| Understanding individual decisions of cnns via contrastive backpropagation J Gu, Y Yang, V Tresp Proceedings of the Asian Conference on Computer Vision (ACCV), 119-134, 2018 | 87 | 2018 |
| Improving the robustness of capsule networks to image affine transformations J Gu, V Tresp IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 7285-7293, 2020 | 34 | 2020 |
| Saliency methods for explaining adversarial attacks J Gu, V Tresp Workshop on Human-Centric Machine Learning, NeurIPS 2019, 2019 | 23 | 2019 |
| Search for better students to learn distilled knowledge J Gu, V Tresp European Conference on Artificial Intelligence (ECAI), 1159-1165, 2020 | 19 | 2020 |
| Interpretable graph capsule networks for object recognition J Gu Proceedings of the AAAI Conference on Artificial Intelligence 35 (2), 1469-1477, 2021 | 17 | 2021 |
| Are vision transformers robust to patch perturbations? J Gu, V Tresp, Y Qin Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 16 | 2022 |
| Attacking Adversarial Attacks as A Defense B Wu, H Pan, L Shen, J Gu, S Zhao, Z Li, D Cai, X He, W Liu arXiv preprint arXiv:2106.04938, 2021 | 16 | 2021 |
| Capsule network is not more robust than convolutional network J Gu, V Tresp, H Hu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 14309-14317, 2021 | 15 | 2021 |
| Understanding bias in machine learning J Gu, D Oelke Workshop on Visualization for AI Explainability, IEEE Vis 2018, 2019 | 15 | 2019 |
| Effective and Efficient Vote Attack on Capsule Networks J Gu, B Wu, V Tresp International Conference on Learning Representations (ICLR), 2021, 2021 | 13 | 2021 |
| Semantics for global and local interpretation of deep neural networks J Gu, V Tresp arXiv preprint arXiv:1910.09085, 2019 | 13 | 2019 |
| Contextual prediction difference analysis for explaining individual image classifications J Gu, V Tresp arXiv preprint arXiv:1910.09086, 2019 | 9 | 2019 |
| Towards efficient adversarial training on vision transformers B Wu*, J Gu*, Z Li, D Cai, X He, W Liu Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 7 | 2022 |
| Adversarial examples on segmentation models can be easy to transfer J Gu, H Zhao, V Tresp, P Torr arXiv preprint arXiv:2111.11368, 2021 | 6 | 2021 |
| Neural network memorization dissection J Gu, V Tresp Workshop on Machine Learning with Guarantees, NeurIPS 2019, 2019 | 6 | 2019 |
| SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness J Gu, H Zhao, V Tresp, PHS Torr Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 5 | 2022 |
| Simple Distillation Baselines for Improving Small Self-supervised Models J Gu, W Liu, Y Tian Workshop on SSL for Autonomous Driving, ICCV 2021, 2021 | 4 | 2021 |
| Verification of classification decisions in convolutional neural networks J Gu US Patent App. 17/294,746, 2022 | 2 | 2022 |
| Watermark Vaccine: Adversarial Attacks to Prevent Watermark Removal X Liu, J Liu, Y Bai, J Gu, T Chen, X Jia, X Cao Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 1 | 2022 |
| Backdoor Defense via Adaptively Splitting Poisoned Dataset K Gao, Y Bai, J Gu, Y Yang, ST Xia arXiv preprint arXiv:2303.12993, 2023 | | 2023 |
Volker TrespLudwig Maximilian University of Munich / München (LMU) and Siemens AGVerified email at dbs.ifi.lmu.de
