| On the vulnerability of capsule networks to adversarial attacks F Michels, T Uelwer, E Upschulte, S Harmeling arXiv preprint arXiv:1906.03612, 2019 | 25 | 2019 |
| Exploring the limits of deep image clustering using pretrained models N Adaloglou, F Michels, H Kalisch, M Kollmann arXiv preprint arXiv:2303.17896, 2023 | 7 | 2023 |
| Contrastive language-image pretrained (clip) models are powerful out-of-distribution detectors F Michels, N Adaloglou, T Kaiser, M Kollmann arXiv preprint arXiv:2303.05828, 2023 | 2 | 2023 |
| Learning to Detect Adversarial Examples Based on Class Scores T Uelwer, F Michels, O De Candido KI 2021: Advances in Artificial Intelligence: 44th German Conference on AI …, 2021 | 1 | 2021 |
| Rethinking cluster-conditioned diffusion models N Adaloglou, T Kaiser, F Michels, M Kollmann arXiv preprint arXiv:2403.00570, 2024 | | 2024 |
| Adapting Contrastive Language-Image Pretrained (CLIP) Models for Out-of-Distribution Detection N Adaloglou, F Michels, T Kaiser, M Kollmann arXiv e-prints, arXiv: 2303.05828, 2023 | | 2023 |
| Evaluating Robust Perceptual Losses for Image Reconstruction T Uelwer, F Michels, O De Candido I Can't Believe It's Not Better Workshop: Understanding Deep Learning …, 2022 | | 2022 |
