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Titel:

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

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz
Autor(en):
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...     »
Stichworte:
graph neural networks, numerical methods, numerical simulation, physical simulations
Dewey-Dezimalklassifikation:
620 Ingenieurwissenschaften
Kongress- / Buchtitel:
ICML 2022 2nd AI for Science Workshop
Jahr:
2022
Sprache:
en
WWW:
https://openreview.net/forum?id=I9Wjg82SWx
TUM Einrichtung:
Lehrstuhl für Aerodynamik und Strömungsmechanik
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