Can Pouliquen

Quick bio

Hello ! I am a 2nd year PhD student in Machine Learning at the Ecole Normale Supérieure de Lyon under the supervision of Mathurin Massias, Titouan Vayer and Paulo Gonçalves. I am a part of OCKHAM, a joint team of Inria¹ and CNRS², led by Rémi Gribonval.

Previously, I was a research intern in Deep Learning in the NeuroAI team of CERCO, a CNRS lab in Toulouse³, under the supervision of Andrea Alamia and Rufin VanRullen, where I had the opportunity to work on the oscillatory dynamics of artificial neural networks under some biological feasibility constraints.

Before that, we may have met in Berlin, Montpellier, Lyon, Istanbul, Beyrouth, Amman or Cairo. Hit me up if that's the case !

Outside of research, I enjoy hiking, running, food, beers, and "la belle vie" with my girlfriend⁴.

French national institute of research in informatics and applied mathematics
French national center of scientific research
The "pink city" in beautiful South-West, France
The picture above is us on top of the Ben Nevis, Scotland

Research

I am currently working on large-scale optimization for statistical machine learning in the context of sparse graph learning.

A bit more formally, given an empirical covariance matrix \(S \in \mathbb{R}^{p \times p}\) of a dataset of \(n\) random vectors \( x_i \sim \mathcal{N}^p(\mu, \Sigma) \), I am interested in estimating \( \Theta = \Sigma^{-1}\) (called precision matrix) with a sparsity prior. I am currently trying to bridge the gap between convex optimization-based approaches and deep learning-based approaches to do so.

I have a particular interest in applications to neuroscience problems.

Here is a list of links to my publications:

Implicit differentiation for hyperparameter tuning the weighted Graphical Lasso.
Can Pouliquen, Paulo Gonçalves, Mathurin Massias, Titouan Vayer
GRETSI, 2023.

Sparsity in neural networks can improve their privacy.
Antoine Gonon, Léon Zheng, Clément Lalanne, Quoc-Tung Le, Guillaume Lauga, Can Pouliquen
GRETSI, 2023.

Teaching

ENS de Lyon: Convex optimization M1 (2023-2024)
TA of Mathurin Massias, 12h

CPE Lyon: Optimization algorithms M1 (2023-2024)
TA of Marion Foare, 20h

Ecole Centrale de Lyon: Probability theory L3 (2023-2024)
TA of Céline Helbert and Christophette Blanchet, 32h

Talks

Implicit differentiation for hyperparameter tuning the weighted Graphical Lasso. GRETSI oral, August 2023.

Neuroscience inspired machine learning. OCKHAM seminar, June 2023.

Estimating dynamic functional connectivity graphs. LIP PhD seminar, May 2023.

Contact

To get in touch:

Email: can.pouliquen \AT\ ens-lyon \DOT\ fr
Office: M7-1H29, ENS Lyon, site Monod, 46 allée d'Italie, 69007, Lyon, France
Tel: If you know me already, shoot me an email so I can send it to you :)