Shijin Duan — accepted AI-conference papers

2024

GraphCroc: Cross-Correlation Autoencoder for Graph Structural Reconstruction

Shijin Duan, Ruyi Ding, Jiaxing He, Aidong Adam Ding, Yunsi Fei, Xiaolin Xu

NeurIPS 2024poster

Graph-structured data is integral to many applications, prompting the development of various graph representation methods. Graph autoencoders (GAEs), in particular, reconstruct graph structures from node embeddings. Current GAE models primarily utilize self-correlation to represent graph structures…

Cited by 0 Source ↗PDF ↗code ↗Scholar ↗

2023

VertexSerum: Poisoning Graph Neural Networks for Link Inference

Ruyi Ding, Shijin Duan, Xiaolin Xu, Yunsi Fei

ICCV 2023poster

Graph neural networks (GNNs) have brought superb performance to various applications utilizing graph structural data, such as social analysis and fraud detection. The graph links, e.g., social relationships and transaction history, are sensitive and valuable information, which raises privacy concern…

Cited by 6 PDF ↗code ↗Scholar ↗