Hao Wu
Hao Wu
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Zitiert von
Zitiert von
Markov models of molecular kinetics: Generation and validation
JH Prinz, H Wu, M Sarich, B Keller, M Senne, M Held, JD Chodera, ...
The Journal of chemical physics 134 (17), 174105, 2011
VAMPnets for deep learning of molecular kinetics
A Mardt, L Pasquali, H Wu, F Noé
Nature communications 9 (1), 5, 2018
Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning
F Noé, S Olsson, J Köhler, H Wu
Science 365 (6457), eaaw1147, 2019
Data-driven model reduction and transfer operator approximation
S Klus, F Nüske, P Koltai, H Wu, I Kevrekidis, C Schütte, F Noé
Journal of Nonlinear Science 28, 985-1010, 2018
Multiensemble Markov models of molecular thermodynamics and kinetics
H Wu, F Paul, C Wehmeyer, F Noé
Proceedings of the National Academy of Sciences 113 (23), E3221-E3230, 2016
Variational approach for learning Markov processes from time series data
H Wu, F Noé
Journal of Nonlinear Science 30 (1), 23-66, 2020
Projected and hidden Markov models for calculating kinetics and metastable states of complex molecules
F Noé, H Wu, JH Prinz, N Plattner
The Journal of chemical physics 139 (18), 11B609_1, 2013
Protein-peptide association kinetics beyond the seconds timescale from atomistic simulations
F Paul, C Wehmeyer, ET Abualrous, H Wu, MD Crabtree, J Schöneberg, ...
Nature communications 8 (1), 1095, 2017
Estimation and uncertainty of reversible Markov models
B Trendelkamp-Schroer, H Wu, F Paul, F Noé
The Journal of chemical physics 143 (17), 11B601_1, 2015
Variational Koopman models: Slow collective variables and molecular kinetics from short off-equilibrium simulations
H Wu, F Nüske, F Paul, S Klus, P Koltai, F Noé
The Journal of chemical physics 146 (15), 154104, 2017
Combining experimental and simulation data of molecular processes via augmented Markov models
S Olsson, H Wu, F Paul, C Clementi, F Noé
Proceedings of the National Academy of Sciences 114 (31), 8265-8270, 2017
Statistically optimal analysis of state-discretized trajectory data from multiple thermodynamic states
H Wu, ASJS Mey, E Rosta, F Noé
The Journal of Chemical Physics 141 (21), 12B629_1, 2014
Stochastic normalizing flows
H Wu, J Köhler, F Noé
Advances in Neural Information Processing Systems 33, 5933-5944, 2020
Markov state models from short non-equilibrium simulations—Analysis and correction of estimation bias
F Nüske, H Wu, JH Prinz, C Wehmeyer, C Clementi, F Noé
The Journal of Chemical Physics 146 (9), 094104, 2017
Deep generative markov state models
H Wu, A Mardt, L Pasquali, F Noe
Advances in Neural Information Processing Systems 31, 2018
xTRAM: Estimating equilibrium expectations from time-correlated simulation data at multiple thermodynamic states
ASJS Mey, H Wu, F Noé
Physical Review X 4 (4), 041018, 2014
Variational selection of features for molecular kinetics
MK Scherer, BE Husic, M Hoffmann, F Paul, H Wu, F Noé
The Journal of chemical physics 150 (19), 194108, 2019
Optimal trajectory planning of a flexible dual-arm space robot with vibration reduction
H Wu, F Sun, Z Sun, L Wu
Journal of Intelligent and Robotic Systems 40, 147-163, 2004
Optimal data-driven estimation of generalized Markov state models for non-equilibrium dynamics
P Koltai, H Wu, F Noé, C Schütte
Computation 6 (1), 22, 2018
Deeptime: a Python library for machine learning dynamical models from time series data
M Hoffmann, M Scherer, T Hempel, A Mardt, B de Silva, BE Husic, S Klus, ...
Machine Learning: Science and Technology 3 (1), 015009, 2021
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