| Crypten: Secure multi-party computation meets machine learning B Knott, S Venkataraman, A Hannun, S Sengupta, M Ibrahim, ... Advances in Neural Information Processing Systems 34, 4961-4973, 2021 | 386 | 2021 |
| Global Explanations of Neural Networks M Ibrahim, M Louie, C Modarres, J Paisley AAAI AIES, 2019 | 148* | 2019 |
| The united states covid-19 forecast hub dataset EY Cramer, Y Huang, Y Wang, EL Ray, M Cornell, J Bracher, A Brennen, ... Scientific data 9 (1), 462, 2022 | 103 | 2022 |
| Avi Schwarzschild, Andrew Gordon Wilson, Jonas Geiping, Quentin Garrido, Pierre Fernandez, Amir Bar, Hamed Pirsiavash, Yann LeCun, and Micah Goldblum R Balestriero, M Ibrahim, V Sobal, A Morcos, S Shekhar, T Goldstein, ... A cookbook of self-supervised learning 2, 2023 | 86 | 2023 |
| A whac-a-mole dilemma: Shortcuts come in multiples where mitigating one amplifies others Z Li, I Evtimov, A Gordo, C Hazirbas, T Hassner, CC Ferrer, C Xu, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 55 | 2023 |
| Battle of the backbones: A large-scale comparison of pretrained models across computer vision tasks M Goldblum, H Souri, R Ni, M Shu, V Prabhu, G Somepalli, ... Advances in Neural Information Processing Systems 36, 2024 | 52 | 2024 |
| Imagenet-x: Understanding model mistakes with factor of variation annotations BY Idrissi, D Bouchacourt, R Balestriero, I Evtimov, C Hazirbas, N Ballas, ... arXiv preprint arXiv:2211.01866, 2022 | 43 | 2022 |
| An introduction to vision-language modeling F Bordes, RY Pang, A Ajay, AC Li, A Bardes, S Petryk, O Maņas, Z Lin, ... arXiv preprint arXiv:2405.17247, 2024 | 36 | 2024 |
| Towards Explainable Deep Learning for Credit Lending: A Case Study C Modarres, M Ibrahim, M Louie, J Paisley NeurIPS FEAP 2018 Workshop, 2018 | 35 | 2018 |
| Disentanglement of correlated factors via hausdorff factorized support K Roth, M Ibrahim, Z Akata, P Vincent, D Bouchacourt arXiv preprint arXiv:2210.07347, 2022 | 32 | 2022 |
| Grounding inductive biases in natural images: invariance stems from variations in data D Bouchacourt, M Ibrahim, A Morcos Advances in Neural Information Processing Systems 34, 19566-19579, 2021 | 26 | 2021 |
| Pug: Photorealistic and semantically controllable synthetic data for representation learning F Bordes, S Shekhar, M Ibrahim, D Bouchacourt, P Vincent, A Morcos Advances in Neural Information Processing Systems 36, 2024 | 16 | 2024 |
| The robustness limits of sota vision models to natural variation M Ibrahim, Q Garrido, A Morcos, D Bouchacourt arXiv preprint arXiv:2210.13604, 2022 | 14 | 2022 |
| Modeling caption diversity in contrastive vision-language pretraining S Lavoie, P Kirichenko, M Ibrahim, M Assran, AG Wilson, A Courville, ... arXiv preprint arXiv:2405.00740, 2024 | 13 | 2024 |
| Discovering environments with XRM M Pezeshki, D Bouchacourt, M Ibrahim, N Ballas, P Vincent, D Lopez-Paz arXiv preprint arXiv:2309.16748, 2023 | 13 | 2023 |
| A cookbook of self-supervised learning. arXiv 2023 R Balestriero, M Ibrahim, V Sobal, A Morcos, S Shekhar, T Goldstein, ... arXiv preprint arXiv:2304.12210, 0 | 13 | |
| Addressing the topological defects of disentanglement via distributed operators D Bouchacourt, M Ibrahim, S Deny arXiv preprint arXiv:2102.05623, 2021 | 12 | 2021 |
| Neural relational autoregression for high-resolution COVID-19 forecasting M Le, M Ibrahim, L Sagun, T Lacroix, M Nickel Facebook AI Research, 2020 | 11 | 2020 |
| Does Progress On Object Recognition Benchmarks Improve Real-World Generalization? M Richards, P Kirichenko, D Bouchacourt, M Ibrahim arXiv preprint arXiv:2307.13136, 2023 | 10 | 2023 |
| CrypTen: a new research tool for secure machine learning with PyTorch D Gunning, A Hannun, M Ibrahim, B Knott, L van der Maaten, V Reis, ... Blog post available at https://ai. facebook. com/blog/crypten-a-new-research …, 2019 | 10 | 2019 |
Randall BalestrieroAI ResearcherVerified email at brown.edu
