Kay Liu

BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs

2022 · arXiv (Cornell University)

Detecting which nodes in graphs are outliers is a relatively new machine learning task with numerous applications. Despite the proliferation of algorithms developed in recent years for this task, there has been no standard comprehensive …

LEGO-Learn: Label-Efficient Graph Open-Set Learning

2024 · arXiv (Cornell University)

How can we train graph-based models to recognize unseen classes while keeping labeling costs low? Graph open-set learning (GOL) and out-of-distribution (OOD) detection aim to address this challenge by training models that can accurately classify …