Hao Wu

Orcid: 0000-0002-2170-0618

Affiliations:
  • Tongji University, School of Mathematical Sciences, Shanghai, China
  • Free University of Berlin, Department of Mathematics and Computer Science, Berlin, Germany (2007 - 2018)


According to our database1, Hao Wu authored at least 23 papers between 2004 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Efficient Bayesian inference using physics-informed invertible neural networks for inverse problems.
Mach. Learn. Sci. Technol., 2024

IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning.
J. Comput. Phys., 2024

2023
Reaction coordinate flows for model reduction of molecular kinetics.
CoRR, 2023

2022
Deeptime: a Python library for machine learning dynamical models from time series data.
Mach. Learn. Sci. Technol., 2022

Normalizing field flows: Solving forward and inverse stochastic differential equations using physics-informed flow models.
J. Comput. Phys., 2022

2021
Kernel Embedding Based Variational Approach for Low-Dimensional Approximation of Dynamical Systems.
Comput. Methods Appl. Math., 2021

2020
Variational Approach for Learning Markov Processes from Time Series Data.
J. Nonlinear Sci., 2020

Stochastic Normalizing Flows.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Deep learning Markov and Koopman models with physical constraints.
Proceedings of Mathematical and Scientific Machine Learning, 2020

2018
Data-Driven Model Reduction and Transfer Operator Approximation.
J. Nonlinear Sci., 2018

Boltzmann Generators - Sampling Equilibrium States of Many-Body Systems with Deep Learning.
CoRR, 2018

Optimal Data-Driven Estimation of Generalized Markov State Models for Non-Equilibrium Dynamics.
Comput., 2018

Deep Generative Markov State Models.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2016
Spectral Learning of Dynamic Systems from Nonequilibrium Data.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Maximum margin clustering for state decomposition of metastable systems.
Neurocomputing, 2015

2014
Optimal Estimation of Free Energies and Stationary Densities from Multiple Biased Simulations.
Multiscale Model. Simul., 2014

2011
A flat Dirichlet process switching model for Bayesian estimation of hybrid systems.
Proceedings of the International Conference on Computational Science, 2011

Adaptive hypersonic flight control via back-stepping and Kriging estimation.
Proceedings of the IEEE International Conference on Systems, 2011

2010
Maximum a posteriori estimation for Markov chains based on Gaussian Markov random fields.
Proceedings of the International Conference on Computational Science, 2010

Probability Distance Based Compression of Hidden Markov Models.
Multiscale Model. Simul., 2010

2008
Fuzzy Particle Filtering for Uncertain Systems.
IEEE Trans. Fuzzy Syst., 2008

2004
Optimal Trajectory Planning of a Flexible Dual-Arm Space Robot with Vibration Reduction.
J. Intell. Robotic Syst., 2004

Neuro-Fuzzy Hybrid Position/Force Control for a Space Robot with Flexible Dual-Arms.
Proceedings of the Advances in Neural Networks, 2004


  Loading...