Principles of Multiscale Modeling

By Nicholas K.-R. Kevlahan. 2012

328 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/224d24a8203d1518c7ece62a01a42063177e16b9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. F. Profito
2. P. Grützmacher
3. A. Rosenkranz

Citations in the corpus

• GNOT: A General Neural Operator Transformer for Operator Learning (2023, background): “Third, real physical systems can be multi-scale which means that the whole domain could be divided into physically distinct subdomains (Weinan, 2011).”
• Multi-Scale Surface Texturing in Tribology—Current Knowledge and Future Perspectives (2019, methodology): “Numerical multi-scale methods can be divided into two main classes [143].”
• OpenWorm: an open-science approach to modeling Caenorhabditis elegans (2014, methodology): “In the integrative framework of OpenWorm there is no single preferred scale, and so Geppetto has been developed as a multiscale platform (Vlachos, 2005; Weinan, 2011).”
• Deep relaxation: partial differential equations for optimizing deep neural networks (2017, unknown): “10, 17) or E (2011) for details.”