QUANTIFYING UNCERTAINTY OF PHYSICS-INFORMED NEURAL NETWORKS FOR CONTINUUM MECHANICS APPLICATIONS

Physics-informed neural networks (PINNs) are a relatively new technique that has gained significant attention in recent years as a versatile and robust way to solve a wide range of physical problems, including continuum mechanics. One of the main advantages of using PINNs is that they can directly i...

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Bibliographische Detailangaben

Hauptverfasser:	Bonnet-Eymard, Damien, Persoons, Augustin, Faes, Matthias G.R, Moens, David
Format:	Tagungsbericht
Sprache:	eng
Online-Zugang:	Volltext bestellen
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