I am currently undertaking my second year of Ph.D in Machine Learning at Sorbonne Université. I work within the departement of statistics (LPSM) under the supervision of Claire Boyer (Sorbonne-Université) and Erwan Scornet (Ecole Polytechnique).

My research is focused on the theoretical aspects of ML. I am particularly interested in studying Neural Networks from an interpretability perspective. More generally, I am very enthusiastic about deep neural networks seen as either mathematical objects or practical tools.

Publications

Analyzing the tree-layer structure of Deep Forests, Ludovic Arnould, Claire Boyer, Erwan Scornet. Proceedings of the 38th International Conference on Machine Learning, PMLR 139:342-350, 2021. Download paper here

Is interpolation benign for random forest regression?, Ludovic Arnould, Claire Boyer, Erwan Scornet. (2022). Accepted at AISTATS 2023. Download paper here

Sparse tree-based initialization for neural networks, Patrick Lutz, Ludovic Arnould, Claire Boyer, Erwan Scornet. (2022). Accepted at ICLR 2023. Download paper here

Teaching

Below is a list of the few courses I taught at Sorbonne Université during my Ph.D from October 2020 to May 2022.

• Probability - Last year of B.S in mathematics.

• Statistics - Last year of B.S in mathematics.

• Linear Models - First year of M.S in mathematics (taught at ISUP)

CV

You can download my cv here: link