Data assimilation and Uncertainty Quantification

  • Bayesian data assimilation and inference

  1. J. Wu, J.-X. Wang, S. C. Shadden, Improving the Convergence of the Iterative Ensemble Kalman Filter by Resampling, 2019. [Arxiv, DOI, bib]
  2. J.-C. Wu, J.-X. Wang, S. C. Shadden, Adding constraints to Bayesian inverse problems, 2019 AAAI Conference on Artificial Intelligence (Acceptance Rate: 16.9%), 2019. [Arxiv, Link]

  • Forward uncertainty propagation and surrogate modeling

  1. H. Gao*, X. Zhu, J.-X. Wang. A Bi-fidelity Surrogate Modeling Approach for Uncertainty Propagation in Three-Dimensional Hemodynamic Simulations. 2019. [Arxiv, DOI, bib]
  2. L. Sun*, H. Gao*, S. Pan, J.-X. Wang. Surrogate Modeling for Fluid Flows Based on Physics-Constrained Deep Learning Without Simulation Data. Computer Methods in Applied Mechanics and Engineering, (Accepted), 2019. [Arxiv, DOI, bib].