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Steering Diffusion Models to Rare Events with Sequential Monte Carlo

Subedi, Aavash et al.
arXiv (All) · Papers
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machine-learning
Diffusion models are increasingly used as surrogates for expensive simulators in weather prediction, molecular dynamics, and materials design. In these models, computing the probability $p_0[E]$ of an event $E$ is difficult, especially when the event of interest is rare. A stable estimate using Mont
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