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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9,361 to 9,420 of 9,676

On Robustness of Neural Ordinary Differential Equations
Hanshu Yan, Jiawei Du, Vincent Y. F. Tan +1
cs.LGstat.MLarXiv:1910.05513v42019
Causal-learn: Causal Discovery in Python
Yujia Zheng, Biwei Huang, Wei Chen +6
cs.LGstat.MEstat.MLarXiv:2307.16405v12023
Fashion-Gen: The Generative Fashion Dataset and Challenge
Negar Rostamzadeh, Seyedarian Hosseini, Thomas Boquet +4
stat.MLcs.LGarXiv:1806.08317v22018
Hidden Fluid Mechanics: A Navier-Stokes Informed Deep Learning Framework for Assimilating Flow Visualization Data
Maziar Raissi, Alireza Yazdani, George Em Karniadakis
cs.CEcs.LGphysics.flu-dynarXiv:1808.04327v12018
Attention Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images
Aleksandar Vakanski, Min Xian, Phoebe Freer
eess.IVcs.LGstat.MLarXiv:1910.08978v22019
Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data
Ethan Steinberg, Ken Jung, Jason A. Fries +3
cs.CLcs.LGstat.MLarXiv:2001.05295v22020
An Architecture Combining Convolutional Neural Network (CNN) and Support Vector Machine (SVM) for Image Classification
Abien Fred Agarap
cs.CVcs.LGcs.NEarXiv:1712.03541v22017
Detecting and interpreting myocardial infarction using fully convolutional neural networks
Nils Strodthoff, Claas Strodthoff
cs.CYcs.LGstat.MLarXiv:1806.07385v22018
Few-Shot Learning with Localization in Realistic Settings
Davis Wertheimer, Bharath Hariharan
cs.CVcs.AIcs.LGarXiv:1904.08502v22019
Stress Field Prediction in Cantilevered Structures Using Convolutional Neural Networks
Zhenguo Nie, Haoliang Jiang, Levent Burak Kara
cs.LGstat.MLarXiv:1808.08914v32018
Learning from VAE Errors to support ECG-based Differential Diagnosis of Myocardial Scar
Shayan Sharifi, Riccardo Treu, Ilaria Gandin +3
cs.LGstat.MLarXiv:2609.05294v12026
Limits of End-to-End Learning
Tobias Glasmachers
cs.LGstat.MLarXiv:1704.08305v12017
Removal of Batch Effects using Distribution-Matching Residual Networks
Uri Shaham, Kelly P. Stanton, Jun Zhao +4
stat.MLarXiv:1610.04181v62016
Split Learning for collaborative deep learning in healthcare
Maarten G. Poirot, Praneeth Vepakomma, Ken Chang +3
cs.LGcs.DCstat.MLarXiv:1912.12115v12019
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks
John Bradshaw, Alexander G. de G. Matthews, Zoubin Ghahramani
stat.MLarXiv:1707.02476v12017
Prostate Cancer Diagnosis using Deep Learning with 3D Multiparametric MRI
Saifeng Liu, Huaixiu Zheng, Yesu Feng +1
cs.CVstat.MLarXiv:1703.04078v12017
More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence
Tianqing Zhu, Dayong Ye, Wei Wang +2
cs.CRcs.LGstat.MLarXiv:2008.01916v12020
Building Damage Detection in Satellite Imagery Using Convolutional Neural Networks
Joseph Z. Xu, Wenhan Lu, Zebo Li +2
cs.CVcs.LGeess.IVarXiv:1910.06444v12019
N2N Learning: Network to Network Compression via Policy Gradient Reinforcement Learning
Anubhav Ashok, Nicholas Rhinehart, Fares Beainy +1
cs.LGstat.MLarXiv:1709.06030v22017
Artificial Intelligence and Statistics
Bin Yu, Karl Kumbier
stat.MLcs.AIarXiv:1712.03779v12017
An Overview of Melanoma Detection in Dermoscopy Images Using Image Processing and Machine Learning
Nabin K. Mishra, M. Emre Celebi
cs.CVstat.MLarXiv:1601.07843v12016
Deep Learning for Reliable Mobile Edge Analytics in Intelligent Transportation Systems
Aidin Ferdowsi, Ursula Challita, Walid Saad
cs.ITstat.MLarXiv:1712.04135v12017
End-to-End Deep Reinforcement Learning for Lane Keeping Assist
Ahmad El Sallab, Mohammed Abdou, Etienne Perot +1
stat.MLcs.LGcs.ROarXiv:1612.04340v12016
Continual Learning via Neural Pruning
Siavash Golkar, Michael Kagan, Kyunghyun Cho
cs.LGcs.NEq-bio.NCarXiv:1903.04476v12019
Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation
Po-Sen Huang, Robert Stanforth, Johannes Welbl +5
cs.CLcs.CRcs.LGarXiv:1909.01492v22019
TristouNet: Triplet Loss for Speaker Turn Embedding
Hervé Bredin
cs.SDstat.MLarXiv:1609.04301v32016
Adversarial Attacks on Machine Learning Cybersecurity Defences in Industrial Control Systems
Eirini Anthi, Lowri Williams, Matilda Rhode +2
cs.LGcs.CReess.SParXiv:2004.05005v12020
Maize Yield and Nitrate Loss Prediction with Machine Learning Algorithms
Mohsen Shahhosseini, Rafael A. Martinez-Feria, Guiping Hu +1
q-bio.OTcs.LGstat.AParXiv:1908.06746v52019
Overfitting Mechanism and Avoidance in Deep Neural Networks
Shaeke Salman, Xiuwen Liu
cs.LGcs.NEstat.MLarXiv:1901.06566v12019
Pushing the limits of unconstrained machine-learned interatomic potentials
Filippo Bigi, Paolo Pegolo, Arslan Mazitov +2
physics.chem-phstat.MLarXiv:2601.16195v32026
Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data
Felipe Petroski Such, Aditya Rawal, Joel Lehman +2
cs.LGstat.MLarXiv:1912.07768v12019
Unsupervised Learning by Competing Hidden Units
Dmitry Krotov, John Hopfield
cs.LGcs.CVcs.NEarXiv:1806.10181v22018
Insights into LSTM Fully Convolutional Networks for Time Series Classification
Fazle Karim, Somshubra Majumdar, Houshang Darabi
cs.LGstat.MLarXiv:1902.10756v32019
Integer Discrete Flows and Lossless Compression
Emiel Hoogeboom, Jorn W. T. Peters, Rianne van den Berg +1
cs.LGcs.CVstat.MLarXiv:1905.07376v42019
Blocks and Fuel: Frameworks for deep learning
Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin +4
cs.LGcs.NEstat.MLarXiv:1506.00619v12015
Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget
Jaewoo Lee, Daniel Kifer
cs.LGstat.MLarXiv:1808.09501v12018
Gotta Learn Fast: A New Benchmark for Generalization in RL
Alex Nichol, Vicki Pfau, Christopher Hesse +2
cs.LGstat.MLarXiv:1804.03720v22018
Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks
Charith Mendis, Alex Renda, Saman Amarasinghe +1
cs.DCcs.LGstat.MLarXiv:1808.07412v22018
On the Reliability of Generative Augmentation: A Wasserstein-Based Theoretical and Empirical Study
Chathurika S Abeykoon, Mathias Nthiani Muia, Mallory Goldstein
stat.MLcs.LGarXiv:2609.01410v12026
AdaComp : Adaptive Residual Gradient Compression for Data-Parallel Distributed Training
Chia-Yu Chen, Jungwook Choi, Daniel Brand +3
cs.LGstat.MLarXiv:1712.02679v12017
A feature agnostic approach for glaucoma detection in OCT volumes
Stefan Maetschke, Bhavna Antony, Hiroshi Ishikawa +3
cs.CVcs.LGstat.MLarXiv:1807.04855v42018
Neural Embeddings of Graphs in Hyperbolic Space
Benjamin Paul Chamberlain, James Clough, Marc Peter Deisenroth
stat.MLcs.LGarXiv:1705.10359v12017
PhaseLink: A Deep Learning Approach to Seismic Phase Association
Zachary E. Ross, Yisong Yue, Men-Andrin Meier +2
cs.LGphysics.geo-phstat.MLarXiv:1809.02880v22018
Imitation Learning from Imperfect Demonstration
Yueh-Hua Wu, Nontawat Charoenphakdee, Han Bao +2
cs.LGcs.AIstat.MLarXiv:1901.09387v32019
Unsupervised Control Through Non-Parametric Discriminative Rewards
David Warde-Farley, Tom Van de Wiele, Tejas Kulkarni +3
cs.LGcs.AIstat.MLarXiv:1811.11359v12018
Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs
Lei Cai, Zhengzhang Chen, Chen Luo +4
cs.LGcs.SIstat.MLarXiv:2005.07427v22020
PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings
Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt +4
cs.LGcs.AIstat.MLarXiv:2007.14175v22020
Global Sparse Momentum SGD for Pruning Very Deep Neural Networks
Xiaohan Ding, Guiguang Ding, Xiangxin Zhou +3
cs.LGcs.CVstat.MLarXiv:1909.12778v32019
Latent Replay for Real-Time Continual Learning
Lorenzo Pellegrini, Gabriele Graffieti, Vincenzo Lomonaco +1
cs.LGcs.CVstat.MLarXiv:1912.01100v22019
Evaluation of the MACE Force Field Architecture: from Medicinal Chemistry to Materials Science
David Peter Kovacs, Ilyes Batatia, Eszter Sara Arany +1
physics.chem-phstat.MLarXiv:2305.14247v22023
GraKeL: A Graph Kernel Library in Python
Giannis Siglidis, Giannis Nikolentzos, Stratis Limnios +3
stat.MLcs.LGarXiv:1806.02193v22018
Jet Flavour Classification Using DeepJet
Emil Bols, Jan Kieseler, Mauro Verzetti +2
hep-exphysics.data-anstat.MLarXiv:2008.10519v22020
Transparency and Explanation in Deep Reinforcement Learning Neural Networks
Rahul Iyer, Yuezhang Li, Huao Li +3
cs.LGstat.MLarXiv:1809.06061v12018
Multivariate Industrial Time Series with Cyber-Attack Simulation: Fault Detection Using an LSTM-based Predictive Data Model
Pavel Filonov, Andrey Lavrentyev, Artem Vorontsov
cs.LGstat.MLarXiv:1612.06676v22016
Learning from Failure: Training Debiased Classifier from Biased Classifier
Junhyun Nam, Hyuntak Cha, Sungsoo Ahn +2
cs.LGstat.MLarXiv:2007.02561v22020
Coarse-Graining Auto-Encoders for Molecular Dynamics
Wujie Wang, Rafael Gómez-Bombarelli
physics.chem-phcs.LGstat.MLarXiv:1812.02706v22018
Achieving Fairness through Adversarial Learning: an Application to Recidivism Prediction
Christina Wadsworth, Francesca Vera, Chris Piech
cs.LGstat.MLarXiv:1807.00199v12018
Deep Learning Approach to Diabetic Retinopathy Detection
Borys Tymchenko, Philip Marchenko, Dmitry Spodarets
cs.LGstat.MLarXiv:2003.02261v12020
Curriculum Adversarial Training
Qi-Zhi Cai, Min Du, Chang Liu +1
cs.LGcs.CRstat.MLarXiv:1805.04807v12018
PCGRL: Procedural Content Generation via Reinforcement Learning
Ahmed Khalifa, Philip Bontrager, Sam Earle +1
cs.LGcs.AIstat.MLarXiv:2001.09212v32020

Machine Learning (stat)

On Robustness of Neural Ordinary Differential Equations

Causal-learn: Causal Discovery in Python

Fashion-Gen: The Generative Fashion Dataset and Challenge

Hidden Fluid Mechanics: A Navier-Stokes Informed Deep Learning Framework for Assimilating Flow Visualization Data

Attention Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images

Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data

An Architecture Combining Convolutional Neural Network (CNN) and Support Vector Machine (SVM) for Image Classification

Detecting and interpreting myocardial infarction using fully convolutional neural networks

Few-Shot Learning with Localization in Realistic Settings

Stress Field Prediction in Cantilevered Structures Using Convolutional Neural Networks

Learning from VAE Errors to support ECG-based Differential Diagnosis of Myocardial Scar

Limits of End-to-End Learning

Removal of Batch Effects using Distribution-Matching Residual Networks

Split Learning for collaborative deep learning in healthcare

Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks

Prostate Cancer Diagnosis using Deep Learning with 3D Multiparametric MRI

More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence

Building Damage Detection in Satellite Imagery Using Convolutional Neural Networks

N2N Learning: Network to Network Compression via Policy Gradient Reinforcement Learning

Artificial Intelligence and Statistics

An Overview of Melanoma Detection in Dermoscopy Images Using Image Processing and Machine Learning

Deep Learning for Reliable Mobile Edge Analytics in Intelligent Transportation Systems

End-to-End Deep Reinforcement Learning for Lane Keeping Assist

Continual Learning via Neural Pruning

Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation

TristouNet: Triplet Loss for Speaker Turn Embedding

Adversarial Attacks on Machine Learning Cybersecurity Defences in Industrial Control Systems

Maize Yield and Nitrate Loss Prediction with Machine Learning Algorithms

Overfitting Mechanism and Avoidance in Deep Neural Networks

Pushing the limits of unconstrained machine-learned interatomic potentials

Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data

Unsupervised Learning by Competing Hidden Units

Insights into LSTM Fully Convolutional Networks for Time Series Classification

Integer Discrete Flows and Lossless Compression

Blocks and Fuel: Frameworks for deep learning

Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget

Gotta Learn Fast: A New Benchmark for Generalization in RL

Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks

On the Reliability of Generative Augmentation: A Wasserstein-Based Theoretical and Empirical Study

AdaComp : Adaptive Residual Gradient Compression for Data-Parallel Distributed Training

A feature agnostic approach for glaucoma detection in OCT volumes

Neural Embeddings of Graphs in Hyperbolic Space

PhaseLink: A Deep Learning Approach to Seismic Phase Association

Imitation Learning from Imperfect Demonstration

Unsupervised Control Through Non-Parametric Discriminative Rewards

Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs

PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings

Global Sparse Momentum SGD for Pruning Very Deep Neural Networks

Latent Replay for Real-Time Continual Learning

Evaluation of the MACE Force Field Architecture: from Medicinal Chemistry to Materials Science

GraKeL: A Graph Kernel Library in Python

Jet Flavour Classification Using DeepJet

Transparency and Explanation in Deep Reinforcement Learning Neural Networks

Multivariate Industrial Time Series with Cyber-Attack Simulation: Fault Detection Using an LSTM-based Predictive Data Model

Learning from Failure: Training Debiased Classifier from Biased Classifier

Coarse-Graining Auto-Encoders for Molecular Dynamics

Achieving Fairness through Adversarial Learning: an Application to Recidivism Prediction

Deep Learning Approach to Diabetic Retinopathy Detection

Curriculum Adversarial Training

PCGRL: Procedural Content Generation via Reinforcement Learning