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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"

9 / 9 papers shown

Calibrated Principal Component Regression

132

21 Oct 2025

Dynamical system prediction from sparse observations using deep neural networks with Voronoi tessellation and physics constraintComputer Methods in Applied Mechanics and Engineering (CMAME), 2024

Hanyang Wang

Hao Zhou

Sibo Cheng

AI4CE

198

31 Aug 2024

Multi-fidelity physics constrained neural networks for dynamical systems

302

03 Feb 2024

Conditional variational autoencoder with Gaussian process regression recognition for parametric modelsJournal of Computational and Applied Mathematics (JCAM), 2023

Xuehan Zhang

Lijian Jiang

BDL DRL

200

16 May 2023

Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles

252

20 Feb 2023

$$\textit{FastSVD-ML-ROM}$: A Reduced-Order Modeling Framework based on Machine Learning for Real-Time Applications$

\textit{FastSVD-ML-ROM}

: A Reduced-Order Modeling Framework based on Machine Learning for Real-Time ApplicationsComputer Methods in Applied Mechanics and Engineering (CMAME), 2022

204

24 Jul 2022

An AI-based Domain-Decomposition Non-Intrusive Reduced-Order Model for Extended Domains applied to Multiphase Flow in PipesThe Physics of Fluids (Phys. Fluids), 2022

291

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

283

11 Nov 2021

Nonlinear proper orthogonal decomposition for convection-dominated flows

263

15 Oct 2021