Structured Bayesian Gaussian process latent variable model: applications to data-driven dimensionality reduction and high-dimensional inversion

11 July 2018

Papers citing "Structured Bayesian Gaussian process latent variable model: applications to data-driven dimensionality reduction and high-dimensional inversion"

5 / 5 papers shown

Title
Harnessing physics-informed operators for high-dimensional reliability analysis problems N Navaneeth Tushar Souvik Chakraborty AI4CE 38 0 0 07 Sep 2024
Attention U-Net as a surrogate model for groundwater prediction M. L. Taccari J. Nuttall Xiaohui Chen He Wang B. Minnema P. Jimack AI4CE 34 16 0 09 Apr 2022
Assessment of DeepONet for reliability analysis of stochastic nonlinear dynamical systems Shailesh Garg Harshit Gupta S. Chakraborty 17 16 0 31 Jan 2022
Data-driven discovery of free-form governing differential equations Steven Atkinson W. Subber Liping Wang Genghis Khan Philippe Hawi R. Ghanem 24 43 0 27 Sep 2019
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data Yinhao Zhu N. Zabaras P. Koutsourelakis P. Perdikaris PINN AI4CE 46 854 0 18 Jan 2019