Graduated from Ecole Polytechnique in 2019
Master’s degree at Université Paris-Sud
Machine Learning and Optimization
Statistical inference on graphs: the graph alignment problem.
We study inference problems in graphs and matrices, such as graph alignment, which aims at finding a matching between nodes of two graphs preserving most of the edges. In a Bayesian setting, several approaches may be followed: analyzing rigorously existing algorithms based on random models to determine the regimes in which they may succeed, look at the information-theoretical and computational thresholds, or design and propose new algorithms that explore new regimes.