Email: inass.sekkat@enpc.fr
I am currently a PhD student working on “Large scale Bayesian inference” under the supervision of Gabriel Stoltz.
I would like to acknowledge financial support from Université Mohammed VI Polytechnique.
Publications
- Removing the mini-batching error in Bayesian inference using Adaptive Langevin dynamics, arXiv preprint 2105.10347 (2021) pdf.
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Generative methods for sampling transition paths in molecular dynamics, arXiv preprint arXiv:2205.02818, (2022) pdf.
Scientific Experience
- October 2021 — November 2021. Worked on minibatching error of Bayesian Neural Networks under the supervision of Ben Leimkuhler as a visiting scholar at University of Edinburgh,School of Mathematics.
- August 2021. Summer School – CEMRACS. Generative methods for reactive trajectories in molecular dynamics, supervised by: Tony Lelièvre, Geneviève Robin and Gabriel Stoltz.
Talks given in conferences and workshops
- Bézout-Facebook scientific workshop, November 4th, 2019.
- International Conference in Monte Carlo & Quasi-Monte Carlo Methods in Scientific Computing MCQMC 2020, August 10-14, 2020.
- Bernoulli-IMS One World Symposium, August 2020.
- GTT seminar (LJLL, Sorbonne université) April 2021.
- SIAM Materials Science 2021, online, May 2021.
- ML/MD seminar, Edinburgh University, October 2021.
Posters
- Bayes Comp, University of Florida, January 2020.
- Bernoulli-IMS One World Symposium, August 2020.
Teaching
- Second year course in analysis at Université Paris-Dauphine, 24h, (tutorials)
- Project for 1A Ecole des Ponts ParisTech (MCMC methods), 10h.
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