| Generalized sliced wasserstein distances S Kolouri, K Nadjahi, U Simsekli, R Badeau, G Rohde Advances in neural information processing systems 32, 2019 | 321 | 2019 |
| Statistical and topological properties of sliced probability divergences K Nadjahi, A Durmus, L Chizat, S Kolouri, S Shahrampour, U Simsekli Advances in Neural Information Processing Systems 33, 20802-20812, 2020 | 80 | 2020 |
| Asymptotic guarantees for learning generative models with the sliced-Wasserstein distance K Nadjahi, A Durmus, U Simsekli, R Badeau Advances in Neural Information Processing Systems 32, 2019 | 69 | 2019 |
| Approximate Bayesian computation with the sliced-Wasserstein distance K Nadjahi, V De Bortoli, A Durmus, R Badeau, U Şimşekli ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 38 | 2020 |
| Safe policy improvement with soft baseline bootstrapping K Nadjahi, R Laroche, R Tachet des Combes Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020 | 37 | 2020 |
| Fast approximation of the sliced-Wasserstein distance using concentration of random projections K Nadjahi, A Durmus, PE Jacob, R Badeau, U Simsekli Advances in Neural Information Processing Systems 34, 12411-12424, 2021 | 34 | 2021 |
| Sliced-Wasserstein distance for large-scale machine learning: theory, methodology and extensions K Nadjahi Institut polytechnique de Paris, 2021 | 17 | 2021 |
| Generalized sliced probability metrics S Kolouri, K Nadjahi, S Shahrampour, U Şimşekli ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 15* | 2022 |
| Unbalanced optimal transport meets sliced-Wasserstein T Séjourné, C Bonet, K Fatras, K Nadjahi, N Courty arXiv preprint arXiv:2306.07176, 2023 | 9 | 2023 |
| Asymmetry in low-rank adapters of foundation models J Zhu, K Greenewald, K Nadjahi, HSO Borde, RB Gabrielsson, L Choshen, ... arXiv preprint arXiv:2402.16842, 2024 | 5 | 2024 |
| Shedding a PAC-Bayesian light on adaptive sliced-Wasserstein distances R Ohana, K Nadjahi, A Rakotomamonjy, L Ralaivola International Conference on Machine Learning, 26451-26473, 2023 | 5 | 2023 |
| Federated wasserstein distance A Rakotomamonjy, K Nadjahi, L Ralaivola arXiv preprint arXiv:2310.01973, 2023 | 3 | 2023 |
| Slicing Mutual Information Generalization Bounds for Neural Networks K Nadjahi, K Greenewald, RB Gabrielsson, J Solomon arXiv preprint arXiv:2406.04047, 2024 | 1 | 2024 |
