Neural network and partial differential equations

Speaker: Prof. Dr. Lexing Ying
Affiliation: Stanford University, Department of Mathematics and ICME, Institute for Computational and Mathematical Engineering (USA)
Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany)

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Meeting ID: 627 2528 2026 | PIN: 138876

Abstract. In this talk, we will discuss recent interaction between neural networks and partial differential equations. In one direction, neural networks have brought some recent successes in solving partial differential equation problems. In the other direction, partial differential equations offer new perspectives on architecture design, optimization, and generative modeling.

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