1.3k citations
- Universidad Autónoma de MadridES24 papers
- Université de Bretagne SudFR21 papers
- Max Planck Institute for Gravitational PhysicsDE19 papers
- University of Wisconsin–MilwaukeeUS15 papers
- Centre National de la Recherche ScientifiqueFR14 papers
- Pennsylvania State UniversityUS14 papers
- Tsinghua UniversityCN14 papers
- The University of Texas at AustinUS13 papers
- University of MichiganUS13 papers
- California Institute of TechnologyUS12 papers
- Goddard Space Flight CenterUS12 papers
- Instituto de Física TeóricaES12 papers
Showing 2020 · math.NAShow all
3 papers · 2 filters
math.NA2020★ 32 cited
Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks
Colby L. Wight, Jia Zhao
Phase field models, in particular, the Allen-Cahn type and Cahn-Hilliard type equations, have been widely used to investigate interfacial dynamic problems. Designing accurate, effi…
math.NA2020★ 1 cited
Discovering Phase Field Models from Image Data with the Pseudo-spectral Physics Informed Neural Networks
Jia Zhao
In this paper, we introduce a new deep learning framework for discovering the phase field models from existing image data. The new framework embraces the approximation power of phy…
math.NA2020★ 28 cited
A Non-uniform Time-stepping Convex Splitting Scheme for the Time-fractional Cahn-Hilliard Equation
Jun Zhang, Jia Zhao, JinRong Wang
In this paper, a non-uniform time-stepping convex-splitting numerical algorithm for solving the widely used time-fractional Cahn-Hilliard equation is introduced. The proposed numer…