One for Two: A Unified Framework for Imbalanced Graph Classification via Dynamic Balanced Prototype

TL;DR

Graph Neural Networks (GNNs) have advanced graph classification, yet they remain vulnerable to graph-level imbalance, encompassing class imbalance and topological imbalance. To address both types of imbalance in a unified manner, we propose UniImb, a Unified framework for Imbalanced graph classification.

Opening excerpt from the authors’ abstract. source