May 9 – 11, 2023
Dijon (campus de l'U. Bourgogne)
Europe/Paris timezone

Statistical insights on PINNs

May 11, 2023, 1:30 PM
Salle René Baire (4th floor) (Dijon (campus de l'U. Bourgogne))

Salle René Baire (4th floor)

Dijon (campus de l'U. Bourgogne)

Faculté des Sciences Mirande 9 avenue Alain Savary - 21078 Dijon Cedex


Claire Boyer


Physics-informed neural networks (PINNs) combine the expressiveness of neural networks with the interpretability of physical modeling. Their good practical performance has been demonstrated both in the context of solving partial differential equations and in the context of hybrid modeling, which consists of combining an imperfect physical model with noisy observations. However, most of their theoretical properties remain to be established. We offer some food for thought and statistical insight into the proper use of PINNs.

Presentation materials

There are no materials yet.