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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14,161 to 14,220 of 20,454

Geometric Deep Learning on Molecular Representations
Kenneth Atz, Francesca Grisoni, Gisbert Schneider
physics.chem-phcs.AIcs.LGarXiv:2107.12375v42021
Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks
Tianfan Xue, Jiajun Wu, Katherine L. Bouman +1
cs.CVcs.LGarXiv:1607.02586v12016
What's Hidden in a Randomly Weighted Neural Network?
Vivek Ramanujan, Mitchell Wortsman, Aniruddha Kembhavi +2
cs.CVcs.LGarXiv:1911.13299v22019
TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting
Vijay Ekambaram, Arindam Jati, Nam Nguyen +2
cs.LGcs.AIarXiv:2306.09364v42023
NeMo: a toolkit for building AI applications using Neural Modules
Oleksii Kuchaiev, Jason Li, Huyen Nguyen +11
cs.LGcs.CLcs.SDarXiv:1909.09577v12019
Subgraph Filtering for Fair Graph Neural Networks
Haohui Lu, jiyuan Tian, Fangyu Zhou +1
cs.LGarXiv:2608.26437v12026
NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models
Zeqian Ju, Yuancheng Wang, Kai Shen +16
eess.AScs.AIcs.CLarXiv:2403.03100v32024
Geometry-Informed Neural Operator for Large-Scale 3D PDEs
Zongyi Li, Nikola Borislavov Kovachki, Chris Choy +8
cs.LGmath.NAarXiv:2309.00583v12023
A causal graph-informed temporal convolution architecture for interpretable retail electricity price forecasting
Yufan Ji, Abdollah Shafieezadeh, Noah Dormady
stat.APcs.LGarXiv:2608.26234v12026
ReZero is All You Need: Fast Convergence at Large Depth
Thomas Bachlechner, Bodhisattwa Prasad Majumder, Huanru Henry Mao +2
cs.LGcs.CLstat.MLarXiv:2003.04887v22020
Co-Evolving Structured Knowledge and Reasoning in Language Models
Ryan Thomas Noonan, Linxi Zhao, Menghan Xu +6
cs.CLcs.AIcs.LGarXiv:2608.26386v12026
Efficient Online Reinforcement Learning with Offline Data
Philip J. Ball, Laura Smith, Ilya Kostrikov +1
cs.LGcs.AIarXiv:2302.02948v42023
Recurrent Batch Normalization
Tim Cooijmans, Nicolas Ballas, César Laurent +2
cs.LGarXiv:1603.09025v52016
Insights into Performance Fitness and Error Metrics for Machine Learning
M. Z. Naser, Amir Alavi
cs.LGphysics.data-anstat.MLarXiv:2006.00887v12020
A Survey of Deep Learning Techniques for Weed Detection from Images
A S M Mahmudul Hasan, Ferdous Sohel, Dean Diepeveen +2
cs.CVcs.LGarXiv:2103.01415v12021
Training behavior of deep neural network in frequency domain
Zhi-Qin John Xu, Yaoyu Zhang, Yanyang Xiao
cs.LGcs.AIcs.ITarXiv:1807.01251v62018
Distributed Training using an Intelligent Network
Nihar Shah, Ben Blier
cs.LGcs.DCcs.NIarXiv:2608.26453v12026
Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations
Huan Zhang, Hongge Chen, Chaowei Xiao +4
cs.LGstat.MLarXiv:2003.08938v72020
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
Ekagra Ranjan, Soumya Sanyal, Partha Pratim Talukdar
cs.LGstat.MLarXiv:1911.07979v32019
HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization
Xingxing Zhang, Furu Wei, Ming Zhou
cs.CLcs.LGarXiv:1905.06566v12019
Privacy Preserving Machine Learning: Threats and Solutions
Mohammad Al-Rubaie, J. Morris Chang
cs.CRcs.LGarXiv:1804.11238v12018
Understanding and Robustifying Differentiable Architecture Search
Arber Zela, Thomas Elsken, Tonmoy Saikia +3
cs.LGcs.AIcs.CVarXiv:1909.09656v22019
Data Augmentation Can Improve Robustness
Sylvestre-Alvise Rebuffi, Sven Gowal, Dan A. Calian +3
cs.CVcs.LGstat.MLarXiv:2111.05328v12021
Learning Sampling Distributions for Robot Motion Planning
Brian Ichter, James Harrison, Marco Pavone
cs.ROcs.LGarXiv:1709.05448v32017
Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning
Matthias Feurer, Katharina Eggensperger, Stefan Falkner +2
cs.LGstat.MLarXiv:2007.04074v32020
Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translation
YuXuan Liu, Abhishek Gupta, Pieter Abbeel +1
cs.LGcs.AIcs.CVarXiv:1707.03374v22017
Visual Classification via Description from Large Language Models
Sachit Menon, Carl Vondrick
cs.CVcs.LGarXiv:2210.07183v22022
Local Differential Privacy based Federated Learning for Internet of Things
Yang Zhao, Jun Zhao, Mengmeng Yang +5
cs.CRcs.LGarXiv:2004.08856v22020
Predicting Station-level Hourly Demands in a Large-scale Bike-sharing Network: A Graph Convolutional Neural Network Approach
Lei Lin, Zhengbing He, Srinivas Peeta
stat.MLcs.LGarXiv:1712.04997v22017
Arrive and Survive: Scaling Safe Goal-Conditioned Policy Learning from One-Bit Failure Signals
Guopeng Li, Yiyang Duan, Yiru Jiao +1
cs.LGcs.ROarXiv:2608.26571v12026
Making Latent Evolution Explicit: Operator-Structured Transitions for World Action Models
Xiaoxiao Lu, Yunlong Dong, Jiahao Shi +1
cs.LGarXiv:2608.27259v12026
Spectral Norm Regularization for Improving the Generalizability of Deep Learning
Yuichi Yoshida, Takeru Miyato
stat.MLcs.LGarXiv:1705.10941v12017
Word Representations via Gaussian Embedding
Luke Vilnis, Andrew McCallum
cs.CLcs.LGarXiv:1412.6623v42014
Exponentially Weighted Moving Average Charts for Detecting Concept Drift
Gordon J. Ross, Niall M. Adams, Dimitris K. Tasoulis +1
stat.MLcs.LGstat.AParXiv:1212.6018v12012
Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning
Elias Frantar, Sidak Pal Singh, Dan Alistarh
cs.LGarXiv:2208.11580v22022
PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training
Kimin Lee, Laura Smith, Pieter Abbeel
cs.LGcs.AIarXiv:2106.05091v12021
Experience-driven Networking: A Deep Reinforcement Learning based Approach
Zhiyuan Xu, Jian Tang, Jingsong Meng +4
cs.NIcs.AIcs.LGarXiv:1801.05757v12018
Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data
Maximilian Karl, Maximilian Soelch, Justin Bayer +1
stat.MLcs.LGeess.SYarXiv:1605.06432v32016
A Survey of Deep Meta-Learning
Mike Huisman, Jan N. van Rijn, Aske Plaat
cs.LGcs.AIstat.MLarXiv:2010.03522v22020
RMP-SNN: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Network
Bing Han, Gopalakrishnan Srinivasan, Kaushik Roy
cs.NEcs.CVcs.LGarXiv:2003.01811v22020
Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble
Gaon An, Seungyong Moon, Jang-Hyun Kim +1
cs.LGcs.AIarXiv:2110.01548v22021
Hyperbolic Image Embeddings
Valentin Khrulkov, Leyla Mirvakhabova, Evgeniya Ustinova +2
cs.CVcs.LGarXiv:1904.02239v22019
High Dimensional Bayesian Optimisation and Bandits via Additive Models
Kirthevasan Kandasamy, Jeff Schneider, Barnabas Poczos
stat.MLcs.LGarXiv:1503.01673v32015
Learnable latent embeddings for joint behavioral and neural analysis
Steffen Schneider, Jin Hwa Lee, Mackenzie Weygandt Mathis
cs.LGq-bio.NCq-bio.QMarXiv:2204.00673v22022
InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation
Xingchao Liu, Xiwen Zhang, Jianzhu Ma +2
cs.LGcs.CVarXiv:2309.06380v22023
Mitigating Neural Network Overconfidence with Logit Normalization
Hongxin Wei, Renchunzi Xie, Hao Cheng +3
cs.LGarXiv:2205.09310v22022
Identity Matters in Deep Learning
Moritz Hardt, Tengyu Ma
cs.LGcs.NEstat.MLarXiv:1611.04231v32016
MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations
Ajay Mandlekar, Soroush Nasiriany, Bowen Wen +5
cs.ROcs.AIcs.CVarXiv:2310.17596v12023
Beyond Parity: Fairness Objectives for Collaborative Filtering
Sirui Yao, Bert Huang
cs.IRcs.AIcs.LGarXiv:1705.08804v22017
Preserving Statistical Validity in Adaptive Data Analysis
Cynthia Dwork, Vitaly Feldman, Moritz Hardt +3
cs.LGcs.DSarXiv:1411.2664v32014
DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models
Yung-Sung Chuang, Yujia Xie, Hongyin Luo +3
cs.CLcs.AIcs.LGarXiv:2309.03883v22023
What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning
Wei Liu, Weihao Zeng, Keqing He +2
cs.CLcs.AIcs.LGarXiv:2312.15685v22023
Programmatically Interpretable Reinforcement Learning
Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh +2
cs.LGcs.AIcs.PLarXiv:1804.02477v32018
The Contextual Loss for Image Transformation with Non-Aligned Data
Roey Mechrez, Itamar Talmi, Lihi Zelnik-Manor
cs.CVcs.LGarXiv:1803.02077v42018
Decoupled Neural Interfaces using Synthetic Gradients
Max Jaderberg, Wojciech Marian Czarnecki, Simon Osindero +4
cs.LGarXiv:1608.05343v22016
Computing a Nonnegative Matrix Factorization -- Provably
Sanjeev Arora, Rong Ge, Ravi Kannan +1
cs.DScs.LGarXiv:1111.0952v12011
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search
Colin White, Willie Neiswanger, Yash Savani
cs.LGcs.NEstat.MLarXiv:1910.11858v32019
Neural Lyapunov Control
Ya-Chien Chang, Nima Roohi, Sicun Gao
cs.LGcs.NEcs.ROarXiv:2005.00611v42020
Bridging short- and medium-range weather forecasting with machine learning
Timothy A. Smith, Mariah Pope, Sergey Frolov +4
physics.ao-phcs.LGarXiv:2608.26822v12026
Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models
Samuel Marks, Can Rager, Eric J. Michaud +3
cs.LGcs.AIcs.CLarXiv:2403.19647v32024

Machine Learning

Geometric Deep Learning on Molecular Representations

Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks

What's Hidden in a Randomly Weighted Neural Network?

TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting

NeMo: a toolkit for building AI applications using Neural Modules

Subgraph Filtering for Fair Graph Neural Networks

NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models

Geometry-Informed Neural Operator for Large-Scale 3D PDEs

A causal graph-informed temporal convolution architecture for interpretable retail electricity price forecasting

ReZero is All You Need: Fast Convergence at Large Depth

Co-Evolving Structured Knowledge and Reasoning in Language Models

Efficient Online Reinforcement Learning with Offline Data

Recurrent Batch Normalization

Insights into Performance Fitness and Error Metrics for Machine Learning

A Survey of Deep Learning Techniques for Weed Detection from Images

Training behavior of deep neural network in frequency domain

Distributed Training using an Intelligent Network

Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations

ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization

Privacy Preserving Machine Learning: Threats and Solutions

Understanding and Robustifying Differentiable Architecture Search

Data Augmentation Can Improve Robustness

Learning Sampling Distributions for Robot Motion Planning

Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning

Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translation

Visual Classification via Description from Large Language Models

Local Differential Privacy based Federated Learning for Internet of Things

Predicting Station-level Hourly Demands in a Large-scale Bike-sharing Network: A Graph Convolutional Neural Network Approach

Arrive and Survive: Scaling Safe Goal-Conditioned Policy Learning from One-Bit Failure Signals

Making Latent Evolution Explicit: Operator-Structured Transitions for World Action Models

Spectral Norm Regularization for Improving the Generalizability of Deep Learning

Word Representations via Gaussian Embedding

Exponentially Weighted Moving Average Charts for Detecting Concept Drift

Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning

PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training

Experience-driven Networking: A Deep Reinforcement Learning based Approach

Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data

A Survey of Deep Meta-Learning

RMP-SNN: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Network

Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble

Hyperbolic Image Embeddings

High Dimensional Bayesian Optimisation and Bandits via Additive Models

Learnable latent embeddings for joint behavioral and neural analysis

InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation

Mitigating Neural Network Overconfidence with Logit Normalization

Identity Matters in Deep Learning

MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations

Beyond Parity: Fairness Objectives for Collaborative Filtering

Preserving Statistical Validity in Adaptive Data Analysis

DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models

What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning

Programmatically Interpretable Reinforcement Learning

The Contextual Loss for Image Transformation with Non-Aligned Data

Decoupled Neural Interfaces using Synthetic Gradients

Computing a Nonnegative Matrix Factorization -- Provably

BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search

Neural Lyapunov Control

Bridging short- and medium-range weather forecasting with machine learning

Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models