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Charlie B. Tan

2 accepted papers

2025

Amortized Sampling with Transferable Normalizing Flows

NeurIPS 2025poster

Efficient equilibrium sampling of molecular conformations remains a core challenge in computational chemistry and statistical inference. Classical approaches such as molecular dynamics or Markov chain Monte Carlo inherently lack amortization; the computational cost of sampling must be paid in-full f…

Cited by 0SourceScholar
2025

Scalable Equilibrium Sampling with Sequential Boltzmann Generators

ICML 2025poster

Scalable sampling of molecular states in thermodynamic equilibrium is a long-standing challenge in statistical physics. Boltzmann generators tackle this problem by pairing normalizing flows with importance sampling to obtain uncorrelated samples under the target distribution. In this paper, we exten…

Cited by 2SourcePDFScholar