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ORCIDMido Assran
Person information
- affiliation: Meta AI, FAIR, Montreal, Canada
- affiliation (PhD): McGill University, Mila, Montreal, Canada
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2020 – today
- 2025
[c14]Han Lin, Tushar Nagarajan, Nicolas Ballas, Mido Assran, Mojtaba Komeili, Mohit Bansal, Koustuv Sinha:
VEDIT: Latent Prediction Architecture For Procedural Video Representation Learning. ICLR 2025- [c13]Duy-Kien Nguyen, Mido Assran, Unnat Jain, Martin R. Oswald, Cees G. M. Snoek, Xinlei Chen:
An Image is Worth More Than 16x16 Patches: Exploring Transformers on Individual Pixels. ICLR 2025 - [i24]Quentin Garrido, Nicolas Ballas, Mahmoud Assran, Adrien Bardes, Laurent Najman, Michael Rabbat, Emmanuel Dupoux, Yann LeCun:
Intuitive physics understanding emerges from self-supervised pretraining on natural videos. CoRR abs/2502.11831 (2025) - [i23]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, Ayush Jain, Ang Cao, Ishita Prasad, Mrinal Kalakrishnan, Michael Rabbat, Nicolas Ballas, Mido Assran, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier:
Locate 3D: Real-World Object Localization via Self-Supervised Learning in 3D. CoRR abs/2504.14151 (2025) - [i22]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, Abha Gejji, Ada Martin, Francois Robert Hogan, Daniel Dugas, Piotr Bojanowski, Vasil Khalidov, Patrick Labatut, Francisco Massa, Marc Szafraniec, Kapil Krishnakumar, Yong Li, Xiaodong Ma, Sarath Chandar, Franziska Meier, Yann LeCun, Michael Rabbat, Nicolas Ballas:
V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning. CoRR abs/2506.09985 (2025) - [i21]Benno Krojer, Mojtaba Komeili, Candace Ross, Quentin Garrido, Koustuv Sinha, Nicolas Ballas, Mahmoud Assran:
A Shortcut-aware Video-QA Benchmark for Physical Understanding via Minimal Video Pairs. CoRR abs/2506.09987 (2025) - 2024
- [j4]Adrien Bardes, Quentin Garrido, Jean Ponce, Xinlei Chen, Michael Rabbat, Yann LeCun, Mido Assran, Nicolas Ballas:
Revisiting Feature Prediction for Learning Visual Representations from Video. Trans. Mach. Learn. Res. 2024 (2024) - [j3]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, Wojciech Galuba, Russell Howes, Po-Yao Huang, Shang-Wen Li, Ishan Misra, Michael Rabbat, Vasu Sharma, Gabriel Synnaeve, Hu Xu, Hervé Jégou, Julien Mairal, Patrick Labatut, Armand Joulin, Piotr Bojanowski:
DINOv2: Learning Robust Visual Features without Supervision. Trans. Mach. Learn. Res. 2024 (2024) - [c12]Amir Bar, Florian Bordes, Assaf Shocher, Mido Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann LeCun:
Stochastic positional embeddings improve masked image modeling. ICML 2024 - [c11]Samuel Lavoie, Polina Kirichenko, Mark Ibrahim, Mido Assran, Andrew Gordon Wilson, Aaron C. Courville, Nicolas Ballas:
Modeling Caption Diversity in Contrastive Vision-Language Pretraining. ICML 2024 - [i20]Quentin Garrido, Mahmoud Assran, Nicolas Ballas, Adrien Bardes, Laurent Najman, Yann LeCun:
Learning and Leveraging World Models in Visual Representation Learning. CoRR abs/2403.00504 (2024) - [i19]Adrien Bardes, Quentin Garrido, Jean Ponce, Xinlei Chen, Michael G. Rabbat, Yann LeCun, Mahmoud Assran, Nicolas Ballas:
Revisiting Feature Prediction for Learning Visual Representations from Video. CoRR abs/2404.08471 (2024) - [i18]Samuel Lavoie, Polina Kirichenko, Mark Ibrahim, Mahmoud Assran, Andrew Gordon Wilson, Aaron C. Courville, Nicolas Ballas:
Modeling Caption Diversity in Contrastive Vision-Language Pretraining. CoRR abs/2405.00740 (2024) - [i17]Duy-Kien Nguyen, Mahmoud Assran, Unnat Jain, Martin R. Oswald, Cees G. M. Snoek, Xinlei Chen:
An Image is Worth More Than 16x16 Patches: Exploring Transformers on Individual Pixels. CoRR abs/2406.09415 (2024) - [i16]Han Lin, Tushar Nagarajan, Nicolas Ballas, Mido Assran, Mojtaba Komeili, Mohit Bansal, Koustuv Sinha:
VEDIT: Latent Prediction Architecture For Procedural Video Representation Learning. CoRR abs/2410.03478 (2024) - 2023
- [c10]Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Yann LeCun, Nicolas Ballas:
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. CVPR 2023: 15619-15629 - [c9]Mido Assran, Randall Balestriero, Quentin Duval, Florian Bordes, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Nicolas Ballas:
The hidden uniform cluster prior in self-supervised learning. ICLR 2023 - [c8]Sangwoo Mo, Jong-Chyi Su, Chih-Yao Ma, Mido Assran, Ishan Misra, Licheng Yu, Sean Bell:
RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data. ICLR 2023 - [i15]Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Yann LeCun, Nicolas Ballas:
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. CoRR abs/2301.08243 (2023) - [i14]Sangwoo Mo, Jong-Chyi Su, Chih-Yao Ma, Mido Assran, Ishan Misra, Licheng Yu, Sean Bell:
RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data. CoRR abs/2302.14483 (2023) - [i13]Maxime Oquab, Timothée Darcet, Théo Moutakanni
, Huy V. Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, Mahmoud Assran, Nicolas Ballas, Wojciech Galuba, Russell Howes, Po-Yao Huang, Shang-Wen Li, Ishan Misra, Michael G. Rabbat, Vasu Sharma, Gabriel Synnaeve, Hu Xu, Hervé Jégou, Julien Mairal, Patrick Labatut, Armand Joulin, Piotr Bojanowski:
DINOv2: Learning Robust Visual Features without Supervision. CoRR abs/2304.07193 (2023) - [i12]Amir Bar, Florian Bordes, Assaf Shocher, Mahmoud Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann LeCun:
Predicting masked tokens in stochastic locations improves masked image modeling. CoRR abs/2308.00566 (2023) - 2022
- [c7]Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Florian Bordes, Pascal Vincent, Armand Joulin, Mike Rabbat, Nicolas Ballas:
Masked Siamese Networks for Label-Efficient Learning. ECCV (31) 2022: 456-473 - [c6]Paul-Aymeric Martin McRae, Prasanna Parthasarathi, Mido Assran, Sarath Chandar:
Memory Augmented Optimizers for Deep Learning. ICLR 2022 - [i11]Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Florian Bordes, Pascal Vincent, Armand Joulin, Michael G. Rabbat, Nicolas Ballas:
Masked Siamese Networks for Label-Efficient Learning. CoRR abs/2204.07141 (2022) - [i10]Mahmoud Assran, Randall Balestriero, Quentin Duval, Florian Bordes, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Nicolas Ballas:
The Hidden Uniform Cluster Prior in Self-Supervised Learning. CoRR abs/2210.07277 (2022) - 2021
- [j2]Mahmoud Assran, Michael G. Rabbat:
Asynchronous Gradient Push. IEEE Trans. Autom. Control. 66(1): 168-183 (2021) - [c5]Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Armand Joulin, Nicolas Ballas, Michael G. Rabbat:
Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples. ICCV 2021: 8423-8432 - [i9]Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Armand Joulin, Nicolas Ballas, Michael G. Rabbat:
Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples. CoRR abs/2104.13963 (2021) - [i8]Paul-Aymeric McRae, Prasanna Parthasarathi, Mahmoud Assran, Sarath Chandar:
Memory Augmented Optimizers for Deep Learning. CoRR abs/2106.10708 (2021) - 2020
- [j1]Mahmoud Assran, Arda Aytekin, Hamid Reza Feyzmahdavian, Mikael Johansson, Michael G. Rabbat:
Advances in Asynchronous Parallel and Distributed Optimization. Proc. IEEE 108(11): 2013-2031 (2020) - [c4]Mahmoud Assran, Mike Rabbat:
On the Convergence of Nesterov's Accelerated Gradient Method in Stochastic Settings. ICML 2020: 410-420 - [i7]Mahmoud Assran, Michael G. Rabbat:
On the Convergence of Nesterov's Accelerated Gradient Method in Stochastic Settings. CoRR abs/2002.12414 (2020) - [i6]Mahmoud Assran, Nicolas Ballas, Lluís Castrejón, Michael G. Rabbat:
Recovering Petaflops in Contrastive Semi-Supervised Learning of Visual Representations. CoRR abs/2006.10803 (2020) - [i5]Mahmoud Assran, Arda Aytekin, Hamid Reza Feyzmahdavian, Mikael Johansson, Michael G. Rabbat:
Advances in Asynchronous Parallel and Distributed Optimization. CoRR abs/2006.13838 (2020) - [i4]Shagun Sodhani, Olivier Delalleau, Mahmoud Assran, Koustuv Sinha, Nicolas Ballas, Michael G. Rabbat:
A Closer Look at Codistillation for Distributed Training. CoRR abs/2010.02838 (2020)
2010 – 2019
- 2019
- [c3]Mahmoud Assran, Nicolas Loizou, Nicolas Ballas, Michael G. Rabbat:
Stochastic Gradient Push for Distributed Deep Learning. ICML 2019: 344-353 - [c2]Mahmoud Assran, Joshua Romoff, Nicolas Ballas, Joelle Pineau, Mike Rabbat:
Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning. NeurIPS 2019: 13299-13309 - [i3]Mahmoud Assran, Joshua Romoff, Nicolas Ballas, Joelle Pineau, Mike Rabbat:
Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning. CoRR abs/1906.04585 (2019) - 2018
- [i2]Mahmoud Assran, Michael G. Rabbat:
Asynchronous Subgradient-Push. CoRR abs/1803.08950 (2018) - [i1]Mahmoud Assran, Nicolas Loizou, Nicolas Ballas, Michael G. Rabbat:
Stochastic Gradient Push for Distributed Deep Learning. CoRR abs/1811.10792 (2018) - 2017
- [c1]Mahmoud Assran, Michael G. Rabbat:
An empirical comparison of multi-agent optimization algorithms. GlobalSIP 2017: 573-577
Coauthor Index
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last updated on 2025-07-13 20:24 CEST by the dblp team
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