Browsing Tag
Paris Perdikaris
6 posts
Paris Perdikaris Receives New Scialog Award for Collaborative Work in Bioimaging
The Scialog: Advanced Bioimaging initiative has selected Paris Perdikaris, Assistant Professor of Mechanical Engineering and Applied Mechanics, to be part of its first cohort of researchers.
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks
Professor Paris Perdikaris, Assistant ProfessorMechanical Engineering and Applied Mechanics, has a new paper out in Computer Methods in…
Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets
The Perdikaris Group has a new paper in preprint about deep operator networks. Abstract Deep operator networks (DeepONets)…
Physics-Informed Neural Networks (PINNs) for Heat Transfer Problems
The Perdikaris Group has a new paper out in the Journal of Heat Transfer.
Congratulations to Professor Paris Perdikaris
Congratulations are in order for Professor Paris Perdikaris who has been selected to receive an Air Force’s Young…
Professor Paris Perdikaris featured in the Department of Energy’s (DOE) ASCR Discovery
In the article, “Lessons machine-learned” in the United States Department of Energy’s (DOE) ASCR Discovery, Professor Paris Perdikaris discusses…