Workshop

The workshop »Advancing Scientific Machine Learning in Industry« is organized at the TU Munich and deals with Scientific Machine Learning (SciML). This field of research combines traditional scientific modeling with machine learning methods to overcome challenges such as interpretability and physical limitations. SciML uses approaches such as physically informed neural networks and stochastic differential equation solvers to improve scientific modeling. It offers versatile applications in various disciplines, from subatomic particles to economics and climate.

Dr. Matthias Kabel, deputy head of the department »Flow and Material Simulation«, Dr. Matti Schneider and Pavan Bhat Keelanje Srinivas are on site with the two poster presentations »Selective Distillation Algorithm to Evaluate Deep Material Networks« and »Deep Material Networks«.