| On the reproducibility of expert-operated and robotic ultrasound acquisitions R Kojcev, A Khakzar, B Fuerst, O Zettinig, C Fahkry, R DeJong, J Richmon, ... International journal of computer assisted radiology and surgery 12, 1003-1011, 2017 | 58 | 2017 |
| Neural Response Interpretation through the Lens of Critical Pathways A Khakzar, S Baselizadeh, S Khanduja, C Rupprecht, ST Kim, N Navab Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 51* | 2021 |
| Fine-grained neural network explanation by identifying input features with predictive information Y Zhang, A Khakzar, Y Li, A Farshad, ST Kim, N Navab Advances in Neural Information Processing Systems 34, 20040-20051, 2021 | 31 | 2021 |
| Do explanations explain? model knows best A Khakzar, P Khorsandi, R Nobahari, N Navab Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 30 | 2022 |
| Chexplaining in style: Counterfactual explanations for chest x-rays using stylegan M Atad, V Dmytrenko, Y Li, X Zhang, M Keicher, J Kirschke, B Wiestler, ... ICML 2022 Interpretable Machine Learning in Healthcare (IMLH) Workshop, 2022 | 28 | 2022 |
| A survey on transferability of adversarial examples across deep neural networks J Gu, X Jia, P de Jorge, W Yu, X Liu, A Ma, Y Xun, A Hu, A Khakzar, Z Li, ... Transactions on Machine Learning Research, 2024 | 26 | 2024 |
| Spatio-temporal Learning from Longitudinal Data for Multiple Sclerosis Lesion Segmentation S Denner, A Khakzar, M Sajid, M Saleh, Z Spiclin, ST Kim, N Navab International Conference on Medical Image Computing and Computer-Assisted …, 2020 | 26 | 2020 |
| Learning Interpretable Features via Adversarially Robust Optimization of Chest X-ray Models A Khakzar, S Albarqouni, N Navab International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 25* | 2019 |
| Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models A Khakzar, S Musatian, J Buchberger, IV Quiroz, N Pinger, S Baselizadeh, ... International Conference on Medical Image Computing and Computer-Assisted …, 2021 | 18 | 2021 |
| Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Features A Khakzar, Y Zhang, W Mansour, Y Cai, Y Li, Y Zhang, ST Kim, N Navab International Conference on Medical Image Computing and Computer-Assisted …, 2021 | 17 | 2021 |
| FlexR: few-shot classification with language embeddings for structured reporting of chest x-rays M Keicher, K Zaripova, T Czempiel, K Mach, A Khakzar, N Navab Medical Imaging with Deep Learning, 1493-1508, 2023 | 15* | 2023 |
| Latent guard: a safety framework for text-to-image generation R Liu, A Khakzar, J Gu, Q Chen, P Torr, F Pizzati ECCV24, 2024 | 12 | 2024 |
| Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs ST Kim, L Goli, M Paschali, A Khakzar, M Keicher, T Czempiel, E Burian, ... International Conference on Medical Image Computing and Computer-Assisted …, 2021 | 12 | 2021 |
| Pixel-level explanation of multiple instance learning models in biomedical single cell images A Sadafi, O Adonkina, A Khakzar, P Lienemann, RM Hehr, D Rueckert, ... International Conference on Information Processing in Medical Imaging, 170-182, 2023 | 10 | 2023 |
| Rethinking Positive Aggregation and Propagation of Gradients in Gradient-based Saliency Methods A Khakzar, S Baselizadeh, N Navab International Conference on Machine Learning (ICML) 2020, Workshop on Human …, 2020 | 9 | 2020 |
| Interpretable vertebral fracture diagnosis P Engstler, M Keicher, D Schinz, K Mach, AS Gersing, SC Foreman, ... International Workshop on Interpretability of Machine Intelligence in …, 2022 | 8 | 2022 |
| Learning Visual Prompts for Guiding the Attention of Vision Transformers R Rezaei, MJ Sabet, J Gu, D Rueckert, P Torr, A Khakzar CVPR 24 - Transformers for Vision Workshop, 2024 | 4 | 2024 |
| Sparse autoencoders reveal universal feature spaces across large language models M Lan, P Torr, A Meek, A Khakzar, D Krueger, F Barez arXiv preprint arXiv:2410.06981, 2024 | 2 | 2024 |
| The cognitive revolution in interpretability: From explaining behavior to interpreting representations and algorithms A Davies, A Khakzar arXiv preprint arXiv:2408.05859, 2024 | 2 | 2024 |
| AttributionLab: Faithfulness of Feature Attribution Under Controllable Environments Y Zhang, Y Li, H Brown, M Rezaei, B Bischl, P Torr, A Khakzar, ... NeurIPS 2023 Workshop XAIA, 2024 | 1 | 2024 |
Nassir NavabProfessor of Computer Science, Technische Universität MünchenVerified email at cs.tum.edu
