Machine Learning

Papers filed under cs.LG 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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16,261 to 16,320 of 20,193

GPT-GNN: Generative Pre-Training of Graph Neural Networks
Ziniu Hu, Yuxiao Dong, Kuansan Wang +2
cs.LGcs.SIstat.MLarXiv:2006.15437v12020
Graph Matching Networks for Learning the Similarity of Graph Structured Objects
Yujia Li, Chenjie Gu, Thomas Dullien +2
cs.LGstat.MLarXiv:1904.12787v22019
Value Iteration Networks
Aviv Tamar, Yi Wu, Garrett Thomas +2
cs.AIcs.LGcs.NEarXiv:1602.02867v42016
Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations
Maziar Raissi, Paris Perdikaris, George Em Karniadakis
cs.AIcs.LGmath.AParXiv:1711.10566v12017
Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset
Ke Wang, Junting Pan, Weikang Shi +3
cs.CVcs.AIcs.CLarXiv:2402.14804v12024
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use
Sana Tonekaboni, Shalmali Joshi, Melissa D McCradden +1
cs.LGstat.MLarXiv:1905.05134v22019
ReLMXEL: Adaptive RL-Based Memory Controller with Explainable Energy and Latency Optimization
Panuganti Chirag Sai, Gandholi Sarat, R. Raghunatha Sarma +2
cs.ARcs.AIcs.LGarXiv:2603.17309v12026
Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution
Aaron Lou, Chenlin Meng, Stefano Ermon
stat.MLcs.CLcs.LGarXiv:2310.16834v32023
Discovering Symbolic Models from Deep Learning with Inductive Biases
Miles Cranmer, Alvaro Sanchez-Gonzalez, Peter Battaglia +4
cs.LGastro-ph.COastro-ph.IMarXiv:2006.11287v22020
PRISM: Demystifying Retention and Interaction in Mid-Training
Bharat Runwal, Ashish Agrawal, Anurag Roy +1
cs.LGarXiv:2603.17074v32026
Hungry Hungry Hippos: Towards Language Modeling with State Space Models
Daniel Y. Fu, Tri Dao, Khaled K. Saab +3
cs.LGcs.CLarXiv:2212.14052v32022
DAW: Dynamics-Aware Weighting for Deep Learning Forecasts of Chaotic Systems
Zhou Fang, Gianmarco Mengaldo
cs.LGphysics.comp-pharXiv:2608.22277v12026
BLADE: Bilevel Low-rank Augmented-Lagrangian Erasure for LLM Unlearning
Md Toufikuzzaman, Ahmad Mousavi, Dongwon Lee
cs.LGcs.AIcs.CLarXiv:2608.22557v12026
Graph Representation Learning via Graphical Mutual Information Maximization
Zhen Peng, Wenbing Huang, Minnan Luo +4
cs.LGcs.AIstat.MLarXiv:2002.01169v12020
Efficient Exploration at Scale
Seyed Mohammad Asghari, Chris Chute, Vikranth Dwaracherla +5
cs.LGcs.AIarXiv:2603.17378v22026
A Survey on Causal Inference
Liuyi Yao, Zhixuan Chu, Sheng Li +3
stat.MEcs.AIcs.LGarXiv:2002.02770v12020
Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models
Yixin Liu, Kai Zhang, Yuan Li +9
cs.CVcs.AIcs.LGarXiv:2402.17177v32024
Machine Learning in IoT Security: Current Solutions and Future Challenges
Fatima Hussain, Rasheed Hussain, Syed Ali Hassan +1
cs.CRcs.LGstat.MLarXiv:1904.05735v12019
ReMAP: Self-supervised learning to unveil brain representations and vulnerability
Jade Perdereau, Virginie Loison, Kanssa El Ayeb +5
cs.LGarXiv:2608.22042v12026
BEHRT: Transformer for Electronic Health Records
Yikuan Li, Shishir Rao, Jose Roberto Ayala Solares +5
cs.LGstat.MLarXiv:1907.09538v12019
Relational Graph Attention Network for Aspect-based Sentiment Analysis
Kai Wang, Weizhou Shen, Yunyi Yang +2
cs.CLcs.LGarXiv:2004.12362v12020
Do VLMs Need Vision Transformers? Evaluating State Space Models as Vision Encoders
Shang-Jui Ray Kuo, Paola Cascante-Bonilla
cs.CVcs.LGarXiv:2603.19209v12026
Scalable Prompt Routing via Fine-Grained Latent Task Discovery
Yunyi Zhang, Soji Adeshina, Sheng Guan +5
cs.CLcs.AIcs.LGarXiv:2603.19415v22026
Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data
Yen-Chang Hsu, Yilin Shen, Hongxia Jin +1
cs.CVcs.LGeess.IVarXiv:2002.11297v22020
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
AI Generalisation Gap In Comorbid Sleep Disorder Staging
Saswata Bose, Suvadeep Maiti, Shivam Kumar Sharma +4
cs.LGcs.AIarXiv:2603.23582v22026
VISion On Request: Enhanced VLLM efficiency with sparse, dynamically selected, vision-language interactions
Adrian Bulat, Alberto Baldrati, Ioannis Maniadis Metaxas +2
cs.CVcs.AIcs.LGarXiv:2603.23495v12026
Scaling up GANs for Text-to-Image Synthesis
Minguk Kang, Jun-Yan Zhu, Richard Zhang +4
cs.CVcs.GRcs.LGarXiv:2303.05511v22023
Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation
Michael Yeung, Evis Sala, Carola-Bibiane Schönlieb +1
eess.IVcs.CVcs.LGarXiv:2102.04525v42021
Scaling Out-of-Distribution Detection for Real-World Settings
Dan Hendrycks, Steven Basart, Mantas Mazeika +5
cs.CVcs.LGarXiv:1911.11132v42019
Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders
Edgar Schönfeld, Sayna Ebrahimi, Samarth Sinha +2
cs.CVcs.AIcs.LGarXiv:1812.01784v42018
Extending Precipitation Nowcasting Horizons via Spectral Fusion of Radar Observations and Foundation Model Priors
Yuze Qin, Qingyong Li, Zhiqing Guo +3
cs.LGcs.AIarXiv:2603.21768v32026
GraphGAN: Graph Representation Learning with Generative Adversarial Nets
Hongwei Wang, Jia Wang, Jialin Wang +5
cs.LGstat.MLarXiv:1711.08267v12017
Revisiting Batch Normalization For Practical Domain Adaptation
Yanghao Li, Naiyan Wang, Jianping Shi +2
cs.CVcs.LGarXiv:1603.04779v42016
Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning
Zhendong Wang, Jonathan J Hunt, Mingyuan Zhou
cs.LGstat.MLarXiv:2208.06193v32022
Preference Optimization for Non-Verbal Vocalization Synthesis
Haoyang Li, Chenglin Xu, Junchuan Zhao +4
eess.AScs.AIcs.LGarXiv:2608.24163v12026
Structural Deep Clustering Network
Deyu Bo, Xiao Wang, Chuan Shi +3
cs.LGstat.MLarXiv:2002.01633v32020
Professor Forcing: A New Algorithm for Training Recurrent Networks
Alex Lamb, Anirudh Goyal, Ying Zhang +3
stat.MLcs.LGarXiv:1610.09038v12016
Machine Learning DDoS Detection for Consumer Internet of Things Devices
Rohan Doshi, Noah Apthorpe, Nick Feamster
cs.CRcs.LGarXiv:1804.04159v12018
Scaling DoRA: High-Rank Adaptation via Factored Norms and Fused Kernels
Alexandra Zelenin, Alexandra Zhuravlyova
cs.LGstat.MLarXiv:2603.22276v12026
Understanding over-squashing and bottlenecks on graphs via curvature
Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain +2
stat.MLcs.LGarXiv:2111.14522v32021
Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks
Ruediger Ehlers
cs.LOcs.AIcs.LGarXiv:1705.01320v32017
Merging Models with Fisher-Weighted Averaging
Michael Matena, Colin Raffel
cs.LGarXiv:2111.09832v22021
Blockwise Stabilized Adaptive Cubic Regularization with Subsolvers via Recurrence
Rodion Podorozhny
cs.LGmath.NAarXiv:2608.22129v22026
Mobile-Former: Bridging MobileNet and Transformer
Yinpeng Chen, Xiyang Dai, Dongdong Chen +4
cs.CVcs.LGarXiv:2108.05895v32021
The role of explainability in creating trustworthy artificial intelligence for health care: a comprehensive survey of the terminology, design choices, and evaluation strategies
Aniek F. Markus, Jan A. Kors, Peter R. Rijnbeek
cs.AIcs.LGstat.MLarXiv:2007.15911v22020
Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations
Andrew Slavin Ross, Michael C. Hughes, Finale Doshi-Velez
cs.LGcs.AIstat.MLarXiv:1703.03717v22017
Explainable Prediction of Medical Codes from Clinical Text
James Mullenbach, Sarah Wiegreffe, Jon Duke +2
cs.CLcs.LGstat.MLarXiv:1802.05695v22018
Provably Efficient Reinforcement Learning with Linear Function Approximation
Chi Jin, Zhuoran Yang, Zhaoran Wang +1
cs.LGmath.OCstat.MLarXiv:1907.05388v22019
Deep Learning for Time Series Anomaly Detection: A Survey
Zahra Zamanzadeh Darban, Geoffrey I. Webb, Shirui Pan +2
cs.LGcs.AIarXiv:2211.05244v32022
RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
Harrison Lee, Samrat Phatale, Hassan Mansoor +8
cs.CLcs.AIcs.LGarXiv:2309.00267v32023
Deep learning with noisy labels: exploring techniques and remedies in medical image analysis
Davood Karimi, Haoran Dou, Simon K. Warfield +1
cs.CVcs.LGeess.IVarXiv:1912.02911v42019
DAG-GNN: DAG Structure Learning with Graph Neural Networks
Yue Yu, Jie Chen, Tian Gao +1
cs.LGcs.AIstat.MLarXiv:1904.10098v12019
Optimal Ratio for Data Splitting
V. Roshan Joseph
stat.MLcs.LGarXiv:2202.03326v12022
Online Continual Learning with Maximally Interfered Retrieval
Rahaf Aljundi, Lucas Caccia, Eugene Belilovsky +4
cs.LGstat.MLarXiv:1908.04742v32019
How is ChatGPT's behavior changing over time?
Lingjiao Chen, Matei Zaharia, James Zou
cs.CLcs.AIcs.LGarXiv:2307.09009v32023
"Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models
Xinyue Shen, Zeyuan Chen, Michael Backes +2
cs.CRcs.LGarXiv:2308.03825v22023
VirtualHome: Simulating Household Activities via Programs
Xavier Puig, Kevin Ra, Marko Boben +4
cs.CVcs.AIcs.LGarXiv:1806.07011v12018
Unified Training of Universal Time Series Forecasting Transformers
Gerald Woo, Chenghao Liu, Akshat Kumar +3
cs.LGcs.AIarXiv:2402.02592v22024
SuperSpike: Supervised learning in multi-layer spiking neural networks
Friedemann Zenke, Surya Ganguli
q-bio.NCcs.LGcs.NEarXiv:1705.11146v22017

Machine Learning

GPT-GNN: Generative Pre-Training of Graph Neural Networks

Graph Matching Networks for Learning the Similarity of Graph Structured Objects

Value Iteration Networks

Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations

Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset

What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use

ReLMXEL: Adaptive RL-Based Memory Controller with Explainable Energy and Latency Optimization

Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution

Discovering Symbolic Models from Deep Learning with Inductive Biases

PRISM: Demystifying Retention and Interaction in Mid-Training

Hungry Hungry Hippos: Towards Language Modeling with State Space Models

DAW: Dynamics-Aware Weighting for Deep Learning Forecasts of Chaotic Systems

BLADE: Bilevel Low-rank Augmented-Lagrangian Erasure for LLM Unlearning

Graph Representation Learning via Graphical Mutual Information Maximization

Efficient Exploration at Scale

A Survey on Causal Inference

Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models

Machine Learning in IoT Security: Current Solutions and Future Challenges

ReMAP: Self-supervised learning to unveil brain representations and vulnerability

BEHRT: Transformer for Electronic Health Records

Relational Graph Attention Network for Aspect-based Sentiment Analysis

Do VLMs Need Vision Transformers? Evaluating State Space Models as Vision Encoders

Scalable Prompt Routing via Fine-Grained Latent Task Discovery

Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data

Automated Vulnerability Detection in Source Code Using Deep Representation Learning

AI Generalisation Gap In Comorbid Sleep Disorder Staging

VISion On Request: Enhanced VLLM efficiency with sparse, dynamically selected, vision-language interactions

Scaling up GANs for Text-to-Image Synthesis

Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation

Scaling Out-of-Distribution Detection for Real-World Settings

Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders

Extending Precipitation Nowcasting Horizons via Spectral Fusion of Radar Observations and Foundation Model Priors

GraphGAN: Graph Representation Learning with Generative Adversarial Nets

Revisiting Batch Normalization For Practical Domain Adaptation

Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning

Preference Optimization for Non-Verbal Vocalization Synthesis

Structural Deep Clustering Network

Professor Forcing: A New Algorithm for Training Recurrent Networks

Machine Learning DDoS Detection for Consumer Internet of Things Devices

Scaling DoRA: High-Rank Adaptation via Factored Norms and Fused Kernels

Understanding over-squashing and bottlenecks on graphs via curvature

Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks

Merging Models with Fisher-Weighted Averaging

Blockwise Stabilized Adaptive Cubic Regularization with Subsolvers via Recurrence

Mobile-Former: Bridging MobileNet and Transformer

The role of explainability in creating trustworthy artificial intelligence for health care: a comprehensive survey of the terminology, design choices, and evaluation strategies

Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations

Explainable Prediction of Medical Codes from Clinical Text

Provably Efficient Reinforcement Learning with Linear Function Approximation

Deep Learning for Time Series Anomaly Detection: A Survey

RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

Deep learning with noisy labels: exploring techniques and remedies in medical image analysis

DAG-GNN: DAG Structure Learning with Graph Neural Networks

Optimal Ratio for Data Splitting

Online Continual Learning with Maximally Interfered Retrieval

How is ChatGPT's behavior changing over time?

"Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models

VirtualHome: Simulating Household Activities via Programs

Unified Training of Universal Time Series Forecasting Transformers

SuperSpike: Supervised learning in multi-layer spiking neural networks