Contact Info
Department of Applied Mathematics
University of Waterloo
Waterloo, Ontario
Canada N2L 3G1
Phone: 519-888-4567, ext. 32700
Fax: 519-746-4319
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Zoom (Please contact ddelreyfernandez@uwaterloo.ca for meeting link)
Emmanuel Franck, Researcher INRIA
Enhanced Discontinuous Galerkin schemes by neural networks
In this work, we propose to introduce two methods for enriching DG diagrams using learning techniques. The introduction will explain the links between scientific computing and learning methods, and the contribution that the latter can make. Two examples in a discontinuous Galerkin framework for hyperbolic equations will then be introduced. First, we will show how we can improve the accuracy of schemes using parametric physic informed neural networks. The link between these methods and classical numerical methods will also be illustrated. Secondly, we will propose a learning approach close to optimal control methods for constructing new artificial viscosities for these schemes. Both examples will be illustrated with numerical results. In conclusion, the possibilities of hybridation between machine learning and DG methods will be discussed more generally.
Contact Info
Department of Applied Mathematics
University of Waterloo
Waterloo, Ontario
Canada N2L 3G1
Phone: 519-888-4567, ext. 32700
Fax: 519-746-4319
PDF files require Adobe Acrobat Reader
The University of Waterloo acknowledges that much of our work takes place on the traditional territory of the Neutral, Anishinaabeg and Haudenosaunee peoples. Our main campus is situated on the Haldimand Tract, the land granted to the Six Nations that includes six miles on each side of the Grand River. Our active work toward reconciliation takes place across our campuses through research, learning, teaching, and community building, and is co-ordinated within the Office of Indigenous Relations.