3 papers
cs.LG2026
Explaining Temporal Graph Predictions With Shapley Values
Lea-Marie Sussek, Stefan Heindorf
Temporal Graph Neural Networks (TGNNs) have become increasingly popular in recent years due to their superior predictive performance by combining both spatial and temporal informat…
cs.LG2026
Discrete Diffusion-Based Model-Level Explanation of Heterogeneous GNNs with Node Features
Pallabee Das, Stefan Heindorf
Many real-world datasets, such as citation networks, social networks, and molecular structures, are naturally represented as heterogeneous graphs, where nodes belong to different t…
cs.CV2025
A Responsible Face Recognition Approach for Small and Mid-Scale Systems Through Personalized Neural Networks
Sebastian GroÃ, Stefan Heindorf, Philipp Terhörst
Traditional face recognition systems rely on extracting fixed face representations, known as templates, to store and verify identities. These representations are typically generate…