2 papers
cs.LG2026
GraphNNK -- Graph Classification and Interpretability
Zeljko Bolevic, Milos Brajovic, Isidora Stankovic +1
Graph Neural Networks (GNNs) have become a standard approach for learning from graph-structured data. However, their reliance on parametric classifiers (most often linear softmax l…
cs.CV2024
Perturbation on Feature Coalition: Towards Interpretable Deep Neural Networks
Xuran Hu, Mingzhe Zhu, Zhenpeng Feng +2
The inherent "black box" nature of deep neural networks (DNNs) compromises their transparency and reliability. Recently, explainable AI (XAI) has garnered increasing attention from…