Diffusion models learn distributions generated by complex Langevin dynamics
- URL: http://arxiv.org/abs/2412.01919v1
- Date: Mon, 02 Dec 2024 19:07:14 GMT
- Title: Diffusion models learn distributions generated by complex Langevin dynamics
- Abstract summary: Diffusion models, a class of generative AI, can learn distributions from data.<n>In this contribution, we explore the ability of diffusion models to learn the distributions created by a complex Langevin process.
- Score: 6.610338540492242
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The probability distribution effectively sampled by a complex Langevin process for theories with a sign problem is not known a priori and notoriously hard to understand. Diffusion models, a class of generative AI, can learn distributions from data. In this contribution, we explore the ability of diffusion models to learn the distributions created by a complex Langevin process.
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