Conveners
Physics-informed AI for Surrogate Models: Scientific Session
- Michiel Straat
- André Artelt
- Thorben Markmann
Description
This meeting is supposed to bring together people interested in physics-informed AI, particularly for building surrogate models.
We are interested in discussing the following, non-complete, list of topics and applications:
- Making use of physics knowledge (e.g. differential equations) in building AI systems
- Neural surrogate models (e.g. neural operators, PINNs, etc.) for:
- Fast data generation and system exploration
- Control
- Event diagnosis (e.g. event detection, localization, classification, etc.)
- Inverse problems (e.g. inferring system's parameters from sensor measurements, etc.)
- Water distribution networks
- Fluid dynamics
- .....
