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Sampling from unnormalized densities is hard. Neural Non-Equilibrium Hamiltonian Monte Carlo moves probability mass globally while keeping path info. It's tested in simulation only - whether it holds up in real applications is still an open question.
“arXiv:2607.15682v1 Announce Type: new Abstract: Sampling from an unnormalized Boltzmann density requires proposals that move probability mass globally while retaining enough path-probability information for statistical correction. We introd…”
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Neural Non-Equilibrium Hamiltonian Monte Carlo, arXiv
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LAST OBSERVED
Aug 4, 2026