Thea Brüsch

REPEAT: Improving Uncertainty Estimation in Representation Learning Explainability

Incorporating uncertainty is crucial to provide trustworthy explanations of deep learning models. Recent works have demonstrated how uncertainty modeling can be particularly important in the unsupervised field of representation learning explainable artificial intelligence (R-XAI). Current R-XAI meth…