Clément Bonet

I am a postdoctoral researcher at ENSAE/CREST, working with Anna Korba on Wasserstein Gradient Flows.

My researchs lie at the interface of Optimal Transport, Computational Statistics and Deep Learning.

I defended my PhD in November 2023 and I was supervised by François Septier, Nicolas Courty and Lucas Drumetz. Before that, I graduated from Telecom Paris and from the MVA ("Mathématiques, Vision, Apprentissage") of Ecole Normale Superieure Paris-Saclay. For more informations, you can find my resume here.

PhD Thesis

Bonet, C. (2023). Leveraging Optimal Transport via Projections on Subspaces for Machine Learning Applications (Doctoral dissertation, Université de Bretagne Sud).
Abstract Bibtex Slides

Publications

Bonet, C., Uscidda, T., David, A., Aubin-Frankowski, P.C., & Korba, A. (2024). Mirror and Preconditioned Gradient Descent in Wasserstein Space. In Thirty-eight Conference on Neural Information Processing Systems (NeurIPS).
Abstract Bibtex Code Spotlight
Mahey, G., Chapel, L., Gasso, G., Bonet, C., & Courty, N. (2023). Fast Optimal Transport through Sliced Wasserstein Generalized Geodesics. In Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS).
Abstract Bibtex Code Spotlight
Bonet*, C., Malézieux*, B., Rakotomamonjy, A., Drumetz, L., Moreau, T., Kowalski, M. & Courty, N. (2023). Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals. In Proceedings of International Conference on Machine Learning (ICML). PMLR.
Abstract Bibtex Code Poster
Bonet, C., Chapel, L., Drumetz, L., & Courty, N. (2023). Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical Projections. In Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML). PMLR.
Abstract Bibtex Code Poster
Bonet, C., Berg, P., Courty, N., Septier, F., Drumetz, L., & Pham, M. T. (2023). Spherical Sliced-Wasserstein. International Conference on Learning Representations (ICLR).
Abstract Bibtex Code Poster
Bonet, C., Courty, N., Septier, F., & Drumetz, L. (2022). Efficient Gradient Flows in Sliced-Wasserstein Space. Transactions on Machine Learning Research (TMLR).
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Bonet, C., Vayer, T., Courty, N., Septier, F., & Drumetz, L. Subspace Detours Meet Gromov-Wasserstein. Algorithms 2021, 14, 366.
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Preprints

Bonet, C., Drumetz, L., & Courty, N. (2024). Sliced-Wasserstein Distances and Flows on Cartan-Hadamard Manifolds. arXiv preprint arXiv:2403.06560.
Abstract Bibtex Code
Séjourné, T., Bonet, C., Fatras, K., Nadjahi, K., & Courty, N. (2023). Unbalanced Optimal Transport meets Sliced-Wasserstein. arXiv preprint arXiv:2306.07176.
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Talks/Workshops

Divers

Courses

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