Neuro-Fuzzy Hybrid Position/Force Control for a Space Robot with Flexible Dual-Arms. - Fuchun Sun 001; Hao Zhang; Hao Wu 035 (ISNN (2), 2004)

Optimal Trajectory Planning of a Flexible Dual-Arm Space Robot with Vibration Reduction. - Hao Wu 035; Fuchun Sun 001; Zengqi Sun; Licheng Wu (J. Intell. Robotic Syst., 2004)

Fuzzy Particle Filtering for Uncertain Systems. - Hao Wu 035; Fuchun Sun 001; Huaping Liu 001 (IEEE Trans. Fuzzy Syst., 2008)

Probability Distance Based Compression of Hidden Markov Models. - Hao Wu 035; Frank Noé (Multiscale Model. Simul., 2010)

Maximum a posteriori estimation for Markov chains based on Gaussian Markov random fields. - Hao Wu 035; Frank Noé (ICCS, 2010)

Adaptive hypersonic flight control via back-stepping and Kriging estimation. - Bin Xu 003; Fuchun Sun 001; Shixing Wang 002; Hao Wu 035 (SMC, 2011)

A flat Dirichlet process switching model for Bayesian estimation of hybrid systems. - Hao Wu 035; Frank Noé (ICCS, 2011)

Optimal Estimation of Free Energies and Stationary Densities from Multiple Biased Simulations. - Hao Wu 035; Frank Noé (Multiscale Model. Simul., 2014)

Maximum margin clustering for state decomposition of metastable systems. - Hao Wu 035 (Neurocomputing, 2015)

Spectral Learning of Dynamic Systems from Nonequilibrium Data. - Hao Wu 035; Frank Noé (NIPS, 2016)

Deep Generative Markov State Models. - Hao Wu 035; Andreas Mardt; Luca Pasquali; Frank Noé (NeurIPS, 2018)

Optimal Data-Driven Estimation of Generalized Markov State Models for Non-Equilibrium Dynamics. - Péter Koltai; Hao Wu 035; Frank Noé; Christof Schütte (Comput., 2018)

Boltzmann Generators - Sampling Equilibrium States of Many-Body Systems with Deep Learning. - Frank Noé; Hao Wu 035 (CoRR, 2018)

Data-Driven Model Reduction and Transfer Operator Approximation. - Stefan Klus; Feliks Nüske; Péter Koltai; Hao Wu 035; Ioannis G. Kevrekidis; Christof Schütte; Frank Noé (J. Nonlinear Sci., 2018)

Deep learning Markov and Koopman models with physical constraints. - Andreas Mardt; Luca Pasquali; Frank Noé; Hao Wu 035 (MSML, 2020)

Stochastic Normalizing Flows. - Hao Wu 035; Jonas Köhler 001; Frank Noé (NeurIPS, 2020)

Variational Approach for Learning Markov Processes from Time Series Data. - Hao Wu 035; Frank Noé (J. Nonlinear Sci., 2020)

Kernel Embedding Based Variational Approach for Low-Dimensional Approximation of Dynamical Systems. - Wenchong Tian; Hao Wu 035 (Comput. Methods Appl. Math., 2021)

Normalizing field flows: Solving forward and inverse stochastic differential equations using physics-informed flow models. - Ling Guo; Hao Wu 035; Tao Zhou (J. Comput. Phys., 2022)

Deeptime: a Python library for machine learning dynamical models from time series data. - Moritz Hoffmann 002; Martin Scherer; Tim Hempel; Andreas Mardt; Brian de Silva; Brooke E. Husic; Stefan Klus; Hao Wu 035; J. Nathan Kutz; Steven L. Brunton; Frank Noé (Mach. Learn. Sci. Technol., 2022)

Reaction coordinate flows for model reduction of molecular kinetics. - Hao Wu 035; Frank Noé (CoRR, 2023)

IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning. - Ling Guo; Hao Wu 035; Yan Wang; Wenwen Zhou; Tao Zhou (J. Comput. Phys., 2024)

Efficient Bayesian inference using physics-informed invertible neural networks for inverse problems. - Xiaofei Guan; Xintong Wang; Hao Wu 035; Zihao Yang; Peng Yu (Mach. Learn. Sci. Technol., 2024)

Consistent Sampling and Simulation: Molecular Dynamics with Energy-Based Diffusion Models. - Michael Plainer; Hao Wu 035; Leon Klein; Stephan Günnemann; Frank Noé (CoRR, 2025)