Electronic Publication/s

ETNA Special Vol. 56 (2022)

56

ETNA Special Vol. 56 (2022)

Details

ISSN1068-9613
ISSN Online1068-9613
ISBN-13 Online978-3-7001-9165-0
Subject AreaMathematics, Physics and Space Research
Quality reviewrefereed - online
doi10.1553/etna_vol56
Viktor Grimm - Alexander Heinlein - Axel Klawonn - Martin Lanser - Janine Weber

Estimating the time-dependent contact rate of SIR and SEIR models in mathematical epidemiology using physics-informed neural networks

page 1

doi: 10.1553/etna_vol56s1

Peter Benner - Pawan Goyal - Jan Heiland - Igor Pontes Duff

Operator inference and physics-informed learning of low-dimensional models for incompressible flows

page 28

doi: 10.1553/etna_vol56s28

Martin W. Hess - Annalisa Quaini - Gianluigi Rozza

A comparison of reduced-order modeling approaches using artificial neural networks for PDEs with bifurcating solutions

page 52

doi: 10.1553/etna_vol56s52

Sai Manish Reddy Mekarthy - Maryam Hashemitaheri - Harish Cherukuri

A combined finite element and machine learning approach for the prediction of specific cutting forces and maximum tool temperatures in machining

page 66

doi: 10.1553/etna_vol56s66

Nils Margenberg - Christian Lessig - Thomas Richter

Structure preservation for the Deep Neural Network Multigrid Solver

page 86

doi: 10.1553/etna_vol56s86

Karim Cherifi - Pawan Goyal - Peter Benner

A non-intrusive method to inferring linear port-Hamiltonian realizations using time-domain data

page 102

doi: 10.1553/etna_vol56s102

Marius Kurz - Andrea Beck

A machine learning framework for LES closure terms

page 117

doi: 10.1553/etna_vol56s117

Markus Pfeil - Thomas Slawig

Approximation of a marine ecosystem model by artificial neural networks

page 138

doi: 10.1553/etna_vol56s138

Linyan Gu - Wei Zhang - Jia Liu - Xiao-Chuan Cai

Decomposition and composition of deep convolutional neural networks and training acceleration via sub-network transfer learning

page 157

doi: 10.1553/etna_vol56s157

Tak Shing Au Yeung - Eric T. Chung - Simon See

A deep learning based nonlinear upscaling method for transport equations

page 187

doi: 10.1553/etna_vol56s187

Jan Sokolowski - Volker Schulz - Hans-Peter Beise - Udo Schroeder

A hybrid objective function for robustness of artificial neural networks-estimation of parameters in a mechanical system

page 209

doi: 10.1553/etna_vol56s209

Matthias Eichinger - Alexander Heinlein - Axel Klawonn

Surrogate convolutional neural network models for steady computational fluid dynamics simulations

page 235

doi: 10.1553/etna_vol56s235