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Title:

On the Relationships between Graph Neural Networks for the Simulation of Physical Systems and Classical Numerical Methods

Document type:
Konferenzbeitrag
Contribution type:
Textbeitrag / Aufsatz
Author(s):
Toshev, Artur; Paehler, Ludger; Panizza, Andrea; Adams, Nikolaus A.
Abstract:
Recent developments in Machine Learning approaches for modelling physical systems have begun to mirror the past development of numerical methods in the computational sciences. In this survey we begin by providing an example of this development with the parallels between graph neural network acceleration for physical simulations and the development of particle-based approaches. We then give an overview of simulation approaches, which have not yet found their way into state-of-the-art Machine Lear...     »
Keywords:
graph neural networks, numerical methods, numerical simulation, physical simulations
Dewey Decimal Classification:
620 Ingenieurwissenschaften
Book / Congress title:
ICML 2022 2nd AI for Science Workshop
Year:
2022
Language:
en
WWW:
https://openreview.net/forum?id=I9Wjg82SWx
TUM Institution:
Lehrstuhl für Aerodynamik und Strömungsmechanik
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