32 citations · 60 across the 3 of their papers we have counts for
3 papers
physics.flu-dyn2022★ 32 cited
A Finite Element-Inspired Hypergraph Neural Network: Application to Fluid Dynamics Simulations
Rui Gao, Indu Kant Deo, Rajeev K. Jaiman
An emerging trend in deep learning research focuses on the applications of graph neural networks (GNNs) for mesh-based continuum mechanics simulations. Most of these learning frame…
physics.flu-dyn2022★ 26 cited
Predicting fluid-structure interaction with graph neural networks
Rui Gao, Rajeev K. Jaiman
We present a rotation equivariant, quasi-monolithic graph neural network framework for the reduced-order modeling of fluid-structure interaction systems. With the aid of an arbitra…
eess.SP2022★ 2 cited
SSGCNet: A Sparse Spectra Graph Convolutional Network for Epileptic EEG Signal Classification
Jialin Wang, Rui Gao, Haotian Zheng +2
In this article, we propose a sparse spectra graph convolutional network (SSGCNet) for solving Epileptic EEG signal classification problems. The aim is to achieve a lightweight dee…