A Rate-Distortion Framework for Explaining Black-Box Model Decisions. - Stefan Kolek; Duc Anh Nguyen; Ron Levie; Joan Bruna; Gitta Kutyniok (xxAI@ICML, 2020)

Cartoon Explanations of Image Classifiers. - Stefan Kolek; Duc Anh Nguyen; Ron Levie; Joan Bruna; Gitta Kutyniok (ECCV (12), 2022)

Generalised Likelihood Ratio Testing Adversaries through the Differential Privacy Lens. - Georgios Kaissis; Alexander Ziller; Stefan Kolek Martinez de Azagra; Daniel Rueckert (CoRR, 2022)

How Do Input Attributes Impact the Privacy Loss in Differential Privacy? - Tamara T. Mueller; Stefan Kolek; Friederike Jungmann; Alexander Ziller; Dmitrii Usynin; Moritz Knolle; Daniel Rueckert; Georgios Kaissis (CoRR, 2022)

Explaining Image Classifiers with Multiscale Directional Image Representation. - Stefan Kolek; Robert Windesheim; Héctor Andrade-Loarca; Gitta Kutyniok; Ron Levie (CVPR, 2023)

Optimal privacy guarantees for a relaxed threat model: Addressing sub-optimal adversaries in differentially private machine learning. - Georgios Kaissis; Alexander Ziller; Stefan Kolek; Anneliese Riess; Daniel Rueckert (NeurIPS, 2023)

Learning Interpretable Queries for Explainable Image Classification with Information Pursuit. - Stefan Kolek; Aditya Chattopadhyay; Kwan Ho Ryan Chan; Héctor Andrade-Loarca; Gitta Kutyniok; René Vidal (CoRR, 2023)

Beyond the Calibration Point: Mechanism Comparison in Differential Privacy. - Georgios Kaissis; Stefan Kolek; Borja Balle; Jamie Hayes; Daniel Rueckert (ICML, 2024)

Complex-Valued Federated Learning with Differential Privacy and MRI Applications. - Anneliese Riess; Alexander Ziller; Stefan Kolek; Daniel Rueckert; Julia A. Schnabel; Georgios Kaissis (ISIC/iMIMIC/EARTH/DeCaF@MICCAI, 2024)