Julien Mairal

papers

13,350

total citations

papers (17)

A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration

NEURIPS 2021arXiv

citations

Lucas-Kanade Reloaded: End-to-End Super-Resolution From Raw Image Bursts

ICCV 2021arXiv

citations

Semi-Supervised Learning Made Simple With Self-Supervised Clustering

CVPR 2023arXiv

citations

Non-Convex Bilevel Games with Critical Point Selection Maps

NEURIPS 2022arXiv

citations

Selecting Relevant Features from a Multi-domain Representation for Few-shot Classification

ECCV 2020arXiv

citations

LUDVIG: Learning-Free Uplifting of 2D Visual Features to Gaussian Splatting Scenes

ICCV 2025arXiv

citations

SLACK: Stable Learning of Augmentations With Cold-Start and KL Regularization

CVPR 2023arXiv

citations

A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding

NEURIPS 2020arXiv

citations

MAP Estimation with Denoisers: Convergence Rates and Guarantees

NEURIPS 2025arXiv

citations

Unsupervised Imaging Inverse Problems with Diffusion Distribution Matching

ICCV 2025arXiv

citations

A New Statistical Model of Star Speckles for Learning to Detect and Characterize Exoplanets in Direct Imaging Observations

CVPR 2025arXiv

citations

Fully Trainable and Interpretable Non-Local Sparse Models for Image Restoration

ECCV 2020arXiv

citations

Beyond Tikhonov: faster learning with self-concordant losses, via iterative regularization

NEURIPS 2021arXiv

citations

GloptiNets: Scalable Non-Convex Optimization with Certificates

NEURIPS 2023arXiv

citations

Julien Mairal

papers (17)

Emerging Properties in Self-Supervised Vision Transformers

Unsupervised Learning of Visual Features by Contrasting Cluster Assignments

Self-Supervised Models Are Continual Learners

A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration

Lucas-Kanade Reloaded: End-to-End Super-Resolution From Raw Image Bursts

Semi-Supervised Learning Made Simple With Self-Supervised Clustering

Non-Convex Bilevel Games with Critical Point Selection Maps

Selecting Relevant Features from a Multi-domain Representation for Few-shot Classification

LUDVIG: Learning-Free Uplifting of 2D Visual Features to Gaussian Splatting Scenes

SLACK: Stable Learning of Augmentations With Cold-Start and KL Regularization

A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding

MAP Estimation with Denoisers: Convergence Rates and Guarantees

Unsupervised Imaging Inverse Problems with Diffusion Distribution Matching

A New Statistical Model of Star Speckles for Learning to Detect and Characterize Exoplanets in Direct Imaging Observations

Fully Trainable and Interpretable Non-Local Sparse Models for Image Restoration

Beyond Tikhonov: faster learning with self-concordant losses, via iterative regularization

GloptiNets: Scalable Non-Convex Optimization with Certificates

papers (17)

Emerging Properties in Self-Supervised Vision Transformers

Unsupervised Learning of Visual Features by Contrasting Cluster Assignments

Self-Supervised Models Are Continual Learners

A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration

Lucas-Kanade Reloaded: End-to-End Super-Resolution From Raw Image Bursts

Semi-Supervised Learning Made Simple With Self-Supervised Clustering

Non-Convex Bilevel Games with Critical Point Selection Maps

Selecting Relevant Features from a Multi-domain Representation for Few-shot Classification

LUDVIG: Learning-Free Uplifting of 2D Visual Features to Gaussian Splatting Scenes

SLACK: Stable Learning of Augmentations With Cold-Start and KL Regularization

A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding

MAP Estimation with Denoisers: Convergence Rates and Guarantees

Unsupervised Imaging Inverse Problems with Diffusion Distribution Matching

A New Statistical Model of Star Speckles for Learning to Detect and Characterize Exoplanets in Direct Imaging Observations

Fully Trainable and Interpretable Non-Local Sparse Models for Image Restoration

Beyond Tikhonov: faster learning with self-concordant losses, via iterative regularization

GloptiNets: Scalable Non-Convex Optimization with Certificates