1 code implementation • 22 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.
no code implementations • 26 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.
no code implementations • 26 Jan 2020 • Pierre-Henri Conze, Ali Emre Kavur, Emilie Cornec-Le Gall, Naciye Sinem Gezer, Yannick Le Meur, M. Alper Selver, François Rousseau
In this context, we address fully-automated multi-organ segmentation from abdominal CT and MR images using deep learning.
3 code implementations • 1 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.