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Jiaqi Yu

2 accepted papers

2025

Graph Anomaly Detection via Multi-Scale Reconstruction of Graph Encoder-Decoder Networks

ICASSP 2025accepted

Existing unsupervised graph anomaly detection (GAD) methods can be categorized into reconstruction based methods and contrastive learning based methods. The principle of reconstruction methods is to capture anomalous nodes based on data reconstruction errors. However, existing reconstruction methods…

Cited by 0SourceScholar
2025

Hydrodynamics Regularization in Reinforcement Learning for Navigating Crowded Scenarios

RA-L 2025

The navigation task in dense crowds is a key research problem in real-world scenarios. It requires an agent to avoid collisions in dynamic environments and reach the agent's destination, ensuring high accuracy and efficiency in its decisions. Existing methods typically treat pedestrians as rigid bod

Cited by 0SourceScholar