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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6,661 to 6,720 of 6,785

DreamFusion: Text-to-3D using 2D Diffusion
Ben Poole, Ajay Jain, Jonathan T. Barron +1
cs.CVcs.LGstat.MLarXiv:2209.14988v12022
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings
Tolga Bolukbasi, Kai-Wei Chang, James Zou +2
cs.CLcs.AIcs.LGarXiv:1607.06520v12016
Stability-Aware Feature Design for Robust Watermark Detection in Machine-Generated Text
Sina Mansouri, Mohit Marvania, Abolfazl Safikhani
cs.CLcs.LGstat.MLarXiv:2608.18102v12026
Self-Attention Generative Adversarial Networks
Han Zhang, Ian Goodfellow, Dimitris Metaxas +1
stat.MLcs.LGarXiv:1805.08318v22018
Recurrent Models of Visual Attention
Volodymyr Mnih, Nicolas Heess, Alex Graves +1
cs.LGcs.CVstat.MLarXiv:1406.6247v12014
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
Daniel S. Park, William Chan, Yu Zhang +4
eess.AScs.CLcs.LGarXiv:1904.08779v32019
Graph Convolutional Neural Networks for Web-Scale Recommender Systems
Rex Ying, Ruining He, Kaifeng Chen +3
cs.IRcs.LGstat.MLarXiv:1806.01973v12018
Wide & Deep Learning for Recommender Systems
Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen +13
cs.LGcs.IRstat.MLarXiv:1606.07792v12016
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators
Lu Lu, Pengzhan Jin, George Em Karniadakis
cs.LGstat.MLarXiv:1910.03193v32019
FiLM: Visual Reasoning with a General Conditioning Layer
Ethan Perez, Florian Strub, Harm de Vries +2
cs.CVcs.AIcs.CLarXiv:1709.07871v22017
Scalability in Perception for Autonomous Driving: Waymo Open Dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla +22
cs.CVcs.LGstat.MLarXiv:1912.04838v72019
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
Stephane Ross, Geoffrey J. Gordon, J. Andrew Bagnell
cs.LGcs.AIstat.MLarXiv:1011.0686v32010
Markerless tracking of user-defined features with deep learning
Alexander Mathis, Pranav Mamidanna, Taiga Abe +4
cs.CVq-bio.NCq-bio.QMarXiv:1804.03142v12018
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context
Zihang Dai, Zhilin Yang, Yiming Yang +3
cs.LGcs.CLstat.MLarXiv:1901.02860v32019
Knowledge Distillation: A Survey
Jianping Gou, Baosheng Yu, Stephen John Maybank +1
cs.LGstat.MLarXiv:2006.05525v72020
Density estimation using Real NVP
Laurent Dinh, Jascha Sohl-Dickstein, Samy Bengio
cs.LGcs.AIcs.NEarXiv:1605.08803v32016
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
Xi Chen, Yan Duan, Rein Houthooft +3
cs.LGstat.MLarXiv:1606.03657v12016
The Mythos of Model Interpretability
Zachary C. Lipton
cs.LGcs.AIcs.CVarXiv:1606.03490v32016
EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces
Vernon J. Lawhern, Amelia J. Solon, Nicholas R. Waytowich +3
cs.LGq-bio.NCstat.MLarXiv:1611.08024v42016
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
Dan Hendrycks, Thomas Dietterich
cs.LGcs.CVstat.MLarXiv:1903.12261v12019
PointPillars: Fast Encoders for Object Detection from Point Clouds
Alex H. Lang, Sourabh Vora, Holger Caesar +3
cs.LGcs.CVstat.MLarXiv:1812.05784v22018
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
Kihyuk Sohn, David Berthelot, Chun-Liang Li +6
cs.LGcs.CVstat.MLarXiv:2001.07685v22020
iCaRL: Incremental Classifier and Representation Learning
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl +1
cs.CVcs.LGstat.MLarXiv:1611.07725v22016
Variational Inference with Normalizing Flows
Danilo Jimenez Rezende, Shakir Mohamed
stat.MLcs.AIcs.LGarXiv:1505.05770v62015
Spectral Normalization for Generative Adversarial Networks
Takeru Miyato, Toshiki Kataoka, Masanori Koyama +1
cs.LGcs.CVstat.MLarXiv:1802.05957v12018
Wasserstein GAN
Martin Arjovsky, Soumith Chintala, Léon Bottou
stat.MLcs.LGarXiv:1701.07875v32017
Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting
Bing Yu, Haoteng Yin, Zhanxing Zhu
cs.LGstat.MLarXiv:1709.04875v42017
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez, Been Kim
stat.MLcs.AIcs.LGarXiv:1702.08608v22017
Fast Graph Representation Learning with PyTorch Geometric
Matthias Fey, Jan Eric Lenssen
cs.LGstat.MLarXiv:1903.02428v32019
MissForest - nonparametric missing value imputation for mixed-type data
Daniel J. Stekhoven, Peter Bühlmann
stat.APstat.MLarXiv:1105.0828v22011
Flow Matching for Generative Modeling
Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu +2
cs.LGcs.AIstat.MLarXiv:2210.02747v22022
A Comprehensive Survey on Transfer Learning
Fuzhen Zhuang, Zhiyuan Qi, Keyu Duan +5
cs.LGstat.MLarXiv:1911.02685v32019
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances
Marco Cuturi
stat.MLarXiv:1306.0895v12013
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
Wenzhe Shi, Jose Caballero, Ferenc Huszár +5
cs.CVstat.MLarXiv:1609.05158v22016
Improved Denoising Diffusion Probabilistic Models
Alex Nichol, Prafulla Dhariwal
cs.LGcs.AIstat.MLarXiv:2102.09672v12021
Deep reinforcement learning from human preferences
Paul Christiano, Jan Leike, Tom B. Brown +3
stat.MLcs.AIcs.HCarXiv:1706.03741v42017
Learning without Forgetting
Zhizhong Li, Derek Hoiem
cs.CVcs.LGstat.MLarXiv:1606.09282v32016
Modeling Relational Data with Graph Convolutional Networks
Michael Schlichtkrull, Thomas N. Kipf, Peter Bloem +3
stat.MLcs.AIcs.DBarXiv:1703.06103v42017
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Andrew Brock, Jeff Donahue, Karen Simonyan
cs.LGstat.MLarXiv:1809.11096v22018
Learning Transferable Architectures for Scalable Image Recognition
Barret Zoph, Vijay Vasudevan, Jonathon Shlens +1
cs.CVcs.LGstat.MLarXiv:1707.07012v42017
Federated Learning: Challenges, Methods, and Future Directions
Tian Li, Anit Kumar Sahu, Ameet Talwalkar +1
cs.LGcs.DCstat.MLarXiv:1908.07873v12019
Categorical Reparameterization with Gumbel-Softmax
Eric Jang, Shixiang Gu, Ben Poole
stat.MLcs.LGarXiv:1611.01144v52016
BPR: Bayesian Personalized Ranking from Implicit Feedback
Steffen Rendle, Christoph Freudenthaler, Zeno Gantner +1
cs.IRcs.LGstat.MLarXiv:1205.2618v12012
Analyzing and Improving the Image Quality of StyleGAN
Tero Karras, Samuli Laine, Miika Aittala +3
cs.CVcs.LGcs.NEarXiv:1912.04958v22019
Addressing Function Approximation Error in Actor-Critic Methods
Scott Fujimoto, Herke van Hoof, David Meger
cs.AIcs.LGstat.MLarXiv:1802.09477v32018
Neural Ordinary Differential Equations
Ricky T. Q. Chen, Yulia Rubanova, Jesse Bettencourt +1
cs.LGcs.AIstat.MLarXiv:1806.07366v52018
On the Properties of Neural Machine Translation: Encoder-Decoder Approaches
Kyunghyun Cho, Bart van Merrienboer, Dzmitry Bahdanau +1
cs.CLstat.MLarXiv:1409.1259v22014
Advances and Open Problems in Federated Learning
Peter Kairouz, H. Brendan McMahan, Brendan Avent +56
cs.LGcs.CRstat.MLarXiv:1912.04977v32019
Matching Networks for One Shot Learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap +2
cs.LGstat.MLarXiv:1606.04080v22016
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Tero Karras, Timo Aila, Samuli Laine +1
cs.NEcs.LGstat.MLarXiv:1710.10196v32017
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
Michaël Defferrard, Xavier Bresson, Pierre Vandergheynst
cs.LGstat.MLarXiv:1606.09375v32016
Causal Discovery in Equal Variance Linear Gaussian DAGs via SURE-Tuned Ridge Regression
Sambit Mishra, Urbashi Mitra
cs.LGeess.SPstat.MLarXiv:2608.17132v12026
Diagonal Multi-omics Integration of Heterogenous Datasets
Maksim V. Kukushkin, Mikhail S. Arbatskiy, Dmitriy E. Balandin +1
stat.MLcs.LGmath.FAarXiv:2608.16968v12026
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh +1
cs.CVcs.LGeess.IVarXiv:1807.10165v12018
Where A Small Language Model Helps in Invoice Categorisation, Understood Through Embedding Geometry
Emma Ceccherini, Daniel Lawson, Anjulika Salhan
stat.MLcs.LGarXiv:2608.18033v12026
Improved Training of Wasserstein GANs
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky +2
cs.LGstat.MLarXiv:1704.00028v32017
Nonlocal Transition Kernel for Efficient Learning of Restricted Boltzmann Machines
Kaiji Sekimoto, Muneki Yasuda
stat.MLcond-mat.dis-nncs.LGarXiv:2608.17450v12026
Prototypical Networks for Few-shot Learning
Jake Snell, Kevin Swersky, Richard S. Zemel
cs.LGstat.MLarXiv:1703.05175v22017
Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz +11
cs.LGcs.AIstat.MLarXiv:1612.00796v22016
Score-Based Generative Modeling through Stochastic Differential Equations
Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma +3
cs.LGstat.MLarXiv:2011.13456v22020

Machine Learning (stat)

DreamFusion: Text-to-3D using 2D Diffusion

Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings

Stability-Aware Feature Design for Robust Watermark Detection in Machine-Generated Text

Self-Attention Generative Adversarial Networks

Recurrent Models of Visual Attention

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

Graph Convolutional Neural Networks for Web-Scale Recommender Systems

Wide & Deep Learning for Recommender Systems

DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators

FiLM: Visual Reasoning with a General Conditioning Layer

Scalability in Perception for Autonomous Driving: Waymo Open Dataset

A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning

Markerless tracking of user-defined features with deep learning

Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

Knowledge Distillation: A Survey

Density estimation using Real NVP

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

The Mythos of Model Interpretability

EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces

Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

PointPillars: Fast Encoders for Object Detection from Point Clouds

FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence

iCaRL: Incremental Classifier and Representation Learning

Variational Inference with Normalizing Flows

Spectral Normalization for Generative Adversarial Networks

Wasserstein GAN

Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting

Towards A Rigorous Science of Interpretable Machine Learning

Fast Graph Representation Learning with PyTorch Geometric

MissForest - nonparametric missing value imputation for mixed-type data

Flow Matching for Generative Modeling

A Comprehensive Survey on Transfer Learning

Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

Improved Denoising Diffusion Probabilistic Models

Deep reinforcement learning from human preferences

Learning without Forgetting

Modeling Relational Data with Graph Convolutional Networks

Large Scale GAN Training for High Fidelity Natural Image Synthesis

Learning Transferable Architectures for Scalable Image Recognition

Federated Learning: Challenges, Methods, and Future Directions

Categorical Reparameterization with Gumbel-Softmax

BPR: Bayesian Personalized Ranking from Implicit Feedback

Analyzing and Improving the Image Quality of StyleGAN

Addressing Function Approximation Error in Actor-Critic Methods

Neural Ordinary Differential Equations

On the Properties of Neural Machine Translation: Encoder-Decoder Approaches

Advances and Open Problems in Federated Learning

Matching Networks for One Shot Learning

Progressive Growing of GANs for Improved Quality, Stability, and Variation

Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

Causal Discovery in Equal Variance Linear Gaussian DAGs via SURE-Tuned Ridge Regression

Diagonal Multi-omics Integration of Heterogenous Datasets

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

Where A Small Language Model Helps in Invoice Categorisation, Understood Through Embedding Geometry

Improved Training of Wasserstein GANs

Nonlocal Transition Kernel for Efficient Learning of Restricted Boltzmann Machines

Prototypical Networks for Few-shot Learning

Overcoming catastrophic forgetting in neural networks

Score-Based Generative Modeling through Stochastic Differential Equations