Yazid Janati
I am currently a postdoctoral research at CMAP, Ecole polytechnique working with Eric Moulines and Alain Durmus. Previously I was a PhD candidate in Statistics at Télécom SudParis - Institut Polytechnique de Paris, advised by Sylvain Le Corff (LPSM, Sorbonne Université) and Yohan Petetin (CITI, Télécom SudParis). My PhD work focused on building new algorithms related to Monte Carlo methods and studying their theoretical properties. I was and still am particularly interested in the interplay between MC and deep learning methods. At the moment I work on solving inverse problems with Denoising Diffusion models.
Research
Divide-and-Conquer posterior sampling with Denoising Diffusion priors YJ, A. Durmus, E. Moulines, J. Olsson. Under review.
Entropic Mirror Monte Carlo YJ, A. Durmus, S. Le Corff, Y. Petetin, J. Stoehr. Under review.
Monte Carlo guided Diffusion for Bayesian linear inverse problems G. Cardoso, YJ, S. Le Corff, E. Moulines. International Conference on Learning Representations (ICLR) 2024. Oral, top 1.2%.
State and parameter learning with PaRISian Particle Gibbs G. Cardoso, YJ, S. Le Corff, E. Moulines and J. Olsson. International Conference on Machine Learning (ICML) 2023.
Variance estimation for Sequential Monte Carlo Algorithms: a backward sampling approach YJ, S. Le Corff and Y. Petetin. Accepted for publication in Bernoulli.
NEO: Non Equilibrium Sampling on the Orbit of a Deterministic Transform A. Thin, YJ, S. Le Corff, C. Ollion, A. Doucet, A. Durmus, E. Moulines and C. Robert. Advances in Neural Information Processing Systems (NeurIPS) 34 (2021): 17060-17071.
Structured variational Bayesian inference for Gaussian state-space models with regime switching. Y. Petetin, YJ and F. Desbouvries. IEEE Signal Processing Letters 28 (2021): 1953-1957.
Talks and posters
Monte Carlo guided Diffusion for Bayesian linear inverse problems- Mostly Monte Carlo Seminar, Paris Santé Campus, 11/2023
- Un-conference Hawaii in Paris, HEC Paris, 07/2023.
- Journée de la statistique, Université libre de Bruxelles, 07/2023
- PhD statistics seminar, University of Edinburgh (online), 02/2023
- Workshop "On Future Trends and Opportunities for Monte Carlo methods", University of Warsaw, 12/2022.
- PhD students seminar, LPSM, Sorbonne Université, 11/2022.
- Rencontres statistiques du CEREMADE, Université Paris Dauphine, 11/2022.
- MIA seminar, Agro ParisTech, 09/2022.
- Mathematics in Machine Learning summer school, UM6P University, Ben Guerir, 07/2022.
- 5th SMC workshop (poster), UC3M, Madrid, 05/2022.
- PhD students seminar, Télécom Paris, 04/2022.
- NeuRIPS in Paris (poster), SCAI Sorbonne, 11/2021.