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Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|April 27, 2011
Bayesian framework for modeling diffusion processes with nonlinear drift based on nonlinear and incomplete observationsHao Wu, Frank NoéThe Journal of Chemical Physics|March 2, 2015
Gaussian Markov transition models of molecular kineticsHao Wu, Frank NoéThe Journal of Chemical Physics|January 25, 2024
Reaction coordinate flows for model reduction of molecular kineticsHao Wu, Frank NoéThe Journal of Chemical Physics|October 17, 2015
Projected metastable Markov processes and their estimation with observable operator modelsHao Wu, Jan-Hendrik Prinz, Frank NoéProceedings of the National Academy of Sciences of the United States of America|May 27, 2016
Multiensemble Markov models of molecular thermodynamics and kineticsHao Wu, Fabian Paul, Christoph Wehmeyer, et al.Nature Communications|October 24, 2018
Author Correction: VAMPnets for deep learning of molecular kineticsAndreas Mardt, Luca Pasquali, Hao Wu, et al.Nature Communications|January 4, 2018
VAMPnets for deep learning of molecular kineticsAndreas Mardt, Luca Pasquali, Hao Wu, et al.Science (New York, N.Y.)|September 7, 2019
Boltzmann generators: Sampling equilibrium states of many-body systems with deep learningFrank Noé, Simon Olsson, Jonas Köhler, et al.The Journal of Chemical Physics|December 11, 2013
Projected and hidden Markov models for calculating kinetics and metastable states of complex moleculesFrank Noé, Hao Wu, Jan-Hendrik Prinz, et al.The Journal of Chemical Physics|November 9, 2015
Estimation and uncertainty of reversible Markov modelsBenjamin Trendelkamp-Schroer, Hao Wu, Fabian Paul, et al.Pageof 793