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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6,721 to 6,780 of 6,782

Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Yarin Gal, Zoubin Ghahramani
stat.MLcs.LGarXiv:1506.02142v62015
Diffusion Models Beat GANs on Image Synthesis
Prafulla Dhariwal, Alex Nichol
cs.LGcs.AIcs.CVarXiv:2105.05233v42021
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
Mike Lewis, Yinhan Liu, Naman Goyal +5
cs.CLcs.LGstat.MLarXiv:1910.13461v12019
Summaries:한국어
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang, Moustapha Cisse, Yann N. Dauphin +1
cs.LGstat.MLarXiv:1710.09412v22017
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
Christian Ledig, Lucas Theis, Ferenc Huszar +8
cs.CVstat.MLarXiv:1609.04802v52016
node2vec: Scalable Feature Learning for Networks
Aditya Grover, Jure Leskovec
cs.SIcs.LGstat.MLarXiv:1607.00653v12016
Feature Priming in Online Linear Regression: Sparse-Regret Lower Bounds and a Tight Univariate Rate
Huibo Xu, Shi Fu, Qixin Zhang +1
stat.MLcs.LGstat.AParXiv:2608.17573v12026
Layer Normalization
Jimmy Lei Ba, Jamie Ryan Kiros, Geoffrey E. Hinton
stat.MLcs.LGarXiv:1607.06450v12016
A Style-Based Generator Architecture for Generative Adversarial Networks
Tero Karras, Samuli Laine, Timo Aila
cs.NEcs.LGstat.MLarXiv:1812.04948v32018
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt +2
stat.MLcs.LGcs.NEarXiv:1706.06083v42017
Continuous control with deep reinforcement learning
Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel +5
cs.LGstat.MLarXiv:1509.02971v62015
Tight Bounds for Data-driven Multiple Hyper-parameter Tuning with Structured Loss Function
Anh Tuan Nguyen, Viet Anh Nguyen
cs.LGstat.MLarXiv:2608.17343v12026
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Mingxing Tan, Quoc V. Le
cs.LGcs.CVstat.MLarXiv:1905.11946v52019
Inductive Representation Learning on Large Graphs
William L. Hamilton, Rex Ying, Jure Leskovec
cs.SIcs.LGstat.MLarXiv:1706.02216v42017
Explaining and Harnessing Adversarial Examples
Ian J. Goodfellow, Jonathon Shlens, Christian Szegedy
stat.MLcs.LGarXiv:1412.6572v32014
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre +4
cs.CLcs.LGcs.NEarXiv:1406.1078v32014
Information fusion and machine learning for sensitivity analysis using physics knowledge and experimental data
Berkcan Kapusuzoglu, Sankaran Mahadevan
cs.CEcs.LGstat.MEarXiv:2608.17248v12026
Graph Attention Networks
Petar Veličković, Guillem Cucurull, Arantxa Casanova +3
stat.MLcs.AIcs.LGarXiv:1710.10903v32017
A Unified Approach to Interpreting Model Predictions
Scott Lundberg, Su-In Lee
cs.AIcs.LGstat.MLarXiv:1705.07874v22017
Distributed Representations of Words and Phrases and their Compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen +2
cs.CLcs.LGstat.MLarXiv:1310.4546v12013
Benchmarking Quantum Machine Learning for Power-System Attack Detection: Evaluation Choices Decide the Outcome Before the Models Do
Md Rezwanul Islam
cs.LGcs.CRstat.MLarXiv:2608.15617v12026
Semi-Supervised Classification with Graph Convolutional Networks
Thomas N. Kipf, Max Welling
cs.LGstat.MLarXiv:1609.02907v42016
Thinking in a Low-Resource Language: What SFT Builds, What RL Fixes, What Accuracy Cannot See
Ayoub Kirouane, Christos Petrocheilos
cs.CLcs.LGcs.ROarXiv:2608.17744v12026
The Data Manifold under the Microscope
Marios Koulakis, Constantin Seibold
cs.LGstat.MLarXiv:2606.15760v12026
Rethinking Reverse KL as Adaptive Entropy Distillation
Shizhen Li, Zhiyu Shen, Yuyin Lu +4
cs.LGstat.MLarXiv:2608.14685v12026
Convolution Smoothed Quantile Regression for XGBoost
Mandy Yao, Meredith Franklin
stat.MLcs.LGarXiv:2608.15290v12026
Cross-Entropy Risk Estimation for Language Models: Inconsistency Must Be Dense, and the Holdout Method Is No Exception
Hanti Lin
cs.LGstat.MLarXiv:2608.15798v12026
Queryable LoRA: Instruction-Regularized Routing Over Shared Low-Rank Update Atoms
Omatharv Bharat Vaidya, Connor T. Jerzak, Nhat Ho +1
cs.LGcs.CLstat.MLarXiv:2605.08423v12026
The Distributional View of Knowledge Distillation
Gordei Verbii, Juho Lee
stat.MLcs.LGarXiv:2608.15215v12026
Summaries:한국어
Generative Learning of Separatrices
Ellis R. Crabtree, Dimitris G. Giovanis, Anastasia Georgiou +2
cs.LGmath.DSstat.MLarXiv:2608.14743v12026
Shape Operator PCA: Curvature-Aware Projections for Geometric Machine Learning
Alexandre L. M. Levada
cs.LGcs.AIcs.CVarXiv:2608.15313v12026
Adaptive surrogate modeling for high-dimensional spatio-temporal output
Berkcan Kapusuzoglu, Shunsaku Matsumoto, Yoshitomo Miyagi +2
cs.CEcs.AIcs.LGarXiv:2608.17250v12026
A Deep Learning Model for Spatially Clustered Data via Differentiable Cluster Assignment
Kexuan Li, Weidong Ma
stat.MLcs.LGarXiv:2608.14968v12026
ARISE: An adaptive residual-informed stability ensemble for feature selection in small-sample biomedical omics
Zardad Khan, Amjad Ali, Naz Gul +2
stat.MLcs.LGarXiv:2608.14866v12026
How Many Samples Are Needed to Determine Causal Direction? Sharp Minimax Bounds for Bivariate LiNGAM
Jikai Jin
math.STcs.LGecon.EMarXiv:2608.15840v12026
Inferential Evaluation of Surrogate-Derived Models under Covariate Shift
Longtian Shi, Molei Liu, Doudou Zhou
stat.MLcs.LGstat.AParXiv:2608.15783v12026
Self-Supervised Auxiliary Task Discovery for Stable Reinforcement Learning in Stock Trading
Arishi Orra, Himanshu Choudhary, Manoj Thakur
cs.LGq-fin.CPstat.MLarXiv:2608.15841v12026
Learning Stock Trading Policies via Barycenter-Based Adversarial Inverse Reinforcement Learning
Arishi Orra, Himanshu Choudhary, Manoj Thakur
cs.LGstat.MLarXiv:2608.15770v12026
FirstDiff: One-Step Diffusion-Based Anomaly Detection for Multivariate Time Series via Initial Noise Prediction
Ali Boudaghi, Alireza Nemati, Hadi Zare
cs.LGcs.AIstat.MLarXiv:2608.15727v12026
PERO: Efficient Robust Post-Training Foundation Models for Encrypted Traffic Classification
Wumei Du, Jiarong Wen, Kaiyu Zhang +5
cs.LGstat.MLarXiv:2608.15504v12026
Conditional Evaluation of Language Models with Cheap Auxiliary Signals
Zhi Zhang, Lingfeng Lyu, Yue Kang +1
cs.LGstat.MLarXiv:2608.16210v12026
Pion: A Spectrum-Preserving Optimizer via Orthogonal Equivalence Transformation
Kexuan Shi, Hanxuan Li, Zeju Qiu +3
cs.LGstat.MLarXiv:2605.12492v12026
Hide&Seek: Learning to Explain in an End-to-End Differentiable Network
Tal Ellinson, Hadi Mohasel Afshar, Sally Cripps
stat.MLcs.LGarXiv:2608.16689v12026
A Unified Geometric Framework for Developmental Analysis of Spatial Transcriptomic Data
Mary Chriselda Antony Oliver, Kaitlyn Hohmeier, Tuyen Tran +3
stat.MLcs.LGmath.MGarXiv:2608.15306v12026
Coded Hankel Polynomial Chaos: Spectral Identification of Dominant Polynomial-Chaos Modes
Zhiliang Deng, Xiaomei Yang
stat.MLcs.LGarXiv:2608.16126v12026
Scale-Consistent Posterior Dynamics for Diffusion Inverse Problems
Zhaoqiang Liu, Tongyao Pang, Ruibing Wang +1
stat.MLcs.AIcs.LGarXiv:2608.15144v12026
Beyond Effective Sample Size: Effective Number of Proposals for Adaptive Importance Sampling
Ali Mousavi, Victor Elvira
stat.MLcs.LGarXiv:2608.15154v12026
PathFinder: Joint Decompositions of Linked Multimodal Datasets
Ying-Qiu Zheng, Alex Fung, Stephen M Smith +2
cs.LGeess.IVq-bio.QMarXiv:2608.14951v12026
GRPO, Dr. GRPO, and DAPO Are Three Operations on One Number: The Group-Standard-Deviation Identity
Yong Yi Bay, Kathleen A. Yearick
cs.LGcs.AIcs.CLarXiv:2607.00152v12026
SiamJEPA: On the Role of Siamese Student Encoders in JEPA
Makoto Yamada
cs.CVstat.MLarXiv:2607.04044v22026
TREK: Distill to Explore, Reinforce to Refine
Yuanda Xu, Zhengze Zhou, Kayhan Behdin +10
cs.LGcs.AIstat.MLarXiv:2607.05339v12026
When More Sampling Hurts: The Modal Ceiling and Correlation Ceiling of Test-Time Scaling
Yong Yi Bay, Kathleen A. Yearick
cs.LGcs.AIcs.CLarXiv:2606.28661v12026
High-dimensional nonparametric changepoint detection via low-rank degree-two density projection
Guoqing Zhang, Zhaixin Chen
cs.LGstat.MLarXiv:2608.13922v12026
Multi-Turn On-Policy Distillation with Prefix Replay
Baohao Liao, Hanze Dong, Christof Monz +3
cs.LGcs.AIcs.CLarXiv:2607.04763v32026
Round-Trip Consistency: Bidirectional Diffusion Models Can Predict Their Own Rollout Errors
Alexander Scheinker
stat.MLcs.LGphysics.comp-pharXiv:2608.00675v22026
Learning Unsteady Aneurysm Hemodynamics with Physics-Informed DeepONets
Oscar L. Cruz-Gonzalez, Valérie Deplano, Badih Ghattas
stat.MLcs.LGphysics.flu-dynarXiv:2608.13629v12026
On the Brittleness of Maximum Likelihood Estimation for Gaussian Process Hyperparameter Optimization
Tyler R. Johnson, Kian Ben-Jacob, Christopher P. Muller +1
stat.MLcs.LGstat.MEarXiv:2608.13793v12026
L-FNO: Lorentzian Fourier Neural Operator for Stochastic Event Dynamics
Songhee Kang, Jihoon Kang
cs.LGstat.MLarXiv:2608.13562v12026
When Does More Correct Data Hurt? Insertion-Stability and the Limits of Dimension-Based Theory
Joseph Sankoorikal Johny
cs.LGstat.MLarXiv:2608.14020v12026
Forecast Collapse in Time-Series Foundation Models
Shu Wan, Miles Ma, Hank Zhu +4
cs.LGcs.AIcs.CEarXiv:2608.14106v12026

Machine Learning (stat)

Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

Diffusion Models Beat GANs on Image Synthesis

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

mixup: Beyond Empirical Risk Minimization

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

node2vec: Scalable Feature Learning for Networks

Feature Priming in Online Linear Regression: Sparse-Regret Lower Bounds and a Tight Univariate Rate

Layer Normalization

A Style-Based Generator Architecture for Generative Adversarial Networks

Towards Deep Learning Models Resistant to Adversarial Attacks

Continuous control with deep reinforcement learning

Tight Bounds for Data-driven Multiple Hyper-parameter Tuning with Structured Loss Function

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Inductive Representation Learning on Large Graphs

Explaining and Harnessing Adversarial Examples

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

Information fusion and machine learning for sensitivity analysis using physics knowledge and experimental data

Graph Attention Networks

A Unified Approach to Interpreting Model Predictions

Distributed Representations of Words and Phrases and their Compositionality

Benchmarking Quantum Machine Learning for Power-System Attack Detection: Evaluation Choices Decide the Outcome Before the Models Do

Semi-Supervised Classification with Graph Convolutional Networks

Thinking in a Low-Resource Language: What SFT Builds, What RL Fixes, What Accuracy Cannot See

The Data Manifold under the Microscope

Rethinking Reverse KL as Adaptive Entropy Distillation

Convolution Smoothed Quantile Regression for XGBoost

Cross-Entropy Risk Estimation for Language Models: Inconsistency Must Be Dense, and the Holdout Method Is No Exception

Queryable LoRA: Instruction-Regularized Routing Over Shared Low-Rank Update Atoms

The Distributional View of Knowledge Distillation

Generative Learning of Separatrices

Shape Operator PCA: Curvature-Aware Projections for Geometric Machine Learning

Adaptive surrogate modeling for high-dimensional spatio-temporal output

A Deep Learning Model for Spatially Clustered Data via Differentiable Cluster Assignment

ARISE: An adaptive residual-informed stability ensemble for feature selection in small-sample biomedical omics

How Many Samples Are Needed to Determine Causal Direction? Sharp Minimax Bounds for Bivariate LiNGAM

Inferential Evaluation of Surrogate-Derived Models under Covariate Shift

Self-Supervised Auxiliary Task Discovery for Stable Reinforcement Learning in Stock Trading

Learning Stock Trading Policies via Barycenter-Based Adversarial Inverse Reinforcement Learning

FirstDiff: One-Step Diffusion-Based Anomaly Detection for Multivariate Time Series via Initial Noise Prediction

PERO: Efficient Robust Post-Training Foundation Models for Encrypted Traffic Classification

Conditional Evaluation of Language Models with Cheap Auxiliary Signals

Pion: A Spectrum-Preserving Optimizer via Orthogonal Equivalence Transformation

Hide&Seek: Learning to Explain in an End-to-End Differentiable Network

A Unified Geometric Framework for Developmental Analysis of Spatial Transcriptomic Data

Coded Hankel Polynomial Chaos: Spectral Identification of Dominant Polynomial-Chaos Modes

Scale-Consistent Posterior Dynamics for Diffusion Inverse Problems

Beyond Effective Sample Size: Effective Number of Proposals for Adaptive Importance Sampling

PathFinder: Joint Decompositions of Linked Multimodal Datasets

GRPO, Dr. GRPO, and DAPO Are Three Operations on One Number: The Group-Standard-Deviation Identity

SiamJEPA: On the Role of Siamese Student Encoders in JEPA

TREK: Distill to Explore, Reinforce to Refine

When More Sampling Hurts: The Modal Ceiling and Correlation Ceiling of Test-Time Scaling

High-dimensional nonparametric changepoint detection via low-rank degree-two density projection

Multi-Turn On-Policy Distillation with Prefix Replay

Round-Trip Consistency: Bidirectional Diffusion Models Can Predict Their Own Rollout Errors

Learning Unsteady Aneurysm Hemodynamics with Physics-Informed DeepONets

On the Brittleness of Maximum Likelihood Estimation for Gaussian Process Hyperparameter Optimization

L-FNO: Lorentzian Fourier Neural Operator for Stochastic Event Dynamics

When Does More Correct Data Hurt? Insertion-Stability and the Limits of Dimension-Based Theory

Forecast Collapse in Time-Series Foundation Models