Research
Conferences:
- R. Ohana, K. Nadjahi, A. Rakotomamonjy, L. Ralaivola. Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances. ICML 2023. [pdf]
- S. Kolouri, K. Nadjahi, U. Şimşekli, S. Shahrampour. Generalized Sliced Probability Metrics. IEEE ICASSP 2022 (Best Paper Award). [pdf]
- K. Nadjahi, A. Durmus, P. E. Jacob, R. Badeau, U. Şimşekli. Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections. NeurIPS 2021. [pdf]
- K. Nadjahi, A. Durmus, L. Chizat, S. Kolouri, S. Shahrampour, U. Şimşekli. Statistical and Topological Properties of Sliced Probability Divergences. NeurIPS 2020 (Spotlight presentation). [pdf]
- K. Nadjahi, V. De Bortoli, A. Durmus, R. Badeau, U. Şimşekli. Approximate Bayesian Computation with the Sliced-Wasserstein Distance. IEEE ICASSP 2020 (Best Student Paper Award). [pdf] [code]
- K. Nadjahi, A. Durmus, U. Şimşekli, R. Badeau. Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance. NeurIPS 2019 (Spotlight presentation). [pdf] [code] [poster] [slides] [video]
- S. Kolouri, K. Nadjahi, U. Şimşekli, R. Badeau, G. K. Rohde. Generalized Sliced Wasserstein Distances. NeurIPS 2019. [pdf] [code] [poster]
- K. Nadjahi, R. Laroche, R. Tachet des Combes. Safe Policy Improvement with Soft Baseline Bootstrapping. ECML-PKDD 2019. [pdf] [code] [poster]
Workshops: