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

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

23 July 2020

Nesar Ramachandra

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

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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 65 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 103 23 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 44 1 0 11 Nov 2021
Nonlinear proper orthogonal decomposition for convection-dominated flows Shady E. Ahmed Omer San Adil Rasheed T. Iliescu 56 38 0 15 Oct 2021