A Quasi-Monte Carlo Method Based on Neural Autoregressive Flow
This paper proposes a novel transport quasi-Monte Carlo framework that combines randomized quasi-Monte Carlo sampling with a neural autoregressive flow architecture for efficient sampling and integration over complex, high-dimensional distributions. The method constructs a sequence of invertible tra...
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| Auteurs principaux: | , |
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| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
MDPI AG
2025-09-01
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| Collection: | Entropy |
| Sujets: | |
| Accès en ligne: | https://www.mdpi.com/1099-4300/27/9/952 |
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