Targeted free energy estimation via learned mappings

Free energy perturbation (FEP) was proposed by Zwanzig more than six decades ago as a method to estimate free energy differences, and has since inspired a huge body of related methods that use it as an integral building block. Being an importance sampling based estimator, however, FEP suffers from a...

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Veröffentlicht in:	arXiv.org 2020-08
Hauptverfasser:	Wirnsberger, Peter, Ballard, Andrew J, Papamakarios, George, Abercrombie, Stuart, Racanière, Sébastien, Pritzel, Alexander, Danilo Jimenez Rezende, Blundell, Charles
Format:	Artikel
Sprache:	eng
Schlagworte:	Free energy Importance sampling Machine learning Mapping Neural networks Perturbation Physics - Chemical Physics Physics - Computational Physics Solvation Statistics - Machine Learning Test procedures
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