| 2024 | ICLR | On Adversarial Training without Perturbing all Examples. | Max Maria Losch, Mohamed Omran, David Stutz, Mario Fritz, Bernt Schiele |
| 2023 | CVPR | Improving Robustness of Vision Transformers by Reducing Sensitivity to Patch Corruptions. | Yong Guo, David Stutz, Bernt Schiele |
| 2023 | ICCV | Robustifying Token Attention for Vision Transformers. | Yong Guo, David Stutz, Bernt Schiele |
| 2022 | ECCV | Improving Robustness by Enhancing Weak Subnets. | Yong Guo, David Stutz, Bernt Schiele |
| 2022 | ICLR | Learning Optimal Conformal Classifiers. | David Stutz, Krishnamurthy Dvijotham, Ali Taylan Cemgil, Arnaud Doucet |
| 2021 | ICCV | Relating Adversarially Robust Generalization to Flat Minima. | David Stutz, Matthias Hein, Bernt Schiele |
| 2020 | ECCV | Adversarial Training Against Location-Optimized Adversarial Patches. | Sukrut Rao, David Stutz, Bernt Schiele |
| 2020 | ICML | Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks. | David Stutz, Matthias Hein, Bernt Schiele |
| 2019 | CVPR | Disentangling Adversarial Robustness and Generalization. | David Stutz, Matthias Hein, Bernt Schiele |
| 2018 | CVPR | Learning 3D Shape Completion From Laser Scan Data With Weak Supervision. | David Stutz, Andreas Geiger |