Stutz, David

14 publications

TMLR 2026 Robust Conformal Prediction for Infrequent Classes Jens-Michalis Papaioannou, Sebastian Jäger, Alexei Figueroa, David Stutz, Betty van Aken, Keno Bressem, Wolfgang Nejdl, Felix Gers, Alexander Löser, Felix Biessmann

TMLR 2025 Conformalized Credal Regions for Classification with Ambiguous Ground Truth Michele Caprio, David Stutz, Shuo Li, Arnaud Doucet

NeurIPS 2024 Conformalized Credal Set Predictors Alireza Javanmardi, David Stutz, Eyke Hüllermeier

ICMLW 2024 Conformalized Credal Set Predictors Alireza Javanmardi, David Stutz, Eyke Hüllermeier

ICLR 2024 On Adversarial Training Without Perturbing All Examples Max Losch, Mohamed Omran, David Stutz, Mario Fritz, Bernt Schiele

TMLR 2023 Conformal Prediction Under Ambiguous Ground Truth David Stutz, Abhijit Guha Roy, Tatiana Matejovicova, Patricia Strachan, Ali Taylan Cemgil, Arnaud Doucet

CVPR 2023 Improving Robustness of Vision Transformers by Reducing Sensitivity to Patch Corruptions Yong Guo, David Stutz, Bernt Schiele

ICCV 2023 Robustifying Token Attention for Vision Transformers Yong Guo, David Stutz, Bernt Schiele

ECCV 2022 Improving Robustness by Enhancing Weak Subnets Yong Guo, David Stutz, Bernt Schiele

ICLR 2022 Learning Optimal Conformal Classifiers David Stutz, Krishnamurthy Dj Dvijotham, Ali Taylan Cemgil, Arnaud Doucet

ICMLW 2021 A Closer Look at the Adversarial Robustness of Information Bottleneck Models Iryna Korshunova, David Stutz, Alexander A Alemi, Olivia Wiles, Sven Gowal

ICCV 2021 Relating Adversarially Robust Generalization to Flat Minima David Stutz, Matthias Hein, Bernt Schiele

ECCVW 2020 Adversarial Training Against Location-Optimized Adversarial Patches Sukrut Rao, David Stutz, Bernt Schiele

ICML 2020 Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks David Stutz, Matthias Hein, Bernt Schiele