Xinyan Pu — accepted AI-conference papers

2023

Graph Contrastive Learning with Learnable Graph Augmentation

Xinyan Pu, Ke Zhang, Huazhong Shu, Jean-Louis Coatrieux, Youyong Kong

ICASSP 2023accepted

Graph contrastive learning has gained popularity due to its success in self-supervised graph representation learning. Augmented views in contrastive learning greatly determine the quality of the learned representations. Handcrafted data augmentations in previous work require tedious trial-and- error…

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2022

Hierarchical Diffusion Scattering Graph Neural Network

Ke Zhang, Xinyan Pu, Jiaxing Li, Jiasong Wu, Huazhong Shu, Youyong Kong

IJCAI 2022poster

Graph neural network (GNN) is popular now to solve the tasks in non-Euclidean space and most of them learn deep embeddings by aggregating the neighboring nodes. However, these methods are prone to some problems such as over-smoothing because of the single-scale perspective field and the nature of lo…

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