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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9,601 to 9,660 of 9,676

CREPE: A Convolutional Representation for Pitch Estimation
Jong Wook Kim, Justin Salamon, Peter Li +1
eess.AScs.LGcs.SDarXiv:1802.06182v12018
A Study of BFLOAT16 for Deep Learning Training
Dhiraj Kalamkar, Dheevatsa Mudigere, Naveen Mellempudi +16
cs.LGstat.MLarXiv:1905.12322v32019
FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents
Guillaume Jaume, Hazim Kemal Ekenel, Jean-Philippe Thiran
cs.IRcs.CVcs.LGarXiv:1905.13538v22019
The huge Package for High-dimensional Undirected Graph Estimation in R
Tuo Zhao, Han Liu, Kathryn Roeder +2
stat.MLcs.LGmath.OCarXiv:2006.14781v12020
Predicting Alzheimer's disease: a neuroimaging study with 3D convolutional neural networks
Adrien Payan, Giovanni Montana
cs.CVcs.LGstat.AParXiv:1502.02506v12015
A Fair Comparison of Graph Neural Networks for Graph Classification
Federico Errica, Marco Podda, Davide Bacciu +1
cs.LGstat.MLarXiv:1912.09893v32019
Learning Features by Watching Objects Move
Deepak Pathak, Ross Girshick, Piotr Dollár +2
cs.CVcs.AIcs.LGarXiv:1612.06370v22016
Fine-Tuning Whisper for Automatic Speech Recognition in Baniwa: A Preliminary Study
Leonardo Duart, Tiago Fonseca, Thiago Chacón
cs.CLstat.MLarXiv:2608.26060v12026
AI4COVID-19: AI Enabled Preliminary Diagnosis for COVID-19 from Cough Samples via an App
Ali Imran, Iryna Posokhova, Haneya N. Qureshi +6
eess.AScs.LGcs.SDarXiv:2004.01275v62020
Hidden Stratification Causes Clinically Meaningful Failures in Machine Learning for Medical Imaging
Luke Oakden-Rayner, Jared Dunnmon, Gustavo Carneiro +1
cs.LGstat.MLarXiv:1909.12475v22019
Threats to Federated Learning: A Survey
Lingjuan Lyu, Han Yu, Qiang Yang
cs.CRcs.LGstat.MLarXiv:2003.02133v12020
NVExplain: Explaining Time Series Forecasting with Latent Trajectory Analysis and Structure-Preserving Surrogates
Muyan Anna Li, Manikandan Ravikiran, Aditi Gautam
cs.LGcs.AIstat.MLarXiv:2608.25080v12026
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges
Christoph Molnar, Giuseppe Casalicchio, Bernd Bischl
stat.MLcs.LGarXiv:2010.09337v12020
Representing MAX functions using two-hidden-layer ReLU networks
Zhimao Wang, Amitabh Basu
cs.LGmath.OCstat.MLarXiv:2608.25221v12026
Training Deep Neural Networks with 8-bit Floating Point Numbers
Naigang Wang, Jungwook Choi, Daniel Brand +2
cs.LGstat.MLarXiv:1812.08011v12018
A Self-Attentive model for Knowledge Tracing
Shalini Pandey, George Karypis
cs.LGcs.CYstat.MLarXiv:1907.06837v12019
Scale-invariant Optimal Sampling for Rare-events Data with Sparse Models
Jing Wang, HaiYing Wang, Qiang Zhang +1
stat.MLcs.LGarXiv:2608.22597v12026
AtomNet: A Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery
Izhar Wallach, Michael Dzamba, Abraham Heifets
cs.LGcs.NEq-bio.BMarXiv:1510.02855v12015
Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet
Wieland Brendel, Matthias Bethge
cs.CVcs.LGstat.MLarXiv:1904.00760v12019
Ansor: Generating High-Performance Tensor Programs for Deep Learning
Lianmin Zheng, Chengfan Jia, Minmin Sun +9
cs.LGcs.NEcs.PFarXiv:2006.06762v52020
Deep learning for neuroimaging: a validation study
Sergey M. Plis, Devon R. Hjelm, Ruslan Salakhutdinov +1
cs.NEcs.LGstat.MLarXiv:1312.5847v32013
The What-If Tool: Interactive Probing of Machine Learning Models
James Wexler, Mahima Pushkarna, Tolga Bolukbasi +3
cs.LGstat.MLarXiv:1907.04135v22019
Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation
Chen-Yu Lee, Tanmay Batra, Mohammad Haris Baig +1
cs.CVcs.LGstat.MLarXiv:1903.04064v12019
A review: Deep learning for medical image segmentation using multi-modality fusion
Tongxue Zhou, Su Ruan, Stéphane Canu
eess.IVcs.CVcs.LGarXiv:2004.10664v22020
Deep Learning in Medical Image Registration: A Review
Yabo Fu, Yang Lei, Tonghe Wang +3
eess.IVcs.CVcs.LGarXiv:1912.12318v12019
Generative and Discriminative Voxel Modeling with Convolutional Neural Networks
Andrew Brock, Theodore Lim, J. M. Ritchie +1
cs.CVcs.HCcs.LGarXiv:1608.04236v22016
Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons
Byeongho Heo, Minsik Lee, Sangdoo Yun +1
cs.LGcs.CVstat.MLarXiv:1811.03233v22018
Lagrangian Neural Networks
Miles Cranmer, Sam Greydanus, Stephan Hoyer +3
cs.LGmath.DSphysics.comp-pharXiv:2003.04630v22020
Deep Reinforcement Learning for Intelligent Transportation Systems: A Survey
Ammar Haydari, Yasin Yilmaz
cs.LGcs.MAeess.SParXiv:2005.00935v12020
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks
Jonathan Uesato, Brendan O'Donoghue, Aaron van den Oord +1
cs.LGcs.CRstat.MLarXiv:1802.05666v22018
Learning the Difference that Makes a Difference with Counterfactually-Augmented Data
Divyansh Kaushik, Eduard Hovy, Zachary C. Lipton
cs.CLcs.AIcs.LGarXiv:1909.12434v22019
Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networks
Hoo-Chang Shin, Neil A Tenenholtz, Jameson K Rogers +5
cs.CVcs.LGstat.MLarXiv:1807.10225v22018
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use
Sana Tonekaboni, Shalmali Joshi, Melissa D McCradden +1
cs.LGstat.MLarXiv:1905.05134v22019
Machine Learning in IoT Security: Current Solutions and Future Challenges
Fatima Hussain, Rasheed Hussain, Syed Ali Hassan +1
cs.CRcs.LGstat.MLarXiv:1904.05735v12019
Malware Detection by Eating a Whole EXE
Edward Raff, Jon Barker, Jared Sylvester +3
stat.MLcs.CRcs.LGarXiv:1710.09435v12017
Applied Federated Learning: Improving Google Keyboard Query Suggestions
Timothy Yang, Galen Andrew, Hubert Eichner +5
cs.LGstat.MLarXiv:1812.02903v12018
Wave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source Separation
Daniel Stoller, Sebastian Ewert, Simon Dixon
cs.SDeess.ASstat.MLarXiv:1806.03185v12018
Deep Evidential Regression
Alexander Amini, Wilko Schwarting, Ava Soleimany +1
cs.LGcs.NEstat.MLarXiv:1910.02600v22019
Deep Learning for Computational Chemistry
Garrett B. Goh, Nathan O. Hodas, Abhinav Vishnu
stat.MLcs.AIcs.CEarXiv:1701.04503v12017
Cross-validation failure: small sample sizes lead to large error bars
Gaël Varoquaux
q-bio.QMstat.MEstat.MLarXiv:1706.07581v12017
Mish: A Self Regularized Non-Monotonic Activation Function
Diganta Misra
cs.LGcs.CVcs.NEarXiv:1908.08681v32019
Picking Winning Tickets Before Training by Preserving Gradient Flow
Chaoqi Wang, Guodong Zhang, Roger Grosse
cs.LGcs.CVstat.MLarXiv:2002.07376v22020
Quantifying Generalization in Reinforcement Learning
Karl Cobbe, Oleg Klimov, Chris Hesse +2
cs.LGstat.MLarXiv:1812.02341v32018
The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs
Han Liu, John Lafferty, Larry Wasserman
stat.MLarXiv:0903.0649v12009
Time Series Data Augmentation for Deep Learning: A Survey
Qingsong Wen, Liang Sun, Fan Yang +4
cs.LGeess.SPstat.MLarXiv:2002.12478v42020
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
Maziar Raissi
stat.MLcs.LGmath.AParXiv:1801.06637v12018
PyOD: A Python Toolbox for Scalable Outlier Detection
Yue Zhao, Zain Nasrullah, Zheng Li
cs.LGcs.IRstat.MLarXiv:1901.01588v22019
Model-Agnostic Interpretability of Machine Learning
Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin
stat.MLcs.LGarXiv:1606.05386v12016
Understanding disentangling in $β$-VAE
Christopher P. Burgess, Irina Higgins, Arka Pal +4
stat.MLcs.AIcs.LGarXiv:1804.03599v12018
Tensor Robust Principal Component Analysis with A New Tensor Nuclear Norm
Canyi Lu, Jiashi Feng, Yudong Chen +3
stat.MLcs.LGarXiv:1804.03728v22018
On Evaluating Adversarial Robustness
Nicholas Carlini, Anish Athalye, Nicolas Papernot +6
cs.LGcs.CRstat.MLarXiv:1902.06705v22019
Recent Advances in Open Set Recognition: A Survey
Chuanxing Geng, Sheng-jun Huang, Songcan Chen
cs.LGstat.MLarXiv:1811.08581v42018
Learning multiple visual domains with residual adapters
Sylvestre-Alvise Rebuffi, Hakan Bilen, Andrea Vedaldi
cs.CVstat.MLarXiv:1705.08045v52017
Geometric Stability: The Missing Axis of Representations
Prashant C. Raju
cs.LGcs.CLq-bio.QMarXiv:2601.09173v52026
Tune: A Research Platform for Distributed Model Selection and Training
Richard Liaw, Eric Liang, Robert Nishihara +3
cs.LGcs.DCstat.MLarXiv:1807.05118v12018
A Minimalist Approach to Offline Reinforcement Learning
Scott Fujimoto, Shixiang Shane Gu
cs.LGcs.AIstat.MLarXiv:2106.06860v22021
Virtual Worlds as Proxy for Multi-Object Tracking Analysis
Adrien Gaidon, Qiao Wang, Yohann Cabon +1
cs.CVcs.LGcs.NEarXiv:1605.06457v12016
The StarCraft Multi-Agent Challenge
Mikayel Samvelyan, Tabish Rashid, Christian Schroeder de Witt +7
cs.LGcs.MAstat.MLarXiv:1902.04043v52019
Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks
Ali Shafahi, W. Ronny Huang, Mahyar Najibi +4
cs.LGcs.CRcs.CVarXiv:1804.00792v22018
LSTM Fully Convolutional Networks for Time Series Classification
Fazle Karim, Somshubra Majumdar, Houshang Darabi +1
cs.LGstat.MLarXiv:1709.05206v12017

Machine Learning (stat)

CREPE: A Convolutional Representation for Pitch Estimation

A Study of BFLOAT16 for Deep Learning Training

FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents

The huge Package for High-dimensional Undirected Graph Estimation in R

Predicting Alzheimer's disease: a neuroimaging study with 3D convolutional neural networks

A Fair Comparison of Graph Neural Networks for Graph Classification

Learning Features by Watching Objects Move

Fine-Tuning Whisper for Automatic Speech Recognition in Baniwa: A Preliminary Study

AI4COVID-19: AI Enabled Preliminary Diagnosis for COVID-19 from Cough Samples via an App

Hidden Stratification Causes Clinically Meaningful Failures in Machine Learning for Medical Imaging

Threats to Federated Learning: A Survey

NVExplain: Explaining Time Series Forecasting with Latent Trajectory Analysis and Structure-Preserving Surrogates

Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges

Representing MAX functions using two-hidden-layer ReLU networks

Training Deep Neural Networks with 8-bit Floating Point Numbers

A Self-Attentive model for Knowledge Tracing

Scale-invariant Optimal Sampling for Rare-events Data with Sparse Models

AtomNet: A Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery

Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet

Ansor: Generating High-Performance Tensor Programs for Deep Learning

Deep learning for neuroimaging: a validation study

The What-If Tool: Interactive Probing of Machine Learning Models

Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation

A review: Deep learning for medical image segmentation using multi-modality fusion

Deep Learning in Medical Image Registration: A Review

Generative and Discriminative Voxel Modeling with Convolutional Neural Networks

Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons

Lagrangian Neural Networks

Deep Reinforcement Learning for Intelligent Transportation Systems: A Survey

Adversarial Risk and the Dangers of Evaluating Against Weak Attacks

Learning the Difference that Makes a Difference with Counterfactually-Augmented Data

Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networks

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

Machine Learning in IoT Security: Current Solutions and Future Challenges

Malware Detection by Eating a Whole EXE

Applied Federated Learning: Improving Google Keyboard Query Suggestions

Wave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source Separation

Deep Evidential Regression

Deep Learning for Computational Chemistry

Cross-validation failure: small sample sizes lead to large error bars

Mish: A Self Regularized Non-Monotonic Activation Function

Picking Winning Tickets Before Training by Preserving Gradient Flow

Quantifying Generalization in Reinforcement Learning

The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs

Time Series Data Augmentation for Deep Learning: A Survey

Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations

PyOD: A Python Toolbox for Scalable Outlier Detection

Model-Agnostic Interpretability of Machine Learning

Understanding disentangling in $β$-VAE

Tensor Robust Principal Component Analysis with A New Tensor Nuclear Norm

On Evaluating Adversarial Robustness

Recent Advances in Open Set Recognition: A Survey

Learning multiple visual domains with residual adapters

Geometric Stability: The Missing Axis of Representations

Tune: A Research Platform for Distributed Model Selection and Training

A Minimalist Approach to Offline Reinforcement Learning

Virtual Worlds as Proxy for Multi-Object Tracking Analysis

The StarCraft Multi-Agent Challenge

Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks

LSTM Fully Convolutional Networks for Time Series Classification