Program

Thursday, December 7, 2023
08:00
09:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
›8:30 (30min)
›9:00 (10min)
Opening words
Yves Balkanski, Institut Pascal Director
›9:10 (20min)
Opening session
Marc Schoenauer, Scientific Coordinator, IA2 program – IRT SystemX, Research Director Inria Saclay – Ile-de-France
›10:30 (30min)
›11:00 (25min)
Contributed talks (Session 1) - A Meta-Generation framework for Industrial System Generation
Fouad Oubari, Raphael Meunier, Rodrigue Décatoire, Mathilde Mougeot (ENS-Paris Saclay, Michelin) - A Meta-Generation framework for Industrial System Generation
›11:25 (25min)
Contributed talks (Session 1) - Conditional and Unconditonal Generation of Seismic Signals using Diffusion Model .
Hugo Gabrielidis, Filippo Gatti, Stéphane Vialle (LMPS, LISN) - Conditional and Unconditonal Generation of Seismic Signals using Diffusion Model .
›11:50 (25min)
Contributed talks (Session 1) - Speeding HPC simulation with AI : An Introduction to Physics-informed Machine Learning with NVIDIA Modulus
Francois Courteille (NVIDIA) - Speeding HPC simulation with AI : An Introduction to Physics-informed Machine Learning with NVIDIA Modulus
›12:15 (1h30)
›13:45 (25min)
Contributed talks (Session 2) - Approximately well-balanced Discontinuous Galerkin methods using bases enriched with Physics-Informed Neural Networks
Victor Michel-Dansac, Laurent Navoret, Emmanuel Franck (TONUS-Inria Nancy, IRMA) - Approximately well-balanced Discontinuous Galerkin methods using bases enriched with Physics-Informed Neural Networks
›14:10 (25min)
Contributed talks (Session 2) - A self-supervised learning framework to identify the permeability field from images based on physics-informed and convolutional neural networks
John Hanna, José V. Aguado, Sebastien Comas-Cardona, Yves Le Guennec (Ecole Centrale de Nantes, IRT Jules Vernes) - A self-supervised learning framework to identify the permeability field from images based on physics-informed and convolutional neural networks
›14:35 (25min)
Contributed talks (Session 2) - GNN-based Schwarz Preconditioner for Large Scale Problem Solving
Matthieu Nastorg, Marc Schoenauer, Guillaume Charpiat, Thibault Faney, Jean-Marc Gratien, Michele Alessandro Bucci (Inria, IFPEN, Safran Tech) - GNN-based Schwarz Preconditioner for Large Scale Problem Solving
›15:00 (25min)
Contributed talks (Session 2) - Deep Learning Acceleration of Flash Algorithms to Simulate Multicomponent Multiphase Systems.
Paul Mcginn, Chaouki Habchi, Julien Bohbot, Thibault Faney, Bruno Delhom, Jean-Charles De Hemptinne (IFPEN) - Deep Learning Acceleration of Flash Algorithms to Simulate Multicomponent Multiphase Systems.
›15:25 (30min)
›15:55 (25min)
Contributed talks (Session 3) - Sample efficient fluid flow control using neuroevolution guided deep reinforcement learning
Tarun Singh, Laurent Cordier, Ronan Fablet (PPRIME, Lab-STICC) - Sample efficient fluid flow control using neuroevolution guided deep reinforcement learning
›16:20 (25min)
Contributed talks (Session 3) - Solving source- and parameter-dependent PDEs with a multi-input Fourier Neural Operator
Fanny Lehmann, Filippo Gatti, Michaël Bertin, Didier Clouteau (CEA-DAM, LMPS) - Solving source- and parameter-dependent PDEs with a multi-input Fourier Neural Operator
›16:45 (25min)
Contributed talks (Session 3) - Learning operators via Deep Learning models.
Joel Soffo (Airbus, Centrale Nantes) - Learning operators via Deep Learning models.
›17:10 (10min)
Conclusion
Paul Labrogère, CEO, IRT SystemX
›17:20 (10min)
Session
Speech
Logistics
Break
Tour
Online user: 2 Privacy
Loading...