33 citations · 109 across the 25 of their papers we have counts for
4 papers · 1 filter
STAMP: Outlier-Aware Test-Time Adaptation with Stable Memory Replay
Yongcan Yu, Lijun Sheng, Ran He +1
Test-time adaptation (TTA) aims to address the distribution shift between the training and test data with only unlabeled data at test time. Existing TTA methods often focus on impr…
Mind the Label Shift of Augmentation-based Graph OOD Generalization
Junchi Yu, Jian Liang, Ran He
Out-of-distribution (OOD) generalization is an important issue for Graph Neural Networks (GNNs). Recent works employ different graph editions to generate augmented environments and…
Towards the Explanation of Graph Neural Networks in Digital Pathology with Information Flows
Junchi Yu, Tingyang Xu, Ran He
As Graph Neural Networks (GNNs) are widely adopted in digital pathology, there is increasing attention to developing explanation models (explainers) of GNNs for improved transparen…
Improving Subgraph Recognition with Variational Graph Information Bottleneck
Junchi Yu, Jie Cao, Ran He
Subgraph recognition aims at discovering a compressed substructure of a graph that is most informative to the graph property. It can be formulated by optimizing Graph Information B…