv:1904.09792v12019
Chemical and geometric representation fidelity improves drug--target affinity prediction
Yixiao Li, Yining Qian, Yefan Chen +5
q-bio.BMcs.AIcs.LGarXiv:2609.13230v12026
Neural reparameterization improves structural optimization
Stephan Hoyer, Jascha Sohl-Dickstein, Sam Greydanus
cs.LGcs.NEstat.MLarXiv:1909.04240v22019
Self-Supervised Pretraining of Molecular Graph Encoders with LeJEPA
Michał Kulczykowski, Rafał Łabędzki
q-bio.QMcs.LGstat.MLarXiv:2609.04261v12026
Evaluating Graph Neural Networks for Change-Criticality Classification in Maritime Navigation Charts
Abhishek Potnis, Jacob Arndt
cs.LGcs.AIstat.MLarXiv:2609.02996v12026
When Explainability Meets Adversarial Learning: Detecting Adversarial Examples using SHAP Signatures
Gil Fidel, Ron Bitton, Asaf Shabtai
cs.LGcs.AIcs.CRarXiv:1909.03418v12019
Imperceptible Adversarial Attacks on Tabular Data
Vincent Ballet, Xavier Renard, Jonathan Aigrain +3
stat.MLcs.CRcs.LGarXiv:1911.03274v22019
How I failed machine learning in medical imaging -- shortcomings and recommendations
Gaël Varoquaux, Veronika Cheplygina
eess.IVcs.CVcs.LGarXiv:2103.10292v22021
Deep Reinforcement Learning for General Video Game AI
Ruben Rodriguez Torrado, Philip Bontrager, Julian Togelius +2
cs.LGcs.AIcs.NEarXiv:1806.02448v12018
Are All Training Examples Created Equal? An Empirical Study
Kailas Vodrahalli, Ke Li, Jitendra Malik
cs.LGcs.CVstat.MLarXiv:1811.12569v12018
LakhNES: Improving multi-instrumental music generation with cross-domain pre-training
Chris Donahue, Huanru Henry Mao, Yiting Ethan Li +2
cs.SDcs.LGcs.MMarXiv:1907.04868v12019
EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces
Vernon J. Lawhern, Amelia J. Solon, Nicholas R. Waytowich +3
cs.LGq-bio.NCstat.MLarXiv:1611.08024v42016
Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL
Nils Strodthoff, Patrick Wagner, Tobias Schaeffter +1
cs.LGstat.MLarXiv:2004.13701v12020
End-to-End Model-Free Reinforcement Learning for Urban Driving using Implicit Affordances
Marin Toromanoff, Emilie Wirbel, Fabien Moutarde
cs.LGcs.AIcs.CVarXiv:1911.10868v22019
Decentralized Federated Learning: A Survey on Security and Privacy
Ehsan Hallaji, Roozbeh Razavi-Far, Mehrdad Saif +2
cs.CRcs.AIcs.LGarXiv:2401.17319v12024
Learning Sensor Multiplexing Design through Back-propagation
Ayan Chakrabarti
cs.LGstat.MLarXiv:1605.07078v22016
On the Effectiveness of Low Frequency Perturbations
Yash Sharma, Gavin Weiguang Ding, Marcus Brubaker
cs.CVcs.CRcs.LGarXiv:1903.00073v22019
Neural system identification for large populations separating "what" and "where"
David A. Klindt, Alexander S. Ecker, Thomas Euler +1
stat.MLcs.LGq-bio.NCarXiv:1711.02653v22017
Sliced Wasserstein Distance for Learning Gaussian Mixture Models
Soheil Kolouri, Gustavo K. Rohde, Heiko Hoffmann
cs.CVcs.LGstat.MLarXiv:1711.05376v22017
Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers
Junjie Liu, Zhe Xu, Runbin Shi +2
cs.LGstat.MLarXiv:2005.06870v12020
Multi-Agent Fully Decentralized Value Function Learning with Linear Convergence Rates
Lucas Cassano, Kun Yuan, Ali H. Sayed
cs.LGcs.DCstat.MLarXiv:1810.07792v52018
High-quality nonparallel voice conversion based on cycle-consistent adversarial network
Fuming Fang, Junichi Yamagishi, Isao Echizen +1
eess.AScs.CLcs.SDarXiv:1804.00425v12018
Hopfield Networks is All You Need
Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner +13
cs.NEcs.CLcs.LGarXiv:2008.02217v32020
Reward learning from human preferences and demonstrations in Atari
Borja Ibarz, Jan Leike, Tobias Pohlen +3
cs.LGcs.AIcs.NEarXiv:1811.06521v12018
A Brief Survey of Deep Reinforcement Learning
Kai Arulkumaran, Marc Peter Deisenroth, Miles Brundage +1
cs.LGcs.AIcs.CVarXiv:1708.05866v22017
Generalization through Simulation: Integrating Simulated and Real Data into Deep Reinforcement Learning for Vision-Based Autonomous Flight
Katie Kang, Suneel Belkhale, Gregory Kahn +2
cs.LGcs.ROstat.MLarXiv:1902.03701v12019
Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification
Jiong Zhang, Wei-cheng Chang, Hsiang-fu Yu +1
cs.LGcs.AIcs.IRarXiv:2110.00685v22021
Planning to Explore via Self-Supervised World Models
Ramanan Sekar, Oleh Rybkin, Kostas Daniilidis +3
cs.LGcs.AIcs.CVarXiv:2005.05960v22020
The State of Sparsity in Deep Neural Networks
Trevor Gale, Erich Elsen, Sara Hooker
cs.LGstat.MLarXiv:1902.09574v12019
Learning a Code: Machine Learning for Approximate Non-Linear Coded Computation
Jack Kosaian, K. V. Rashmi, Shivaram Venkataraman
cs.LGcs.ITmath.ITarXiv:1806.01259v12018
Mask-Predict: Parallel Decoding of Conditional Masked Language Models
Marjan Ghazvininejad, Omer Levy, Yinhan Liu +1
cs.CLcs.AIcs.LGarXiv:1904.09324v22019
Infrastructure for Usable Machine Learning: The Stanford DAWN Project
Peter Bailis, Kunle Olukotun, Christopher Re +1
cs.LGcs.DBstat.MLarXiv:1705.07538v22017
Neural Algorithmic Reasoning
Petar Veličković, Charles Blundell
cs.LGcs.AIcs.DSarXiv:2105.02761v12021
Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysis
Benjamin Shickel, Patrick Tighe, Azra Bihorac +1
cs.LGstat.MLarXiv:1706.03446v22017
Session-based Recommendation with Graph Neural Networks
Shu Wu, Yuyuan Tang, Yanqiao Zhu +3
cs.IRcs.LGstat.MLarXiv:1811.00855v42018
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets
Dongxian Wu, Yisen Wang, Shu-Tao Xia +2
cs.LGcs.CRcs.CVarXiv:2002.05990v12020
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches
Yeming Wen, Paul Vicol, Jimmy Ba +2
cs.LGstat.MLarXiv:1803.04386v22018
One-Layer Transformer Provably Learns Multiclass One-Nearest Neighbor in Context
Skanda Athreya, Yutong Wang
cs.LGstat.MLarXiv:2609.01311v12026
Adversarial Reprogramming of Neural Networks
Gamaleldin F. Elsayed, Ian Goodfellow, Jascha Sohl-Dickstein
cs.LGcs.CRcs.CVarXiv:1806.11146v22018
Unsupervised Learning by Predicting Noise
Piotr Bojanowski, Armand Joulin
stat.MLcs.CVcs.LGarXiv:1704.05310v12017
Automated Vulnerability Detection in Source Code Using Deep Representation Learning
Rebecca L. Russell, Louis Kim, Lei H. Hamilton +5
cs.LGcs.AIcs.SEarXiv:1807.04320v22018
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner +2
cs.LGstat.MLarXiv:1706.08500v62017
MLI: An API for Distributed Machine Learning
Evan R. Sparks, Ameet Talwalkar, Virginia Smith +6
cs.LGcs.DCstat.MLarXiv:1310.5426v22013
Holographic Embeddings of Knowledge Graphs
Maximilian Nickel, Lorenzo Rosasco, Tomaso Poggio
cs.AIcs.LGstat.MLarXiv:1510.04935v22015
A Review of Challenges and Opportunities in Machine Learning for Health
Marzyeh Ghassemi, Tristan Naumann, Peter Schulam +3
cs.LGcs.CYstat.MLarXiv:1806.00388v42018
CitySim: A Drone-Based Vehicle Trajectory Dataset for Safety Oriented Research and Digital Twins
Ou Zheng, Mohamed Abdel-Aty, Lishengsa Yue +3
cs.CVstat.MLarXiv:2208.11036v22022
MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare
Edward Choi, Cao Xiao, Walter F. Stewart +1
cs.LGcs.CLstat.MLarXiv:1810.09593v12018
A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning
Iris A. M. Huijben, Wouter Kool, Max B. Paulus +1
cs.LGstat.MLarXiv:2110.01515v22021
The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems
Robert Krajewski, Julian Bock, Laurent Kloeker +1
cs.CVcs.AIcs.IRarXiv:1810.05642v12018
Better Fine-Tuning by Reducing Representational Collapse
Armen Aghajanyan, Akshat Shrivastava, Anchit Gupta +3
cs.LGcs.CLstat.MLarXiv:2008.03156v12020
Gradient Coding from Cyclic MDS Codes and Expander Graphs
Netanel Raviv, Itzhak Tamo, Rashish Tandon +1
cs.ITstat.MLarXiv:1707.03858v32017
Unsupervised Single Image Dehazing Using Dark Channel Prior Loss
Alona Golts, Daniel Freedman, Michael Elad
cs.CVcs.LGstat.MLarXiv:1812.07051v22018
Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems
Sébastien Bubeck, Nicolò Cesa-Bianchi
cs.LGstat.MLarXiv:1204.5721v22012
DTD-VAE: Disentangled Temporal Dependencies VAE for Credit Risk Prediction
Xiaobo Guo, Lu-an Dong, Yanbo Wang +3
q-fin.RMstat.MLarXiv:2608.26473v12026
Incremental Recommendation via Causal Models
Athanasios Vlontzos, David Gustafsson, Michael O'Riordan +1
stat.MLcs.LGstat.MEarXiv:2608.26804v12026
AgensFlow: A Coordination-Policy Substrate for Multi-Agent Systems
Nicole Koenigstein
cs.MAcs.AIcs.LGarXiv:2605.27466v12026
Layer by layer, module by module: Choose both for optimal OOD probing of ViT
Ambroise Odonnat, Vasilii Feofanov, Laetitia Chapel +2
cs.CVcs.LGstat.MLarXiv:2603.05280v12026
Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion
Dongjun Kim, Chieh-Hsin Lai, Wei-Hsiang Liao +6
cs.LGcs.AIcs.CVarXiv:2310.02279v32023
Let Your Graph Do the Talking: Encoding Structured Data for LLMs
Bryan Perozzi, Bahare Fatemi, Dustin Zelle +4
cs.LGcs.AIcs.SIarXiv:2402.05862v12024

Machine Learning (stat)

Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models

A Unified Framework for Structured Graph Learning via Spectral Constraints

Chemical and geometric representation fidelity improves drug--target affinity prediction

Neural reparameterization improves structural optimization

Self-Supervised Pretraining of Molecular Graph Encoders with LeJEPA

Evaluating Graph Neural Networks for Change-Criticality Classification in Maritime Navigation Charts

When Explainability Meets Adversarial Learning: Detecting Adversarial Examples using SHAP Signatures

Imperceptible Adversarial Attacks on Tabular Data

How I failed machine learning in medical imaging -- shortcomings and recommendations

Deep Reinforcement Learning for General Video Game AI

Are All Training Examples Created Equal? An Empirical Study

LakhNES: Improving multi-instrumental music generation with cross-domain pre-training

EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces

Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL

End-to-End Model-Free Reinforcement Learning for Urban Driving using Implicit Affordances

Decentralized Federated Learning: A Survey on Security and Privacy

Learning Sensor Multiplexing Design through Back-propagation

On the Effectiveness of Low Frequency Perturbations

Neural system identification for large populations separating "what" and "where"

Sliced Wasserstein Distance for Learning Gaussian Mixture Models

Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers

Multi-Agent Fully Decentralized Value Function Learning with Linear Convergence Rates

High-quality nonparallel voice conversion based on cycle-consistent adversarial network

Hopfield Networks is All You Need

Reward learning from human preferences and demonstrations in Atari

A Brief Survey of Deep Reinforcement Learning

Generalization through Simulation: Integrating Simulated and Real Data into Deep Reinforcement Learning for Vision-Based Autonomous Flight

Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification

Planning to Explore via Self-Supervised World Models

The State of Sparsity in Deep Neural Networks

Learning a Code: Machine Learning for Approximate Non-Linear Coded Computation

Mask-Predict: Parallel Decoding of Conditional Masked Language Models

Infrastructure for Usable Machine Learning: The Stanford DAWN Project

Neural Algorithmic Reasoning

Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysis

Session-based Recommendation with Graph Neural Networks

Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets

Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches

One-Layer Transformer Provably Learns Multiclass One-Nearest Neighbor in Context

Adversarial Reprogramming of Neural Networks

Unsupervised Learning by Predicting Noise

Automated Vulnerability Detection in Source Code Using Deep Representation Learning

GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium

MLI: An API for Distributed Machine Learning

Holographic Embeddings of Knowledge Graphs

A Review of Challenges and Opportunities in Machine Learning for Health

CitySim: A Drone-Based Vehicle Trajectory Dataset for Safety Oriented Research and Digital Twins

MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare

A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning

The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems

Better Fine-Tuning by Reducing Representational Collapse

Gradient Coding from Cyclic MDS Codes and Expander Graphs

Unsupervised Single Image Dehazing Using Dark Channel Prior Loss

Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems

DTD-VAE: Disentangled Temporal Dependencies VAE for Credit Risk Prediction

Incremental Recommendation via Causal Models

AgensFlow: A Coordination-Policy Substrate for Multi-Agent Systems

Layer by layer, module by module: Choose both for optimal OOD probing of ViT

Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion

Let Your Graph Do the Talking: Encoding Structured Data for LLMs