Model Reduction with Memory and the Machine Learning of Dynamical Systems
type: Item
instance of: scholarly article
title: Model Reduction with Memory and the Machine Learning of Dynamical Systems
zbMATH Open document ID: 1473.35450
author: Chao Ma
author: Jianchun Wang
author: Weinan E
published in: Communications in Computational Physics
publication date: 2021-10-29T00:00:00Z
full work available at URL: https://arxiv.org/abs/1808.04258
Mathematics Subject Classification ID: 35Q35
Mathematics Subject Classification ID: 65P99
zbMATH DE Number: 7417522
zbMATH Keywords: model reduction
zbMATH Keywords: Mori-Zwanzig
zbMATH Keywords: recurrent neural networks
describes a project that uses: Adam
MaRDI profile type: Publication
arXiv ID: 1808.04258
cites work: Transport, Collective Motion, and Brownian Motion
cites work: Optimal prediction with memory
cites work: A dynamic subgrid scale model for large eddy simulations based on the Mori-Zwanzig formalism
cites work: Reynolds averaged turbulence modelling using deep neural networks with embedded invariance
cites work: Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier-Stokes simulations: a data-driven, physics-informed Bayesian approach
cites work: Efficient implementation of essentially nonoscillatory shock-capturing schemes
cites work: A thermodynamic study of the two-dimensional pressure-driven channel flow
OpenAlex ID: W2963721506
Wikidata QID: Q128468120
DOI: 10.4208/CICP.OA-2018-0269
description: scientific article; zbMATH DE number 7417522