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cs.LG2024
Graph Pre-Training Models Are Strong Anomaly Detectors
Jiashun Cheng, Zinan Zheng, Yang Liu +5
Graph Anomaly Detection (GAD) is a challenging and practical research topic where Graph Neural Networks (GNNs) have recently shown promising results. The effectiveness of existing…
cs.LG2024
Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Physical Dynamics Learning
Zinan Zheng, Yang Liu, Jia Li +2
Incorporating Euclidean symmetries (e.g. rotation equivariance) as inductive biases into graph neural networks has improved their generalization ability and data efficiency in unbo…