arXiv (OAI Expanded)
open access
IsingFormer: Augmenting Parallel Tempering With Learned Proposals
Generative models have been extensively used to accelerate MCMC mixing for sampling and optimization, but their effective integration with standard MCMC remains an open question. Here, we introduce a global proposal move in which finite-temperature configurations from an external generator are used
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