Who are we?

We are a team of researchers studying complex systems. This started as a collaboration between members of the former Geostat team at Inria Bordeaux and the Complexity Sciences Center at UC Davis, which lead to an official joint research project of the Inria@SiliconValley program. We are in the process of formalizing a new team around this project.

We gladly welcome collaborators, both working on the theoretical aspects of our research agenda, and also on its practical applications. We can also recruit new people, both in France and in the US.

What do we do?

Our goal is to create practical algorithms that would reveal the hidden dynamics in scientific data sets, providing data interpretability, a feature often missing from concurrent machine learning and signal analysis models. Classical signal analysis is mostly built around frequency decomposition, correlations and power spectrum analysis. This tells the scales and locations at which energy is dissipated, but not how. We aim to go beyond this, by also characterizing what patterns hold information, at which scale, and how they transform.

Updated recap of recent work and applications

This presentation was given at the Grenoble Artificial Intelligence for Physical Sciences.