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Mingyu Yan

2 accepted papers

2023

Simple and Efficient Heterogeneous Graph Neural Network

AAAI 2023technical

Heterogeneous graph neural networks (HGNNs) have the powerful capability to embed rich structural and semantic information of a heterogeneous graph into node representations. Existing HGNNs inherit many mechanisms from graph neural networks (GNNs) designed for homogeneous graphs, especially the atte…

2022

Survey on Graph Neural Network Acceleration: An Algorithmic Perspective

IJCAI 2022poster

Graph neural networks (GNNs) have been a hot spot of recent research and are widely utilized in diverse applications. However, with the use of huger data and deeper models, an urgent demand is unsurprisingly made to accelerate GNNs for more efficient execution. In this paper, we provide a comprehens…

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