An empirical comparison of multi-agent optimization algorithms. - Mahmoud Assran; Michael G. Rabbat (GlobalSIP, 2017)

Asynchronous Subgradient-Push. - Mahmoud Assran; Michael G. Rabbat (CoRR, 2018)

Stochastic Gradient Push for Distributed Deep Learning. - Mahmoud Assran; Nicolas Loizou; Nicolas Ballas; Michael G. Rabbat (ICML, 2019)

Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning. - Mahmoud Assran; Joshua Romoff; Nicolas Ballas; Joelle Pineau; Mike Rabbat (NeurIPS, 2019)

On the Convergence of Nesterov's Accelerated Gradient Method in Stochastic Settings. - Mahmoud Assran; Mike Rabbat (ICML, 2020)

Recovering Petaflops in Contrastive Semi-Supervised Learning of Visual Representations. - Mahmoud Assran; Nicolas Ballas; Lluís Castrejón; Michael G. Rabbat (CoRR, 2020)

A Closer Look at Codistillation for Distributed Training. - Shagun Sodhani; Olivier Delalleau; Mahmoud Assran; Koustuv Sinha; Nicolas Ballas; Michael G. Rabbat (CoRR, 2020)

Advances in Asynchronous Parallel and Distributed Optimization. - Mahmoud Assran; Arda Aytekin; Hamid Reza Feyzmahdavian; Mikael Johansson 001; Michael G. Rabbat (Proc. IEEE, 2020)

Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples. - Mahmoud Assran; Mathilde Caron; Ishan Misra; Piotr Bojanowski; Armand Joulin; Nicolas Ballas; Michael G. Rabbat (ICCV, 2021)

Asynchronous Gradient Push. - Mahmoud Assran; Michael G. Rabbat (IEEE Trans. Autom. Control., 2021)

Masked Siamese Networks for Label-Efficient Learning. - Mahmoud Assran; Mathilde Caron; Ishan Misra; Piotr Bojanowski; Florian Bordes; Pascal Vincent; Armand Joulin; Mike Rabbat; Nicolas Ballas (ECCV (31), 2022)

Memory Augmented Optimizers for Deep Learning. - Paul-Aymeric Martin McRae; Prasanna Parthasarathi; Mido Assran; Sarath Chandar (ICLR, 2022)

Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. - Mahmoud Assran; Quentin Duval; Ishan Misra; Piotr Bojanowski; Pascal Vincent; Michael G. Rabbat; Yann LeCun; Nicolas Ballas (CVPR, 2023)

The hidden uniform cluster prior in self-supervised learning. - Mido Assran; Randall Balestriero; Quentin Duval; Florian Bordes; Ishan Misra; Piotr Bojanowski; Pascal Vincent; Michael G. Rabbat; Nicolas Ballas (ICLR, 2023)

RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data. - Sangwoo Mo; Jong-Chyi Su; Chih-Yao Ma; Mido Assran; Ishan Misra; Licheng Yu; Sean Bell (ICLR, 2023)

Predicting masked tokens in stochastic locations improves masked image modeling. - Amir Bar; Florian Bordes; Assaf Shocher; Mahmoud Assran; Pascal Vincent; Nicolas Ballas; Trevor Darrell; Amir Globerson; Yann LeCun (CoRR, 2023)

Stochastic positional embeddings improve masked image modeling. - Amir Bar; Florian Bordes; Assaf Shocher; Mido Assran; Pascal Vincent; Nicolas Ballas; Trevor Darrell; Amir Globerson; Yann LeCun (ICML, 2024)

Modeling Caption Diversity in Contrastive Vision-Language Pretraining. - Samuel Lavoie; Polina Kirichenko; Mark Ibrahim; Mido Assran; Andrew Gordon Wilson; Aaron C. Courville; Nicolas Ballas (ICML, 2024)

Learning and Leveraging World Models in Visual Representation Learning. - Quentin Garrido; Mahmoud Assran; Nicolas Ballas; Adrien Bardes; Laurent Najman; Yann LeCun (CoRR, 2024)

Revisiting Feature Prediction for Learning Visual Representations from Video. - Adrien Bardes; Quentin Garrido; Jean Ponce; Xinlei Chen; Michael Rabbat; Yann LeCun; Mido Assran; Nicolas Ballas (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)

VEDIT: Latent Prediction Architecture For Procedural Video Representation Learning. - Han Lin; Tushar Nagarajan; Nicolas Ballas; Mido Assran; Mojtaba Komeili; Mohit Bansal; Koustuv Sinha (ICLR, 2025)

An Image is Worth More Than 16x16 Patches: Exploring Transformers on Individual Pixels. - Duy-Kien Nguyen; Mido Assran; Unnat Jain; Martin R. Oswald; Cees G. M. Snoek; Xinlei Chen (ICLR, 2025)

Intuitive physics understanding emerges from self-supervised pretraining on natural videos. - Quentin Garrido; Nicolas Ballas; Mahmoud Assran; Adrien Bardes; Laurent Najman; Michael Rabbat; Emmanuel Dupoux; Yann LeCun (CoRR, 2025)

Locate 3D: Real-World Object Localization via Self-Supervised Learning in 3D. - Sergio Arnaud; Paul McVay; Ada Martin; Arjun Majumdar; Krishna Murthy Jatavallabhula; Phillip Thomas; Ruslan Partsey; Daniel Dugas; Abha Gejji; Alexander Sax; Vincent-Pierre Berges; Mikael Henaff; et al. (CoRR, 2025)

V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning. - Mido Assran; Adrien Bardes; David Fan; Quentin Garrido; Russell Howes; Mojtaba Komeili; Matthew J. Muckley; Ammar Rizvi; Claire Roberts; Koustuv Sinha; Artem Zholus; Sergio Arnaud; et al. (CoRR, 2025)

A Shortcut-aware Video-QA Benchmark for Physical Understanding via Minimal Video Pairs. - Benno Krojer; Mojtaba Komeili; Candace Ross; Quentin Garrido; Koustuv Sinha; Nicolas Ballas; Mahmoud Assran (CoRR, 2025)