3 papers
cs.LG2025
Redundancy-Aware Test-Time Graph Out-of-Distribution Detection
Yue Hou, He Zhu, Ruomei Liu +3
Distributional discrepancy between training and test data can lead models to make inaccurate predictions when encountering out-of-distribution (OOD) samples in real-world applicati…
cs.LG2025
Structural Entropy Guided Unsupervised Graph Out-Of-Distribution Detection
Yue Hou, He Zhu, Ruomei Liu +4
With the emerging of huge amount of unlabeled data, unsupervised out-of-distribution (OOD) detection is vital for ensuring the reliability of graph neural networks (GNNs) by identi…
cs.LG2024
NC-NCD: Novel Class Discovery for Node Classification
Yue Hou, Xueyuan Chen, He Zhu +5
Novel Class Discovery (NCD) involves identifying new categories within unlabeled data by utilizing knowledge acquired from previously established categories. However, existing NCD…