| Multi-level variational autoencoder: Learning disentangled representations from grouped observations D Bouchacourt, R Tomioka, S Nowozin Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 353 | 2018 |
| A benchmark for systematic generalization in grounded language understanding L Ruis, J Andreas, M Baroni, D Bouchacourt, BM Lake Advances in neural information processing systems 33, 19861-19872, 2020 | 165 | 2020 |
| Compositionality and generalization in emergent languages R Chaabouni, E Kharitonov, D Bouchacourt, E Dupoux, M Baroni arXiv preprint arXiv:2004.09124, 2020 | 162 | 2020 |
| Permutation equivariant models for compositional generalization in language J Gordon, D Lopez-Paz, M Baroni, D Bouchacourt International Conference on Learning Representations, 2019 | 125 | 2019 |
| How agents see things: On visual representations in an emergent language game D Bouchacourt, M Baroni arXiv preprint arXiv:1808.10696, 2018 | 112 | 2018 |
| EGG: a toolkit for research on Emergence of lanGuage in Games E Kharitonov, R Chaabouni, D Bouchacourt, M Baroni arXiv preprint arXiv:1907.00852, 2019 | 90 | 2019 |
| Birth of a transformer: A memory viewpoint A Bietti, V Cabannes, D Bouchacourt, H Jegou, L Bottou Advances in Neural Information Processing Systems 36, 1560-1588, 2023 | 78 | 2023 |
| Disco nets: Dissimilarity coefficients networks D Bouchacourt, PK Mudigonda, S Nowozin Advances in Neural Information Processing Systems 29, 2016 | 62 | 2016 |
| An introduction to vision-language modeling F Bordes, RY Pang, A Ajay, AC Li, A Bardes, S Petryk, O Mañas, Z Lin, ... arXiv preprint arXiv:2405.17247, 2024 | 60 | 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 | 49 | 2022 |
| Centralized predictive routing using delay predictability measurements JP Vasseur, G Mermoud, D Bouchacourt US Patent 9,736,056, 2017 | 44 | 2017 |
| Entropy minimization in emergent languages E Kharitonov, R Chaabouni, D Bouchacourt, M Baroni International Conference on Machine Learning, 5220-5230, 2020 | 40 | 2020 |
| Disentanglement of correlated factors via hausdorff factorized support K Roth, M Ibrahim, Z Akata, P Vincent, D Bouchacourt arXiv preprint arXiv:2210.07347, 2022 | 37 | 2022 |
| Hierarchical hybrid batch-incremental learning G Mermoud, JP Vasseur, D Bouchacourt US Patent 9,547,828, 2017 | 33 | 2017 |
| Probing technique for predictive routing in computer networks G Mermoud, JP Vasseur, D Bouchacourt US Patent 9,722,905, 2017 | 29 | 2017 |
| 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 | 28 | 2021 |
| Miss tools and mr fruit: Emergent communication in agents learning about object affordances D Bouchacourt, M Baroni arXiv preprint arXiv:1905.11871, 2019 | 28 | 2019 |
| Educe: Explaining model decisions through unsupervised concepts extraction D Bouchacourt, L Denoyer arXiv preprint arXiv:1905.11852, 2019 | 27 | 2019 |
| Distributed predictive routing using delay predictability measurements JP Vasseur, G Mermoud, D Bouchacourt US Patent 9,525,617, 2016 | 23 | 2016 |
| The robustness limits of sota vision models to natural variation M Ibrahim, Q Garrido, A Morcos, D Bouchacourt arXiv preprint arXiv:2210.13604, 2022 | 21 | 2022 |
Mark IbrahimFundamental AI Research, Meta AIDirección de correo verificada de fb.com
