Latent-space time evolution of non-intrusive reduced-order models using Gaussian process emulation

23 July 2020

Papers citing "Latent-space time evolution of non-intrusive reduced-order models using Gaussian process emulation"

3 / 3 papers shown

Title
Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles R. Maulik Romain Egele Krishnan Raghavan Prasanna Balaprakash UQCV AI4TS AI4CE 35 6 0 20 Feb 2023
An AI-based Domain-Decomposition Non-Intrusive Reduced-Order Model for Extended Domains applied to Multiphase Flow in Pipes Claire E. Heaney Zef Wolffs Jón Atli Tómasson L. Kahouadji P. Salinas A. Nicolle Omar K. Matar Ionel M. Navon N. Srinil Christopher C. Pain AI4CE 34 21 0 13 Feb 2022
Uncertainty quantification of a three-dimensional in-stent restenosis model with surrogate modelling Dongwei Ye Pavel S. Zun Valeria Krzhizhanovskaya Alfons G. Hoekstra 27 1 0 11 Nov 2021