Track A: Simulation & AI

Track A: Simulation & AI


Deep learning-based reduced order models for scientific applicationsStefania Fresca (Politecnico di Milano)
Learning operatorsSiddhartha Mishra (ETHZ)
Pandora’s box of synthetic images for AIPetra Gospodnetić (Fraunhofer ITWM)

Courses & Tutorials

Surrogate model for Monte-Carlo simulation of electron matter interactionTim Dahmen (DFKI) & Katja Schladitz (Fraunhofer Kaiserslautern)

Numerical schemes for hyperbolic equations enhanced by Scientific Machine LearningVictor Michel Dansac (Inria)

Physics-informed neural networks for simulationRégis Duvigneau (Inria)

Generating high-quality synthetic datasets for computer vision deep learning modelsMatthieu Lecce (AI Verse)


Applications of AI inference at the edge with NXP processorsGaétan Bahl (NXP)

Deep learning for fast and efficient glacier modeling, with applications in glacial erosionGuillaume Cordonnier (Inria)

Super-resolution via AI for fluid simulationMathieu Desbrun (Inria)
Qruise: First steps on the path to an ML PhysicistShai Machnes (Qruise) & Anurag Saha Roy (Qruise)