Fast and Efficient Dense Variational Stereo on GPU. - Julien Mairal; Renaud Keriven; Alexandre Chariot (3DPVT, 2006)

Multiscale Sparse Image Representationwith Learned Dictionaries. - Julien Mairal; Guillermo Sapiro; Michael Elad (ICIP (3), 2007)

Discriminative learned dictionaries for local image analysis. - Julien Mairal; Francis R. Bach; Jean Ponce; Guillermo Sapiro; Andrew Zisserman (CVPR, 2008)

Discriminative Sparse Image Models for Class-Specific Edge Detection and Image Interpretation. - Julien Mairal; Marius Leordeanu; Francis R. Bach; Martial Hebert; Jean Ponce (ECCV (3), 2008)

Supervised Dictionary Learning. - Julien Mairal; Francis R. Bach; Jean Ponce; Guillermo Sapiro; Andrew Zisserman (NIPS, 2008)

Convex Sparse Matrix Factorizations - Francis R. Bach; Julien Mairal; Jean Ponce (CoRR, 2008)

Learning Multiscale Sparse Representations for Image and Video Restoration. - Julien Mairal; Guillermo Sapiro; Michael Elad (Multiscale Model. Simul., 2008)

Sparse Representation for Color Image Restoration. - Julien Mairal; Michael Elad; Guillermo Sapiro (IEEE Trans. Image Process., 2008)

Non-local sparse models for image restoration. - Julien Mairal; Francis R. Bach; Jean Ponce; Guillermo Sapiro; Andrew Zisserman (ICCV, 2009)

Online dictionary learning for sparse coding. - Julien Mairal; Francis R. Bach; Jean Ponce; Guillermo Sapiro (ICML, 2009)

Proximal Methods for Sparse Hierarchical Dictionary Learning. - Rodolphe Jenatton; Julien Mairal; Guillaume Obozinski; Francis R. Bach (ICML, 2010)

Network Flow Algorithms for Structured Sparsity. - Julien Mairal; Rodolphe Jenatton; Guillaume Obozinski; Francis R. Bach (NIPS, 2010)

Online Learning for Matrix Factorization and Sparse Coding. - Julien Mairal; Francis R. Bach; Jean Ponce; Guillermo Sapiro (J. Mach. Learn. Res., 2010)

Sparse Representation for Computer Vision and Pattern Recognition. - John Wright 001; Yi Ma 001; Julien Mairal; Guillermo Sapiro; Thomas S. Huang; Shuicheng Yan (Proc. IEEE, 2010)

Sparse image representation with epitomes. - Louise Benoît; Julien Mairal; Francis R. Bach; Jean Ponce (CVPR, 2011)

Structured sparsity through convex optimization - Francis R. Bach; Rodolphe Jenatton; Julien Mairal; Guillaume Obozinski (CoRR, 2011)

Dictionary Learning for Deblurring and Digital Zoom - Florent Couzinie-Devy; Julien Mairal; Francis R. Bach; Jean Ponce (CoRR, 2011)

Learning Hierarchical and Topographic Dictionaries with Structured Sparsity - Julien Mairal; Rodolphe Jenatton; Guillaume Obozinski; Francis R. Bach (CoRR, 2011)

Proximal Methods for Hierarchical Sparse Coding. - Rodolphe Jenatton; Julien Mairal; Guillaume Obozinski; Francis R. Bach (J. Mach. Learn. Res., 2011)

Convex and Network Flow Optimization for Structured Sparsity. - Julien Mairal; Rodolphe Jenatton; Guillaume Obozinski; Francis R. Bach (J. Mach. Learn. Res., 2011)

Complexity Analysis of the Lasso Regularization Path. - Julien Mairal; Bin Yu 001 (ICML, 2012)

Optimization with Sparsity-Inducing Penalties. - Francis R. Bach; Rodolphe Jenatton; Julien Mairal; Guillaume Obozinski (Found. Trends Mach. Learn., 2012)

Task-Driven Dictionary Learning. - Julien Mairal; Francis R. Bach; Jean Ponce (IEEE Trans. Pattern Anal. Mach. Intell., 2012)

Structured Penalties for Log-Linear Language Models. - Anil Kumar Nelakanti; Cédric Archambeau; Julien Mairal; Francis R. Bach; Guillaume Bouchard (EMNLP, 2013)

Optimization with First-Order Surrogate Functions. - Julien Mairal (ICML (3), 2013)

Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization. - Julien Mairal (NIPS, 2013)

Stochastic Majorization-Minimization Optimization with First-Order Surrogate Functions. - Julien Mairal (CoRR, 2013)

Supervised feature selection in graphs with path coding penalties and network flows. - Julien Mairal; Bin Yu 001 (J. Mach. Learn. Res., 2013)

Fast and Robust Archetypal Analysis for Representation Learning. - Yuansi Chen; Julien Mairal; Zaïd Harchaoui (CVPR, 2014)

Mixing Body-Part Sequences for Human Pose Estimation. - Anoop Cherian; Julien Mairal; Karteek Alahari; Cordelia Schmid (CVPR, 2014)

On learning to localize objects with minimal supervision. - Hyun Oh Song; Ross B. Girshick; Stefanie Jegelka; Julien Mairal; Zaïd Harchaoui; Trevor Darrell (ICML, 2014)

Convolutional Kernel Networks. - Julien Mairal; Piotr Koniusz; Zaïd Harchaoui; Cordelia Schmid (NIPS, 2014)

Efficient RNA isoform identification and quantification from RNA-Seq data with network flows. - Elsa Bernard; Laurent Jacob; Julien Mairal; Jean-Philippe Vert (Bioinform., 2014)

One-Bit Object Detection: On learning to localize objects with minimal supervision. - Hyun Oh Song; Ross B. Girshick; Stefanie Jegelka; Julien Mairal; Zaïd Harchaoui; Trevor Darrell (CoRR, 2014)

Sparse Modeling for Image and Vision Processing. - Julien Mairal; Francis R. Bach; Jean Ponce (Found. Trends Comput. Graph. Vis., 2014)

Local Convolutional Features with Unsupervised Training for Image Retrieval. - Mattis Paulin; Matthijs Douze; Zaïd Harchaoui; Julien Mairal; Florent Perronnin; Cordelia Schmid (ICCV, 2015)

A Universal Catalyst for First-Order Optimization. - Hongzhou Lin; Julien Mairal; Zaïd Harchaoui (NIPS, 2015)

A convex formulation for joint RNA isoform detection and quantification from multiple RNA-seq samples. - Elsa Bernard; Laurent Jacob; Julien Mairal; Eric Viara; Jean-Philippe Vert (BMC Bioinform., 2015)

Guest Editorial: Sparse Coding. - Julien Mairal; Michael Elad; Francis R. Bach (Int. J. Comput. Vis., 2015)

Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning. - Julien Mairal (SIAM J. Optim., 2015)

Dictionary learning from phaseless measurements. - Andreas M. Tillmann; Yonina C. Eldar; Julien Mairal (ICASSP, 2016)

Dictionary Learning for Massive Matrix Factorization. - Arthur Mensch; Julien Mairal; Bertrand Thirion; Gaël Varoquaux (ICML, 2016)

End-to-End Kernel Learning with Supervised Convolutional Kernel Networks. - Julien Mairal (NIPS, 2016)

DOLPHIn - Dictionary Learning for Phase Retrieval. - Andreas M. Tillmann; Yonina C. Eldar; Julien Mairal (IEEE Trans. Signal Process., 2016)

Large-Scale Machine Learning and Applications. (Apprentissage à grande échelle et applications). - Julien Mairal (2017)

BlitzNet: A Real-Time Deep Network for Scene Understanding. - Nikita Dvornik; Konstantin Shmelkov; Julien Mairal; Cordelia Schmid (ICCV, 2017)

Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum Structure. - Alberto Bietti; Julien Mairal (NIPS, 2017)

Invariance and Stability of Deep Convolutional Representations. - Alberto Bietti; Julien Mairal (NIPS, 2017)

Learning Neural Representations of Human Cognition across Many fMRI Studies. - Arthur Mensch; Julien Mairal; Danilo Bzdok; Bertrand Thirion; Gaël Varoquaux (NIPS, 2017)

Group Invariance and Stability to Deformations of Deep Convolutional Representations. - Alberto Bietti; Julien Mairal (CoRR, 2017)

Subsampling Enables Fast Factorisation of Huge Matrices into Sparse Signals. - Arthur Mensch; Julien Mairal; Bertrand Thirion; Gaël Varoquaux (ERCIM News, 2017)

Convolutional Patch Representations for Image Retrieval: An Unsupervised Approach. - Mattis Paulin; Julien Mairal; Matthijs Douze; Zaïd Harchaoui; Florent Perronnin; Cordelia Schmid (Int. J. Comput. Vis., 2017)

Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice. - Hongzhou Lin; Julien Mairal; Zaïd Harchaoui (J. Mach. Learn. Res., 2017)

Catalyst for Gradient-based Nonconvex Optimization. - Courtney Paquette; Hongzhou Lin; Dmitriy Drusvyatskiy; Julien Mairal; Zaïd Harchaoui (AISTATS, 2018)

Modeling Visual Context Is Key to Augmenting Object Detection Datasets. - Nikita Dvornik; Julien Mairal; Cordelia Schmid (ECCV (12), 2018)

Unsupervised Learning of Artistic Styles with Archetypal Style Analysis. - Daan Wynen; Cordelia Schmid; Julien Mairal (NeurIPS, 2018)

Extracting Universal Representations of Cognition across Brain-Imaging Studies. - Arthur Mensch; Julien Mairal; Bertrand Thirion; Gaël Varoquaux (CoRR, 2018)

On Regularization and Robustness of Deep Neural Networks. - Alberto Bietti; Grégoire Mialon; Julien Mairal (CoRR, 2018)

Stochastic Subsampling for Factorizing Huge Matrices. - Arthur Mensch; Julien Mairal; Bertrand Thirion; Gaël Varoquaux (IEEE Trans. Signal Process., 2018)

Unsupervised Pre-Training of Image Features on Non-Curated Data. - Mathilde Caron; Piotr Bojanowski; Julien Mairal; Armand Joulin (ICCV, 2019)

Diversity With Cooperation: Ensemble Methods for Few-Shot Classification. - Nikita Dvornik; Julien Mairal; Cordelia Schmid (ICCV, 2019)

A Kernel Perspective for Regularizing Deep Neural Networks. - Alberto Bietti; Grégoire Mialon; Dexiong Chen; Julien Mairal (ICML, 2019)

Estimate Sequences for Variance-Reduced Stochastic Composite Optimization. - Andrei Kulunchakov; Julien Mairal (ICML, 2019)

On the Inductive Bias of Neural Tangent Kernels. - Alberto Bietti; Julien Mairal (NeurIPS, 2019)

Recurrent Kernel Networks. - Dexiong Chen; Laurent Jacob; Julien Mairal (NeurIPS, 2019)

A Generic Acceleration Framework for Stochastic Composite Optimization. - Andrei Kulunchakov; Julien Mairal (NeurIPS, 2019)

Biological sequence modeling with convolutional kernel networks. - Dexiong Chen; Laurent Jacob; Julien Mairal (Bioinform., 2019)

Leveraging Large-Scale Uncurated Data for Unsupervised Pre-training of Visual Features. - Mathilde Caron; Piotr Bojanowski; Julien Mairal; Armand Joulin (CoRR, 2019)

Revisiting Non Local Sparse Models for Image Restoration. - Bruno Lecouat; Jean Ponce; Julien Mairal (CoRR, 2019)

Screening Data Points in Empirical Risk Minimization via Ellipsoidal Regions and Safe Loss Function. - Grégoire Mialon; Alexandre d'Aspremont; Julien Mairal (CoRR, 2019)

Cyanure: An Open-Source Toolbox for Empirical Risk Minimization for Python, C++, and soon more. - Julien Mairal (CoRR, 2019)

Group Invariance, Stability to Deformations, and Complexity of Deep Convolutional Representations. - Alberto Bietti; Julien Mairal (J. Mach. Learn. Res., 2019)

An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration. - Hongzhou Lin; Julien Mairal; Zaïd Harchaoui (SIAM J. Optim., 2019)

Screening Data Points in Empirical Risk Minimization via Ellipsoidal Regions and Safe Loss Functions. - Grégoire Mialon; Julien Mairal; Alexandre d'Aspremont (AISTATS, 2020)

Selecting Relevant Features from a Multi-domain Representation for Few-Shot Classification. - Nikita Dvornik; Cordelia Schmid; Julien Mairal (ECCV (10), 2020)

Fully Trainable and Interpretable Non-local Sparse Models for Image Restoration. - Bruno Lecouat; Jean Ponce; Julien Mairal (ECCV (22), 2020)

Convolutional Kernel Networks for Graph-Structured Data. - Dexiong Chen; Laurent Jacob; Julien Mairal (ICML, 2020)

Unsupervised Learning of Visual Features by Contrasting Cluster Assignments. - Mathilde Caron; Ishan Misra; Julien Mairal; Priya Goyal; Piotr Bojanowski; Armand Joulin (NeurIPS, 2020)

A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding. - Bruno Lecouat; Jean Ponce; Julien Mairal (NeurIPS, 2020)

Pruning Convolutional Neural Networks with Self-Supervision. - Mathilde Caron; Ari Morcos; Piotr Bojanowski; Julien Mairal; Armand Joulin (CoRR, 2020)

Selecting Relevant Features from a Universal Representation for Few-shot Classification. - Nikita Dvornik; Cordelia Schmid; Julien Mairal (CoRR, 2020)

Optimization Approaches for Counterfactual Risk Minimization with Continuous Actions. - Houssam Zenati; Alberto Bietti; Matthieu Martin; Eustache Diemert; Julien Mairal (CoRR, 2020)

An Optimal Transport Kernel for Feature Aggregation and its Relationship to Attention. - Grégoire Mialon; Dexiong Chen; Alexandre d'Aspremont; Julien Mairal (CoRR, 2020)

Designing and Learning Trainable Priors with Non-Cooperative Games. - Bruno Lecouat; Jean Ponce; Julien Mairal (CoRR, 2020)

Estimate Sequences for Stochastic Composite Optimization: Variance Reduction, Acceleration, and Robustness to Noise. - Andrei Kulunchakov; Julien Mairal (J. Mach. Learn. Res., 2020)

Emerging Properties in Self-Supervised Vision Transformers. - Mathilde Caron; Hugo Touvron; Ishan Misra; Hervé Jégou; Julien Mairal; Piotr Bojanowski; Armand Joulin (ICCV, 2021)

Lucas-Kanade Reloaded: End-to-End Super-Resolution from Raw Image Bursts. - Bruno Lecouat; Jean Ponce; Julien Mairal (ICCV, 2021)

A Trainable Optimal Transport Embedding for Feature Aggregation and its Relationship to Attention. - Grégoire Mialon; Dexiong Chen; Alexandre d'Aspremont; Julien Mairal (ICLR, 2021)

Beyond Tikhonov: faster learning with self-concordant losses, via iterative regularization. - Gaspard Beugnot; Julien Mairal; Alessandro Rudi (NeurIPS, 2021)

A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration. - Théo Bodrito; Alexandre Zouaoui; Jocelyn Chanussot; Julien Mairal (NeurIPS, 2021)

Aliasing is your Ally: End-to-End Super-Resolution from Raw Image Bursts. - Bruno Lecouat; Jean Ponce; Julien Mairal (CoRR, 2021)

NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results. - Goutam Bhat; Martin Danelljan; Radu Timofte; Kazutoshi Akita; Wooyeong Cho; Haoqiang Fan; Lanpeng Jia; Daeshik Kim; Bruno Lecouat; Youwei Li; Shuaicheng Liu; Ziluan Liu; et al. (CoRR, 2021)

GraphiT: Encoding Graph Structure in Transformers. - Grégoire Mialon; Dexiong Chen; Margot Selosse; Julien Mairal (CoRR, 2021)

Residual Reinforcement Learning from Demonstrations. - Minttu Alakuijala; Gabriel Dulac-Arnold; Julien Mairal; Jean Ponce; Cordelia Schmid (CoRR, 2021)

On the Importance of Visual Context for Data Augmentation in Scene Understanding. - Nikita Dvornik; Julien Mairal; Cordelia Schmid (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Extracting representations of cognition across neuroimaging studies improves brain decoding. - Arthur Mensch; Julien Mairal; Bertrand Thirion; Gaël Varoquaux (PLoS Comput. Biol., 2021)

Efficient Kernelized UCB for Contextual Bandits. - Houssam Zenati; Alberto Bietti; Eustache Diemert; Julien Mairal; Matthieu Martin; Pierre Gaillard (AISTATS, 2022)

On the Benefits of Large Learning Rates for Kernel Methods. - Gaspard Beugnot; Julien Mairal; Alessandro Rudi (COLT, 2022)

Self-Supervised Models are Continual Learners. - Enrico Fini; Victor G. Turrisi da Costa; Xavier Alameda-Pineda; Elisa Ricci 001; Karteek Alahari; Julien Mairal (CVPR, 2022)

Amortized Implicit Differentiation for Stochastic Bilevel Optimization. - Michael Arbel; Julien Mairal (ICLR, 2022)

The Spectral Bias of Polynomial Neural Networks. - Moulik Choraria; Leello Tadesse Dadi; Grigorios Chrysos 002; Julien Mairal; Volkan Cevher (ICLR, 2022)

Self Supervised Learning for Few Shot Hyperspectral Image Classification. - Nassim Ait Ali Braham; Lichao Mou; Jocelyn Chanussot; Julien Mairal; Xiao Xiang Zhu 001 (IGARSS, 2022)

Non-Convex Bilevel Games with Critical Point Selection Maps. - Michael Arbel; Julien Mairal (NeurIPS, 2022)

Efficient Kernel UCB for Contextual Bandits. - Houssam Zenati; Alberto Bietti; Eustache Diemert; Julien Mairal; Matthieu Martin; Pierre Gaillard (CoRR, 2022)

High dynamic range and super-resolution from raw image bursts. - Bruno Lecouat; Thomas Eboli; Jean Ponce; Julien Mairal (ACM Trans. Graph., 2022)

Semi-supervised learning made simple with self-supervised clustering. - Enrico Fini; Pietro Astolfi; Karteek Alahari; Xavier Alameda-Pineda; Julien Mairal; Moin Nabi; Elisa Ricci 001 (CVPR, 2023)

SLACK: Stable Learning of Augmentations with Cold-Start and KL Regularization. - Juliette Marrie; Michael Arbel; Diane Larlus; Julien Mairal (CVPR, 2023)

Combining Multi-Spectral Data With Statistical and Deep-Learning Models for Improved Exoplanet Detection in Direct Imaging at High Contrast. - Olivier Flasseur; Théo Bodrito; Julien Mairal; Jean Ponce; Maud Langlois; Anne-Marie Lagrange (EUSIPCO, 2023)

Sequential Counterfactual Risk Minimization. - Houssam Zenati; Eustache Diemert; Matthieu Martin; Julien Mairal; Pierre Gaillard (ICML, 2023)

Learning Reward Functions for Robotic Manipulation by Observing Humans. - Minttu Alakuijala; Gabriel Dulac-Arnold; Julien Mairal; Jean Ponce; Cordelia Schmid (ICRA, 2023)

Hysupp: An Open-Source Hyperspectral Unmixing Python Package. - Behnood Rasti; Alexandre Zouaoui; Julien Mairal; Jocelyn Chanussot (IGARSS, 2023)

GloptiNets: Scalable Non-Convex Optimization with Certificates. - Gaspard Beugnot; Julien Mairal; Alessandro Rudi (NeurIPS, 2023)

Towards Real-World Focus Stacking with Deep Learning. - Alexandre Araujo; Jean Ponce; Julien Mairal (CoRR, 2023)

Fine Dense Alignment of Image Bursts through Camera Pose and Depth Estimation. - Bruno Lecouat; Yann Dubois de Mont-Marin; Théo Bodrito; Julien Mairal; Jean Ponce (CoRR, 2023)

SUnAA: Sparse Unmixing Using Archetypal Analysis. - Behnood Rasti; Alexandre Zouaoui; Julien Mairal; Jocelyn Chanussot (IEEE Geosci. Remote. Sens. Lett., 2023)

Entropic Descent Archetypal Analysis for Blind Hyperspectral Unmixing. - Alexandre Zouaoui; Gedeon Muhawenayo; Behnood Rasti; Jocelyn Chanussot; Julien Mairal (IEEE Trans. Image Process., 2023)

Self-Attention in Colors: Another Take on Encoding Graph Structure in Transformers. - Romain Menegaux; Emmanuel Jehanno; Margot Selosse; Julien Mairal (Trans. Mach. Learn. Res., 2023)

Vision Transformers Need Registers. - Timothée Darcet; Maxime Oquab; Julien Mairal; Piotr Bojanowski (ICLR, 2024)

Functional Bilevel Optimization for Machine Learning. - Ieva Petrulionyte; Julien Mairal; Michael Arbel (NeurIPS, 2024)

Fast Semi-supervised Unmixing using Non-convex Optimization. - Behnood Rasti; Alexandre Zouaoui; Julien Mairal; Jocelyn Chanussot (CoRR, 2024)

On Good Practices for Task-Specific Distillation of Large Pretrained Models. - Juliette Marrie; Michael Arbel; Julien Mairal; Diane Larlus (CoRR, 2024)

MODEL&CO: Exoplanet detection in angular differential imaging by learning across multiple observations. - Théo Bodrito; Olivier Flasseur; Julien Mairal; Jean Ponce; Maud Langlois; Anne-Marie Lagrange (CoRR, 2024)

LUDVIG: Learning-free Uplifting of 2D Visual features to Gaussian Splatting scenes. - Juliette Marrie; Romain Menegaux; Michael Arbel; Diane Larlus; Julien Mairal (CoRR, 2024)

Enhancing Contrastive Learning With Positive Pair Mining for Few-Shot Hyperspectral Image Classification. - Nassim Ait Ali Braham; Julien Mairal; Jocelyn Chanussot; Lichao Mou; Xiao Xiang Zhu 001 (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024)

Image Processing and Machine Learning for Hyperspectral Unmixing: An Overview and the HySUPP Python Package. - Behnood Rasti; Alexandre Zouaoui; Julien Mairal; Jocelyn Chanussot (IEEE Trans. Geosci. Remote. Sens., 2024)

Fast Semisupervised Unmixing Using Nonconvex Optimization. - Behnood Rasti; Alexandre Zouaoui; Julien Mairal; Jocelyn Chanussot (IEEE Trans. Geosci. Remote. Sens., 2024)

On Good Practices for Task-Specific Distillation of Large Pretrained Visual Models. - Juliette Marrie; Michael Arbel; Julien Mairal; Diane Larlus (Trans. Mach. Learn. Res., 2024)

DINOv2: Learning Robust Visual Features without Supervision. - Maxime Oquab; Timothée Darcet; Théo Moutakanni; Huy V. Vo; Marc Szafraniec; Vasil Khalidov; Pierre Fernandez; Daniel Haziza; Francisco Massa; Alaaeldin El-Nouby; Mido Assran; Nicolas Ballas; et al. (Trans. Mach. Learn. Res., 2024)

A New Statistical Model of Star Speckles for Learning to Detect and Characterize Exoplanets in Direct Imaging Observations. - Théo Bodrito; Olivier Flasseur; Julien Mairal; Jean Ponce; Maud Langlois; Anne-Marie Lagrange (CVPR, 2025)

SpectralEarth: Training Hyperspectral Foundation Models at Scale. - Nassim Ait Ali Braham; Conrad M. Albrecht; Julien Mairal; Jocelyn Chanussot; Yi Wang 072; Xiao Xiang Zhu 001 (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025)

Cluster and Predict Latents Patches for Improved Masked Image Modeling. - Timothée Darcet; Federico Baldassarre; Maxime Oquab; Julien Mairal; Piotr Bojanowski (Trans. Mach. Learn. Res., 2025)

Counterfactual Learning of Stochastic Policies with Continuous Actions. - Houssam Zenati; Alberto Bietti; Matthieu Martin; Eustache Diemert; Pierre Gaillard; Julien Mairal (Trans. Mach. Learn. Res., 2025)

Cluster and Predict Latent Patches for Improved Masked Image Modeling. - Timothée Darcet; Federico Baldassarre; Maxime Oquab; Julien Mairal; Piotr Bojanowski (CoRR, 2025)

MicroFlow: Domain-Specific Optical Flow for Ground Deformation Estimation in Seismic Events. - Juliette Bertrand; Sophie Giffard-Roisin; James Hollingsworth; Julien Mairal (CoRR, 2025)

Unsupervised Imaging Inverse Problems with Diffusion Distribution Matching. - Giacomo Meanti; Thomas Ryckeboer; Michael Arbel; Julien Mairal (CoRR, 2025)

MAP Estimation with Denoisers: Convergence Rates and Guarantees. - Scott Pesme; Giacomo Meanti; Michael Arbel; Julien Mairal (CoRR, 2025)

DINOv3. - Oriane Siméoni; Huy V. Vo; Maximilian Seitzer; Federico Baldassarre; Maxime Oquab; Cijo Jose; Vasil Khalidov; Marc Szafraniec; Seung Eun Yi; Michaël Ramamonjisoa; Francisco Massa; Daniel Haziza; et al. (CoRR, 2025)