Research

Preprints

• Volume-preserving geometric shape optimization of the Dirichlet energy using variational neural networks, 2024 -
  Amaury Bélières--Frendo, Emmanuel Franck, Victor Michel-Dansac, and Yannick Privat

Software

• GeSONN: GEometric Shape Optimization with Neural Networks, 2024 -
  Amaury Bélières--Frendo, Emmanuel Franck, Victor Michel-Dansac, and Yannick Privat

Communications

Talks and posters in international conferences

• SciML 2024 - Workshop on Scientific Machine Learning - Strasbourg, France, July 2024
  GeSONN: a proof of concept for prescribed volume shape optimization with physics informed and symplectic neural neural networks
• CoMINDS 2024 - Workshop on Computational and Mathematical Methods in Data Science - Delft, Netherlands, April 2024 -
  Geometric shape optimization for Dirichlet energy with physics informed and symplectic neural networks

Talks and posters in French conferences or seminars

• CANUM 2024 - 46ème Congrès d'Analyse Numérique - Île de Ré, France, May 2024 -
  Geometric shape optimization for Dirichlet energy with physics informed and symplectic neural networks
• PhD students' seminar - Strasbourg, France, February 2024
  Relaxation for shape optimisation: porous materials and homogeneisation
• Inria MACARON team seminar - Belmont, France, February 2024
  GeSONN: a python framework for shape optimization with neural networks

Thesis

• M2 thesis - Shape optimization machine learning based - Supervised by V. Michel-Dansac and Y. Privat
• M1 thesis - AvaFrame project - Modeling and simulation of dense quasi-3D snow avalanches, SPH method - Supervised by J.T. Fischer and M. Tonnel