Cerebrovascular Network Segmentation of MRA Images With Deep Learning. - Pedro Sanches; Cyril Meyer; Vincent Vigon; Benoît Naegel (ISBI, 2019)

A neural network closure for the Euler-Poisson system based on kinetic simulations. - Léo Bois; Emmanuel Franck; Laurent Navoret; Vincent Vigon (CoRR, 2020)

Hamiltonian reduction using a convolutional auto-encoder coupled to an Hamiltonian neural network. - Raphaël Côte; Emmanuel Franck; Laurent Navoret; Guillaume Steimer; Vincent Vigon (CoRR, 2023)

An Optimal Control Deep Learning Method to Design Artificial Viscosities for Discontinuous Galerkin Schemes. - Léo Bois; Emmanuel Franck; Laurent Navoret; Vincent Vigon (J. Sci. Comput., 2024)

Accelerating the convergence of Newton's method for nonlinear elliptic PDEs using Fourier neural operators. - Joubine Aghili; Emmanuel Franck; Romain Hild; Victor Michel-Dansac; Vincent Vigon (Commun. Nonlinear Sci. Numer. Simul., 2025)

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries. - Michel Duprez; Vanessa Lleras; Alexei Lozinski; Vincent Vigon; Killian Vuillemot (CoRR, 2025)

Reduced Particle in Cell method for the Vlasov-Poisson system using auto-encoder and Hamiltonian neural. - Emmanuel Franck; Laurent Navoret; Vincent Vigon; Raphaël Côte; Guillaume Steimer (CoRR, 2025)

φ -FD: A Well-conditioned Finite Difference Method Inspired by φ -FEM for General Geometries on Elliptic PDEs. - Michel Duprez; Vanessa Lleras; Alexei Lozinski; Vincent Vigon; Killian Vuillemot (J. Sci. Comput., 2025)

φ-FEM-FNO: A new approach to train a Neural Operator as a fast PDE solver for variable geometries. - Michel Duprez; Vanessa Lleras; Alexei Lozinski; Vincent Vigon; Killian Vuillemot (Commun. Nonlinear Sci. Numer. Simul., 2026)