Data Augmentation in Signed Graph Neural Networks

Introduction

This research, conducted during the NeurIPS rebuttal phase, explored data augmentation methods for signed graph datasets, focusing on link prediction tasks.

The Challenge

Signed graphs present unique augmentation challenges. Additional experiments validated the effectiveness of our methods.

Results

The results strengthened the paper’s arguments and demonstrated the robustness of the proposed approach.