Variational Monte Carlo approach to partial differential equations with neural networks

The accurate numerical solution of partial differential equations is a central task in numerical analysis allowing to model a wide range of natural phenomena by employing specialized solvers depending on the scenario of application. Here, we develop a variational approach for solving partial differe...

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Hauptverfasser:	Reh, Moritz (VerfasserIn) , Gärttner, Martin (VerfasserIn)
Dokumenttyp:	Article (Journal) Kapitel/Artikel
Sprache:	Englisch
Veröffentlicht:	June 7, 2022
In:	Arxiv Year: 2022, Pages: 1-9
DOI:	10.48550/arXiv.2206.01927
Online-Zugang:	Verlag, lizenzpflichtig, Volltext: https://doi.org/10.48550/arXiv.2206.01927 Verlag, lizenzpflichtig, Volltext: http://arxiv.org/abs/2206.01927
Verfasserangaben:	Moritz Reh and Martin Gärttner

Variational Monte Carlo approach to partial differential equations with neural networks von Reh, Moritz (VerfasserIn) , Gärttner, Martin (VerfasserIn) ,

in: Machine learning: science and technology, 3 (2022), 4, Artikel-ID 04LT02, Seite 1-7

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Variational Monte Carlo approach to partial differential equations with neural networks

Variational Monte Carlo approach to partial differential equations with neural networks von Reh, Moritz (VerfasserIn) , Gärttner, Martin (VerfasserIn) ,

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