94 citations · 120 across the 8 of their papers we have counts for
9 papers
Discovering Data Manifold Geometry through Geometric Properties
David Vigouroux, Lucas Drumetz, Ronan Fablet +1
A prevailing paradigm in modern representation learning is the map-first approach, in which a representation map is learned from reconstruction, embedding, or task objectives. At t…
Majorization-Minimization Networks for Inverse Problems: An Application to EEG Imaging
Le Minh Triet Tran, Sarah Reynaud, Ronan Fablet +3
Inverse problems are often ill-posed and require optimization schemes with strong stability and convergence guarantees. While learning-based approaches such as deep unrolling and m…
Gradients of Connectivity as Graph Fourier Bases of Brain Activity
Giulia Lioi, Vincent Gripon, Abdelbasset Brahim +2
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 neu…
Learning Variational Data Assimilation Models and Solvers
Ronan Fablet, Bertrand Chapron, Lucas. Drumetz +3
This paper addresses variational data assimilation from a learning point of view. Data assimilation aims to reconstruct the time evolution of some state given a series of observati…
A fast and memory-efficient algorithm for smooth interpolation of polyrigid transformations: application to human joint tracking
K. Makki, B. Borotikar, M. Garetier +3
The log Euclidean polyrigid registration framework provides a way to smoothly estimate and interpolate poly-rigid/affine transformations for which the invertibility is guaranteed.…
Joint learning of variational representations and solvers for inverse problems with partially-observed data
Ronan Fablet, Lucas Drumetz, Francois Rousseau
Designing appropriate variational regularization schemes is a crucial part of solving inverse problems, making them better-posed and guaranteeing that the solution of the associate…
On early brain folding patterns using biomechanical growth modeling
Xiaoyu Wang, Amine Bohi, Mariam Al Harrach +3
Abnormal cortical folding patterns may be related to neurodevelopmental disorders such as lissencephaly and polymicrogyria. In this context, computational modeling is a powerful to…
Global Perturbation of Initial Geometry in a Biomechanical Model of Cortical Morphogenesis
Amine Bohi, Xiaoyu Wang, Mariam Al Harrach +3
Cortical folding pattern is a main characteristic of the geometry of the human brain which is formed by gyri (ridges) and sulci (grooves). Several biological hypotheses have sugges…
Residual Networks as Geodesic Flows of Diffeomorphisms
Francois Rousseau, Ronan Fablet
This paper addresses the understanding and characterization of residual networks (ResNet), which are among the state-of-the-art deep learning architectures for a variety of supervi…