IEEE

Spectral Analysis of Heterogeneous Graph Representation for GNN Tasks on Electric Circuits

Machine learning (ML) holds significant potential for transforming electronic design automation (EDA), but it currently lacks scalable and robust representations of electric circuits. Existing ...
Microsoft

Heterogeneous Graph Neural Network on Semantic Tree

The recent past has seen an increasing interest in Heterogeneous Graph Neural Networks (HGNNs), since many real-world graphs are heterogeneous in nature, from citation graphs to email graphs. However, ...
IEEE

HGL: Accelerating Heterogeneous GNN Training with Holistic Representation and Optimization

Abstract: Graph neural networks (GNNs) have shown to significantly improve graph analytics. Existing systems for GNN training are primarily designed for homogeneous graphs. In industry, however, most ...
Frontiers

TCMRGAT: Relational graph attention networks for predicting stroke treatment efficacy of traditional Chinese medicine prescriptions

Background: Stroke is a serious neurological disorder that poses a global health challenge. Traditional Chinese Medicine (TCM) prescriptions have shown potential in its treatment. However, TCM ...