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The momentum analogue for Langevin is known as underdamped Langevin, which if you optimize the discretization scheme hard enough, converges faster than ordinary Langevin. As for your question, your guess is as good as mine, but I would guess that the nonconvexity of AI applications causes problems. Sampling is a hard enough problem already in the log-concave setting…