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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6,601 to 6,660 of 6,785

RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie +1
cs.LGcs.CLstat.MLarXiv:1902.10197v12019
Stochastic Variational Inference
Matt Hoffman, David M. Blei, Chong Wang +1
stat.MLcs.AIstat.COarXiv:1206.7051v32012
A Survey on Deep Transfer Learning
Chuanqi Tan, Fuchun Sun, Tao Kong +3
cs.LGstat.MLarXiv:1808.01974v12018
StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
Han Zhang, Tao Xu, Hongsheng Li +4
cs.CVcs.AIstat.MLarXiv:1612.03242v22016
T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Prediction
Ling Zhao, Yujiao Song, Chao Zhang +5
cs.LGstat.MLarXiv:1811.05320v32018
Reformer: The Efficient Transformer
Nikita Kitaev, Łukasz Kaiser, Anselm Levskaya
cs.LGcs.CLstat.MLarXiv:2001.04451v22020
CNN Architectures for Large-Scale Audio Classification
Shawn Hershey, Sourish Chaudhuri, Daniel P. W. Ellis +10
cs.SDcs.LGstat.MLarXiv:1609.09430v22016
Efficient Neural Architecture Search via Parameter Sharing
Hieu Pham, Melody Y. Guan, Barret Zoph +2
cs.LGcs.CLcs.CVarXiv:1802.03268v22018
Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention
Angelos Katharopoulos, Apoorv Vyas, Nikolaos Pappas +1
cs.LGstat.MLarXiv:2006.16236v32020
Big Bird: Transformers for Longer Sequences
Manzil Zaheer, Guru Guruganesh, Avinava Dubey +8
cs.LGcs.CLstat.MLarXiv:2007.14062v22020
A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation
Nikolaus Mayer, Eddy Ilg, Philip Häusser +4
cs.CVcs.LGstat.MLarXiv:1512.02134v12015
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
Stefan Wager, Susan Athey
stat.MEmath.STstat.MLarXiv:1510.04342v42015
Summaries:한국어
A survey of cross-validation procedures for model selection
Sylvain Arlot, Alain Celisse
math.STstat.APstat.MEarXiv:0907.4728v12009
Towards a Physics Foundation Model
Florian Wiesner, Zoë J. Gray, Matthias Wessling +1
cs.LGcs.AIstat.MLarXiv:2509.13805v42025
Multimodal Deep Learning
Cem Akkus, Luyang Chu, Vladana Djakovic +14
cs.CLcs.LGstat.MLarXiv:2301.04856v12023
Summaries:한국어
Deep Learning with Differential Privacy
Martín Abadi, Andy Chu, Ian Goodfellow +4
stat.MLcs.CRcs.LGarXiv:1607.00133v22016
Robust Risk Under Evolving Uncertainty: A Wasserstein Counterpart of the Entropic Value-at-Risk
Deep Kumar Ganguly, Jan Křetínský
cs.AIcs.LGstat.MLarXiv:2608.19073v12026
Spatially explicit feature importance for building height estimation using research-access high-resolution SAR and optical sensors
Guilherme Iablonovski, Pierre-Louis Frison, Tatiana Silva da Silva
physics.soc-phcs.LGstat.MLarXiv:2608.17822v12026
Expected free energy as an information constraint on the Bethe Lagrangian
Wouter M. Kouw
cs.ITcs.AIeess.SYarXiv:2608.17167v12026
Sufficient Dimesion Reduction via Generalized Stein's Lemma
Ye Tian
stat.MLcs.LGstat.MEarXiv:2608.15121v12026
RouteTS: Frequency-Time Routing for Time Series Forecasting
Gaofeng Lin, Lei Duan
cs.LGstat.MLarXiv:2608.14682v12026
High-dimensional networks and mean squared error for possibly misspecified models
Lourens Waldorp
stat.MLcs.LGarXiv:2608.13171v12026
Summaries:简体中文
ProGen: Language Modeling for Protein Generation
Ali Madani, Bryan McCann, Nikhil Naik +5
q-bio.BMcs.LGstat.MLarXiv:2004.03497v12020
nuScenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H. Lang +7
cs.LGcs.CVcs.ROarXiv:1903.11027v52019
Parameter-Efficient Transfer Learning for NLP
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski +5
cs.LGcs.CLstat.MLarXiv:1902.00751v22019
Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation
David M. W. Powers
cs.LGstat.MEstat.MLarXiv:2010.16061v12020
Supervised Contrastive Learning
Prannay Khosla, Piotr Teterwak, Chen Wang +6
cs.LGcs.CVstat.MLarXiv:2004.11362v52020
A Simple Framework for Contrastive Learning of Visual Representations
Ting Chen, Simon Kornblith, Mohammad Norouzi +1
cs.LGcs.CVstat.MLarXiv:2002.05709v32020
Generative Modeling by Estimating Gradients of the Data Distribution
Yang Song, Stefano Ermon
cs.LGstat.MLarXiv:1907.05600v32019
Deep learning in agriculture: A survey
Andreas Kamilaris, Francesc X. Prenafeta-Boldu
cs.LGcs.CVstat.MLarXiv:1807.11809v12018
Glow: Generative Flow with Invertible 1x1 Convolutions
Diederik P. Kingma, Prafulla Dhariwal
stat.MLcs.AIcs.LGarXiv:1807.03039v22018
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel +1
cs.LGcs.AIstat.MLarXiv:1801.01290v22018
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan +1
cs.LGcond-mat.dis-nnq-bio.NCarXiv:1503.03585v82015
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
David Salinas, Valentin Flunkert, Jan Gasthaus
cs.AIcs.LGstat.MLarXiv:1704.04110v32017
Deep Graph Infomax
Petar Veličković, William Fedus, William L. Hamilton +3
stat.MLcs.ITcs.LGarXiv:1809.10341v22018
Ensemble Adversarial Training: Attacks and Defenses
Florian Tramèr, Alexey Kurakin, Nicolas Papernot +3
stat.MLcs.CRcs.LGarXiv:1705.07204v52017
Empirical Evaluation of Rectified Activations in Convolutional Network
Bing Xu, Naiyan Wang, Tianqi Chen +1
cs.LGcs.CVstat.MLarXiv:1505.00853v22015
Deep Leakage from Gradients
Ligeng Zhu, Zhijian Liu, Song Han
cs.LGcs.CRstat.MLarXiv:1906.08935v22019
Towards Federated Learning at Scale: System Design
Keith Bonawitz, Hubert Eichner, Wolfgang Grieskamp +11
cs.LGcs.DCstat.MLarXiv:1902.01046v22019
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
Robert Geirhos, Patricia Rubisch, Claudio Michaelis +3
cs.CVcs.AIcs.LGarXiv:1811.12231v32018
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels
Zhilu Zhang, Mert R. Sabuncu
cs.LGcs.CVstat.MLarXiv:1805.07836v42018
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
Nicolas Papernot, Patrick McDaniel, Xi Wu +2
cs.CRcs.LGcs.NEarXiv:1511.04508v22015
An Overview of Multi-Task Learning in Deep Neural Networks
Sebastian Ruder
cs.LGcs.AIstat.MLarXiv:1706.05098v12017
Deep learning for time series classification: a review
Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber +2
cs.LGcs.AIstat.MLarXiv:1809.04356v42018
Graph WaveNet for Deep Spatial-Temporal Graph Modeling
Zonghan Wu, Shirui Pan, Guodong Long +2
cs.LGstat.MLarXiv:1906.00121v12019
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning
Pranav Rajpurkar, Jeremy Irvin, Kaylie Zhu +9
cs.CVcs.LGstat.MLarXiv:1711.05225v32017
Pointer Networks
Oriol Vinyals, Meire Fortunato, Navdeep Jaitly
stat.MLcs.CGcs.LGarXiv:1506.03134v22015
Adversarial Machine Learning at Scale
Alexey Kurakin, Ian Goodfellow, Samy Bengio
cs.CVcs.CRcs.LGarXiv:1611.01236v22016
FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting
Tian Zhou, Ziqing Ma, Qingsong Wen +3
cs.LGstat.MLarXiv:2201.12740v32022
Ward's Hierarchical Clustering Method: Clustering Criterion and Agglomerative Algorithm
Fionn Murtagh, Pierre Legendre
stat.MLcs.CVstat.AParXiv:1111.6285v22011
Conditional Image Synthesis With Auxiliary Classifier GANs
Augustus Odena, Christopher Olah, Jonathon Shlens
stat.MLcs.CVarXiv:1610.09585v42016
Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning
Qimai Li, Zhichao Han, Xiao-Ming Wu
cs.LGstat.MLarXiv:1801.07606v12018
Convolutional Networks on Graphs for Learning Molecular Fingerprints
David Duvenaud, Dougal Maclaurin, Jorge Aguilera-Iparraguirre +4
cs.LGcs.NEstat.MLarXiv:1509.09292v22015
ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R
Marvin N. Wright, Andreas Ziegler
stat.MLstat.COarXiv:1508.04409v22015
Do Geometry-Aware Positional Encodings Help Transformers in Spatial Imperfect-Information Games?
Wenji Fu
cs.LGcs.AIstat.MLarXiv:2608.14982v12026
MixMatch: A Holistic Approach to Semi-Supervised Learning
David Berthelot, Nicholas Carlini, Ian Goodfellow +3
cs.LGcs.AIcs.CVarXiv:1905.02249v22019
Continual Lifelong Learning with Neural Networks: A Review
German I. Parisi, Ronald Kemker, Jose L. Part +2
cs.LGq-bio.NCstat.MLarXiv:1802.07569v42018
Relational inductive biases, deep learning, and graph networks
Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst +24
cs.LGcs.AIstat.MLarXiv:1806.01261v32018
Complex Embeddings for Simple Link Prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel +2
cs.AIcs.LGstat.MLarXiv:1606.06357v12016
Understanding Black-box Predictions via Influence Functions
Pang Wei Koh, Percy Liang
stat.MLcs.AIcs.LGarXiv:1703.04730v32017

Machine Learning (stat)

RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space

Stochastic Variational Inference

A Survey on Deep Transfer Learning

StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks

T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Prediction

Reformer: The Efficient Transformer

CNN Architectures for Large-Scale Audio Classification

Efficient Neural Architecture Search via Parameter Sharing

Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention

Big Bird: Transformers for Longer Sequences

A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation

Estimation and Inference of Heterogeneous Treatment Effects using Random Forests

A survey of cross-validation procedures for model selection

Towards a Physics Foundation Model

Multimodal Deep Learning

Deep Learning with Differential Privacy

Robust Risk Under Evolving Uncertainty: A Wasserstein Counterpart of the Entropic Value-at-Risk

Spatially explicit feature importance for building height estimation using research-access high-resolution SAR and optical sensors

Expected free energy as an information constraint on the Bethe Lagrangian

Sufficient Dimesion Reduction via Generalized Stein's Lemma

RouteTS: Frequency-Time Routing for Time Series Forecasting

High-dimensional networks and mean squared error for possibly misspecified models

ProGen: Language Modeling for Protein Generation

nuScenes: A multimodal dataset for autonomous driving

Parameter-Efficient Transfer Learning for NLP

Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation

Supervised Contrastive Learning

A Simple Framework for Contrastive Learning of Visual Representations

Generative Modeling by Estimating Gradients of the Data Distribution

Deep learning in agriculture: A survey

Glow: Generative Flow with Invertible 1x1 Convolutions

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

Deep Unsupervised Learning using Nonequilibrium Thermodynamics

DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks

Deep Graph Infomax

Ensemble Adversarial Training: Attacks and Defenses

Empirical Evaluation of Rectified Activations in Convolutional Network

Deep Leakage from Gradients

Towards Federated Learning at Scale: System Design

ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness

Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels

Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks

An Overview of Multi-Task Learning in Deep Neural Networks

Deep learning for time series classification: a review

Graph WaveNet for Deep Spatial-Temporal Graph Modeling

CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning

Pointer Networks

Adversarial Machine Learning at Scale

FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting

Ward's Hierarchical Clustering Method: Clustering Criterion and Agglomerative Algorithm

Conditional Image Synthesis With Auxiliary Classifier GANs

Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning

Convolutional Networks on Graphs for Learning Molecular Fingerprints

ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R

Do Geometry-Aware Positional Encodings Help Transformers in Spatial Imperfect-Information Games?

MixMatch: A Holistic Approach to Semi-Supervised Learning

Continual Lifelong Learning with Neural Networks: A Review

Relational inductive biases, deep learning, and graph networks

Complex Embeddings for Simple Link Prediction

Understanding Black-box Predictions via Influence Functions