1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.LG2025
Feature Bank Enhancement for Distance-based Out-of-Distribution Detection
Yuhang Liu, Yuefei Wu, Bin Shi +1
Out-of-distribution (OOD) detection is critical to ensuring the reliability of deep learning applications and has attracted significant attention in recent years. A rich body of li…
cs.LG2025
Out-of-Distribution Generalization on Graphs via Progressive Inference
Yiming Xu, Bin Shi, Zhen Peng +3
The development and evaluation of graph neural networks (GNNs) generally follow the independent and identically distributed (i.i.d.) assumption. Yet this assumption is often untena…
cs.LG2024★ 1 cited
Training a Label-Noise-Resistant GNN with Reduced Complexity
Rui Zhao, Bin Shi, Zhiming Liang +3
Graph Neural Networks (GNNs) have been widely employed for semi-supervised node classification tasks on graphs. However, the performance of GNNs is significantly affected by label…