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Haotian Chu

2 accepted papers

2022

A Universal PINNs Method for Solving Partial Differential Equations with a Point Source

IJCAI 2022poster

In recent years, deep learning technology has been used to solve partial differential equations (PDEs), among which the physics-informed neural networks (PINNs)method emerges to be a promising method for solving both forward and inverse PDE problems. PDEs with a point source that is expressed as a D…

Cited by 12SourcePDFScholar
2022

Meta-Auto-Decoder for Solving Parametric Partial Differential Equations

NeurIPS 2022accept

Many important problems in science and engineering require solving the so-called parametric partial differential equations (PDEs), i.e., PDEs with different physical parameters, boundary conditions, shapes of computation domains, etc. Recently, building learning-based numerical solvers for parametr…

Cited by 44SourcePDFScholar