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Sampling from complex densities is hard. This method stops the sampler early when a classifier says it's good enough, which can speed up Markov chain Monte Carlo methods. We don't know yet if this holds up outside the benchmark.
“arXiv:2606.16073v2 Announce Type: replace Abstract: Sampling from complex, unnormalized probability densities is a fundamental challenge in Bayesian inference and probabilistic modeling. While Markov chain Monte Carlo (MCMC) methods provide…”
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ENTITY
Markov chain Monte Carlo, arXiv
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Automated · no editorial override
LAST OBSERVED
Aug 7, 2026