Hao Wu

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 19

Top Topics

Markov Processes

Dynamical Systems

Dynamical Models

Top Venues

J. Comput. Phys.

J. Nonlinear Sci.

Publications

Ling Guo, Hao Wu, Yan Wang, Wenwen Zhou, Tao Zhou
IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning. J. Comput. Phys. 510 (2024)
Hao Wu, Frank Noé
Reaction coordinate flows for model reduction of molecular kinetics. CoRR (2023)
Moritz Hoffmann, Martin Scherer, Tim Hempel, Andreas Mardt, Brian de Silva, Brooke E. Husic, Stefan Klus, Hao Wu, J. Nathan Kutz, Steven L. Brunton, Frank Noé
Deeptime: a Python library for machine learning dynamical models from time series data. Mach. Learn. Sci. Technol. 3 (1) (2022)
Ling Guo, Hao Wu, Tao Zhou
Normalizing field flows: Solving forward and inverse stochastic differential equations using physics-informed flow models. J. Comput. Phys. 461 (2022)
Wenchong Tian, Hao Wu
Kernel Embedding Based Variational Approach for Low-Dimensional Approximation of Dynamical Systems. Comput. Methods Appl. Math. 21 (3) (2021)
Moritz Hoffmann, Martin Scherer, Tim Hempel, Andreas Mardt, Brian de Silva, Brooke E. Husic, Stefan Klus, Hao Wu, J. Nathan Kutz, Steven L. Brunton, Frank Noé
Deeptime: a Python library for machine learning dynamical models from time series data. CoRR (2021)
Andreas Mardt, Luca Pasquali, Frank Noé, Hao Wu
Deep learning Markov and Koopman models with physical constraints. MSML (2020)
Hao Wu, Jonas Köhler, Frank Noé
Stochastic Normalizing Flows. CoRR (2020)
Hao Wu, Frank Noé
Variational Approach for Learning Markov Processes from Time Series Data. J. Nonlinear Sci. 30 (1) (2020)
Hao Wu, Jonas Köhler, Frank Noé
Stochastic Normalizing Flows. NeurIPS (2020)
Frank Noé, Hao Wu
Boltzmann Generators - Sampling Equilibrium States of Many-Body Systems with Deep Learning. CoRR (2018)
Hao Wu, Andreas Mardt, Luca Pasquali, Frank Noé
Deep Generative Markov State Models. CoRR (2018)
Hao Wu, Andreas Mardt, Luca Pasquali, Frank Noé
Deep Generative Markov State Models. NeurIPS (2018)
Péter Koltai, Hao Wu, Frank Noé, Christof Schütte
Optimal Data-Driven Estimation of Generalized Markov State Models for Non-Equilibrium Dynamics. Comput. 6 (1) (2018)
Stefan Klus, Feliks Nüske, Péter Koltai, Hao Wu, Ioannis G. Kevrekidis, Christof Schütte, Frank Noé
Data-Driven Model Reduction and Transfer Operator Approximation. J. Nonlinear Sci. 28 (3) (2018)
Hao Wu, Frank Noé
Spectral Learning of Dynamic Systems from Nonequilibrium Data. NIPS (2016)
Hao Wu, Frank Noé
Spectral learning of dynamic systems from nonequilibrium data. CoRR (2016)
Hao Wu
Maximum margin clustering for state decomposition of metastable systems. Neurocomputing 164 (2015)
Hao Wu
Maximum Margin Clustering for State Decomposition of Metastable Systems. CoRR (2015)
Hao Wu, Frank Noé
Optimal Estimation of Free Energies and Stationary Densities from Multiple Biased Simulations. Multiscale Model. Simul. 12 (1) (2014)
Hao Wu
Maximum Margin Clustering for State Decomposition of Metastable Systems. IWANN (1) (2013)
Bin Xu, Fuchun Sun, Shixing Wang, Hao Wu
Adaptive hypersonic flight control via back-stepping and Kriging estimation. SMC (2011)
Hao Wu, Frank Noé
A flat Dirichlet process switching model for Bayesian estimation of hybrid systems. ICCS (2011)
Hao Wu, Frank Noé
Maximum a posteriori estimation for Markov chains based on Gaussian Markov random fields. ICCS (1) (2010)
Hao Wu, Frank Noé
Probability Distance Based Compression of Hidden Markov Models. Multiscale Model. Simul. 8 (5) (2010)