DASTR adaptively samples points from |∇q|² e^{-βV} with a normalizing flow, producing more accurate neural committor approximations on the tested high-dimensional problems.
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Estimating Committor Functions via Deep Adaptive Sampling on Rare Transition Paths
DASTR adaptively samples points from |∇q|² e^{-βV} with a normalizing flow, producing more accurate neural committor approximations on the tested high-dimensional problems.