Volume 56 (2022)

Special Volume on Scientific Machine Learning
(Incomplete)
Estimating the time-dependent contact rate of SIR and SEIR models in mathematical epidemiology using physics-informed neural networks
Viktor Grimm, Alexander Heinlein, Axel Klawonn, Martin Lanser, and Janine Weber
Operator inference and physics-informed learning of low-dimensional models for incompressible flows
Peter Benner, Pawan Goyal, Jan Heiland, and Igor Pontes Duff
Pages 28-51; Abstract and links, Full Text (PDF) [1 MB], BibTeX
A comparison of reduced-order modeling approaches using artificial neural networks for PDEs with bifurcating solutions
Martin W. Hess, Annalisa Quaini, and Gianluigi Rozza
Pages 52-65; Abstract and links, Full Text (PDF) [665 KB], BibTeX
A combined finite element and machine learning approach for the prediction of specific cutting forces and maximum tool temperatures in machining
Sai Manish Reddy Mekarthy, Maryam Hashemitaheri, and Harish Cherukuri
Pages 66-85; Abstract and links, Full Text (PDF) [2.4 MB], BibTeX
Structure preservation for the Deep Neural Network Multigrid Solver
Nils Margenberg, Christian Lessig, and Thomas Richter
Pages 86-101; Abstract and links, Full Text (PDF) [1 MB], BibTeX
A non-intrusive method to inferring linear port-Hamiltonian realizations using time-domain data
Karim Cherifi, Pawan Goyal, and Peter Benner
Pages 102-116; Abstract and links, Full Text (PDF) [381 KB], BibTeX
A machine learning framework for LES closure terms
Marius Kurz and Andrea Beck
Pages 117-137; Abstract and links, Full Text (PDF) [6.9 MB], BibTeX
Approximation of a marine ecosystem model by artificial neural networks
Markus Pfeil and Thomas Slawig
Pages 138-156; Abstract and links, Full Text (PDF) [8.5 MB], BibTeX
Decomposition and composition of deep convolutional neural networks and training acceleration via sub-network transfer learning
Linyan Gu, Wei Zhang, Jia Liu, and Xiao-Chuan Cai
Pages 157-186; Abstract and links, Full Text (PDF) [5.8 MB], BibTeX
A deep learning based nonlinear upscaling method for transport equations
Tak Shing Au Yeung, Eric T. Chung, and Simon See
Pages 187-208; Abstract and links, Full Text (PDF) [5.1 MB], BibTeX
A hybrid objective function for robustness of artificial neural networks-estimation of parameters in a mechanical system
Jan Sokolowski, Volker Schulz, Hans-Peter Beise, and Udo Schroeder
Pages 209-234; Abstract and links, Full Text (PDF) [2.2 MB], BibTeX
Surrogate convolutional neural network models for steady computational fluid dynamics simulations
Matthias Eichinger, Alexander Heinlein, and Axel Klawonn
Pages 235-255; Abstract and links, Full Text (PDF) [6.3 MB], BibTeX