Looking elsewhere: improving variational Monte Carlo gradients by importance sampling
Neural-network quantum states (NQSs) offer a powerful and expressive ansatz for representing quantum many-body wave functions. However, their training via Variational Monte Carlo (VMC) methods remains challenging. It is well known that some scenarios—such as sharply peaked wave functions emerging in...
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| Autores principales: | , , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
IOP Publishing
2026-01-01
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| Colección: | Machine Learning: Science and Technology |
| Materias: | |
| Acceso en línea: | https://doi.org/10.1088/2632-2153/ae387f |
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