“TorchPhysics: Deep Learning for partial differential equations, November 14 & 15, 2024

The Werner von Siemens Center for Industry and Science (Berlin), the Center for Industrial Mathematics (ZeTeM, University of Bremen) and the Committee for Mathematical Modeling, Simulation, and Optimization (KoMSO) are happy to host the second edition of the KoMSO Academy dedicated to ‘TorchPhysics: Deep Learning for partial differential equations’.

The KoMSO Academy aims at offering mathematicians a platform for an exchange on novel mathematical concepts relevant for industrial applications.

Deep Learning concepts for PDEs are booming and everybody working in this area is confronted with the challenge to decide on suitable architectures and concepts for tackling the respective problems. Hence, our present workshop aims at providing an overview on recent developments for deep learning concepts as well as dedicating substantial hours for training sessions with hands-on examples.

The workshop is based on collaboration with Bosch and our joint TorchPhysics-project, see github.com/boschresearch/torchphysics and will be complemented by invited talks of distinguished experts in the field.

We would very much prefer to see you in Berlin in person. However, we will provide online access for a limited number of participants not able to attend in person.

ANMELDUNG

KoMSO Academy aims at addressing novel trends connecting business and technology with mathematics at an early stage of development. They bring together leading experts from industry and academia for a discussion of the present state of the art, potentials and risks as well as future developments. They are open to short contributions by the participants aiming for feedback for their specific problems. The present workshop targets deep learning concepts for solving partial differential equations and related parametric studies. TorchPhysics has been jointly developed by Bosch and the University of Bremen. It aims at providing an ‘as simple as possible’ platform for testing AI concepts for solving PDEs. We include an introduction in using TorchPhysics as well as hands on exercises using this toolbox. Most importantly, we highlight a technical application for simulating corrosion problems. Furthermore, we highlight recent advances in modeling injection molding processes in industrial applications via deep learning based generative models.”

Source: komso.org