Rozet, F. (2026). Generative Modeling in Large-scale Dynamical Systems [Doctoral thesis, ULiège - University of Liège]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/337979 |
Andry, G., Lewin, S., Rozet, F., Rochman, O., Mangeleer, V., Pirlet, M., Faulx, E., Grégoire, M., & Louppe, G. (06 December 2025). Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation [Paper presentation]. Machine Learning and the Physical Sciences Workshop (NeurIPS 2025), San Diego, United States - California. doi:10.48550/arXiv.2504.18720 |
Andry, G., Lewin, S., Rozet, F., Rochman, O., Mangeleer, V., Pirlet, M., Faulx, E., Grégoire, M., & Louppe, G. (06 December 2025). Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation [Poster presentation]. Machine Learning and the Physical Sciences Workshop (NeurIPS 2025). |
Rozet, F., Ohana, R., McCabe, M., Louppe, G., Lanusse, F., & Ho, S. (03 July 2025). Lost in Latent Space: An Empirical Study of Latent Diffusion Models for Physics Emulation. Advances in Neural Information Processing Systems, 38. |
Andry, G., Rozet, F., Lewin, S., Rochman, O., Mangeleer, V., Pirlet, M., Faulx, E., Grégoire, M., & Louppe, G. (2025). Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/333961. |
Savary, T., Rozet, F., & Louppe, G. (2025). Training-Free Data Assimilation with GenCast [Poster presentation]. Climate Change AI Workshop, San Diego, United States - California. |
Ohana, R.* , McCabe, M.* , Meyer, L., Morel, R., Agocs, F. J., Beneitez, M., Berger, M., Burkhart, B., Dalziel, S. B., Fielding, D. B., Fortunato, D., Goldberg, J. A., Hirashima, K., Jiang, Y.-F., Kerswell, R. R., Maddu, S., Miller, J., Mukhopadhyay, P., Nixon, S. S., ... Ho, S. (30 November 2024). The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning. Advances in Neural Information Processing Systems, 37. * These authors have contributed equally to this work. |
Rozet, F., Andry, G., Lanusse, F., & Louppe, G. (22 May 2024). Learning Diffusion Priors from Observations by Expectation Maximization. Advances in Neural Information Processing Systems, 37. |
Vasist, M., Rozet, F., Absil, O., Mollière, P., Nasedkin, E., & Louppe, G. (14 April 2023). Neural posterior estimation for exoplanetary atmospheric retrieval. Astronomy and Astrophysics, 672, 147. doi:10.1051/0004-6361/202245263 |
Rozet, F., & Louppe, G. (2023). Score-based Data Assimilation for a Two-Layer Quasi-Geostrophic Model [Poster presentation]. Machine Learning and the Physical Sciences Workshop (NeurIPS 2023), New Orleans, United States - Louisiana. |
Rozet, F., & Louppe, G. (2023). Score-based Data Assimilation. Advances in Neural Information Processing Systems, 36. |
Delaunoy, A.* , Hermans, J.* , Rozet, F., Wehenkel, A., & Louppe, G. (December 2022). Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation. Advances in Neural Information Processing Systems, 35. * These authors have contributed equally to this work. |
Hermans, J., Delaunoy, A., Rozet, F., Wehenkel, A., & Louppe, G. (2022). A Crisis In Simulation-Based Inference? Beware, Your Posterior Approximations Can Be Unfaithful. Transactions on Machine Learning Research. |
Rozet, F., & Louppe, G. (13 December 2021). Arbitrary Marginal Neural Ratio Estimation for Simulation-based Inference [Poster presentation]. Fourth Workshop on Machine Learning and the Physical Sciences (NeurIPS 2021), Vancouver, Canada. |