Search Results for author: François Rousseau

Found 4 papers, 2 papers with code

Turning Normalizing Flows into Monge Maps with Geodesic Gaussian Preserving Flows

1 code implementation22 Sep 2022 Guillaume Morel, Lucas Drumetz, Simon Benaïchouche, Nicolas Courty, François Rousseau

Normalizing Flows (NF) are powerful likelihood-based generative models that are able to trade off between expressivity and tractability to model complex densities.

Gradients of Connectivity as Graph Fourier Bases of Brain Activity

no code implementations26 Sep 2020 Giulia Lioi, Vincent Gripon, Abdelbasset Brahim, François Rousseau, Nicolas Farrugia

The application of graph theory to model the complex structure and function of the brain has shed new light on its organization and function, prompting the emergence of network neuroscience.

End-to-end learning of energy-based representations for irregularly-sampled signals and images

4 code implementations1 Oct 2019 Ronan Fablet, Lucas. Drumetz, François Rousseau

In this paper, we address the end-to-end learning of representations of signals, images and image sequences from irregularly-sampled data, i. e. when the training data involved missing data.

Time Series Time Series Analysis

Cannot find the paper you are looking for? You can Submit a new open access paper.