3 papers
cs.CR2025
Watermarking Graph Neural Networks via Explanations for Ownership Protection
Jane Downer, Yingdan Shi, Ziyan Liu +2
Graph Neural Networks (GNNs) are widely deployed in industry, making their intellectual property valuable. However, protecting GNNs from unauthorized use remains a challenge. Water…
cs.LG2024
Efficient and Robust Continual Graph Learning for Graph Classification in Biology
Ding Zhang, Jane Downer, Can Chen +1
Graph classification is essential for understanding complex biological systems, where molecular structures and interactions are naturally represented as graphs. Traditional graph n…
cs.LG2024
Identifying Backdoored Graphs in Graph Neural Network Training: An Explanation-Based Approach with Novel Metrics
Jane Downer, Ren Wang, Binghui Wang
Graph Neural Networks (GNNs) have gained popularity in numerous domains, yet they are vulnerable to backdoor attacks that can compromise their performance and ethical application.…