Variational Monte Carlo approach to partial differential equations with neural networks
The accurate numerical solution of partial differential equations (PDEs) 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 PDEs gov...
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| Main Authors: | , |
|---|---|
| Format: | Article (Journal) Editorial |
| Language: | English |
| Published: |
1 December 2022
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| In: |
Machine learning: science and technology
Year: 2022, Volume: 3, Issue: 4, Pages: 1-7 |
| ISSN: | 2632-2153 |
| DOI: | 10.1088/2632-2153/aca317 |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.1088/2632-2153/aca317 Verlag, kostenfrei, Volltext: https://iopscience.iop.org/article/10.1088/2632-2153/aca317 
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| Author Notes: | Moritz Reh and Martin Gärttner |
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Variational Monte Carlo approach to partial differential equations with neural networks
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