2 papers
cs.LG2026
CEAR: Certified Ensemble Adversarial Robustness in DNNs
Daniel Sadig, Mohammadreza Maleki, Hamed Karimi +1
Deep Neural Networks (DNNs) are highly susceptible to adversarial perturbations, leading to extensive research on robustness for safety-critical applications. State-of-the-art empi…
cs.LG2025
GNN's Uncertainty Quantification using Self-Distillation
Hirad Daneshvar, Reza Samavi
Graph Neural Networks (GNNs) have shown remarkable performance in the healthcare domain. However, what remained challenging is quantifying the predictive uncertainty of GNNs, which…