Exploiting Latent Attribute Interaction with Transformer on Heterogeneous Information Networks

no code implementations • 6 Nov 2023 • Zeyuan Zhao, Qingqing Ge, Anfeng Cheng, Yiding Liu, Xiang Li, Shuaiqiang Wang

In addition, most of them only consider the interactions between nodes while neglecting the high-order information behind the latent interactions among different node features.

Attribute

Resist Label Noise with PGM for Graph Neural Networks

no code implementations • 3 Nov 2023 • Qingqing Ge, Jianxiang Yu, Zeyuan Zhao, Xiang Li

To further leverage the information of clean labels in the noisy label set, we put forward LNP-v2, which incorporates the noisy label set into the Bayesian network to generate clean labels.

Enhancing Graph Neural Networks with Structure-Based Prompt

no code implementations • 26 Oct 2023 • Qingqing Ge, Zeyuan Zhao, Yiding Liu, Anfeng Cheng, Xiang Li, Shuaiqiang Wang, Dawei Yin

Graph Neural Networks (GNNs) are powerful in learning semantics of graph data.

Contrastive Learning Graph Classification +1