31 citations · 33 across the 3 of their papers we have counts for
3 papers
Learning Only On Boundaries: a Physics-Informed Neural operator for Solving Parametric Partial Differential Equations in Complex Geometries
Zhiwei Fang, Sifan Wang, Paris Perdikaris
Recently deep learning surrogates and neural operators have shown promise in solving partial differential equations (PDEs). However, they often require a large amount of training d…
A Physics-Informed Neural Network Framework For Partial Differential Equations on 3D Surfaces: Time-Dependent Problems
Zhiwei Fang, Justin Zhang, Xiu Yang
In this paper, we show a physics-informed neural network solver for the time-dependent surface PDEs. Unlike the traditional numerical solver, no extension of PDE and mesh on the su…
NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework
Oliver Hennigh, Susheela Narasimhan, Mohammad Amin Nabian +7
We present SimNet, an AI-driven multi-physics simulation framework, to accelerate simulations across a wide range of disciplines in science and engineering. Compared to traditional…