| Multimodal Prototypical Networks for Few-shot Learning F Pahde, M Puscas, T Klein, M Nabi WACV 2021, 2020 | 110 | 2020 |
| Cross-modal Hallucination for Few-shot Fine-grained Recognition F Pahde, P Jähnichen, T Klein, M Nabi CVPR 2018 Workshop on Fine-grained Visual Categorization, 2018 | 24 | 2018 |
| Discriminative hallucination for multi-modal few-shot learning F Pahde, M Nabi, T Klein, P Jahnichen 2018 25th IEEE International Conference on Image Processing (ICIP), 156-160, 2018 | 22 | 2018 |
| Self Paced Adversarial Training for Multimodal Few-shot Learning F Pahde, O Ostapenko, P Jähnichen, T Klein, M Nabi WACV 2019, 2018 | 21 | 2018 |
| Reveal to revise: An explainable ai life cycle for iterative bias correction of deep models F Pahde, M Dreyer, W Samek, S Lapuschkin Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 …, 2023 | 20 | 2023 |
| Navigating Neural Space: Revisiting Concept Activation Vectors to Overcome Directional Divergence F Pahde, M Dreyer, L Weber, M Weckbecker, CJ Anders, T Wiegand, ... arXiv preprint arXiv:2202.03482, 2024 | 13* | 2024 |
| Optimizing explanations by network canonization and hyperparameter search F Pahde, GÜ Yolcu, A Binder, W Samek, S Lapuschkin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 12 | 2023 |
| Low-Shot Learning from Imaginary 3D Model F Pahde, M Puscas, J Wolff, T Klein, N Sebe, M Nabi WACV 2019, 2019 | 12 | 2019 |
| From Hope to Safety: Unlearning Biases of Deep Models via Gradient Penalization in Latent Space M Dreyer, F Pahde, CJ Anders, W Samek, S Lapuschkin Proceedings of the AAAI Conference on Artificial Intelligence 38 (19), 2024 | 11 | 2024 |
| Low-shot learning from imaginary 3D model F Pahde, M Puscas, M Nabi, T Klein US Patent 11,080,560, 2021 | 8 | 2021 |
| Self-paced adversarial training for multimodal and 3D model few-shot learning F Pahde, O Ostapenko, T Klein, M Nabi, M Puscas US Patent 10,990,848, 2021 | 4 | 2021 |
| Synthetic Generation of Dermatoscopic Images with GAN and Closed-Form Factorization RR Mekala, F Pahde, S Baur, S Chandrashekar, M Diep, M Wenzel, ... arXiv preprint arXiv:2410.05114, 2024 | 2 | 2024 |
| A protocol for annotation of total body photography for machine learning to analyze skin phenotype and lesion classification CA Primiero, B Betz-Stablein, N Ascott, B D’Alessandro, S Gaborit, ... Frontiers in Medicine 11, 1380984, 2024 | 2 | 2024 |
| Explainable concept mappings of MRI: Revealing the mechanisms underlying deep learning-based brain disease classification C Tinauer, A Damulina, M Sackl, M Soellradl, R Achtibat, M Dreyer, ... World Conference on Explainable Artificial Intelligence, 202-216, 2024 | 1 | 2024 |
| Post-Hoc Concept Disentanglement: From Correlated to Isolated Concept Representations E Erogullari, S Lapuschkin, W Samek, F Pahde arXiv preprint arXiv:2503.05522, 2025 | | 2025 |
| Ensuring Medical AI Safety: Explainable AI-Driven Detection and Mitigation of Spurious Model Behavior and Associated Data F Pahde, T Wiegand, S Lapuschkin, W Samek arXiv preprint arXiv:2501.13818, 2025 | | 2025 |
| Reactive Model Correction: Mitigating Harm to Task-Relevant Features via Conditional Bias Suppression D Bareeva, M Dreyer, F Pahde, W Samek, S Lapuschkin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | | 2024 |
| Explainable concept mappings underlying deep learning brain disease classification C Tinauer, M Sackl, A Damulina, R Achtibat, M Dreyer, F Pahde, ... | | |
| Optimizing Explanations by Network Canonization and Hyperparameter Search-Supplementary Material F Pahde, GU Yolcu, A Binder, W Samek, S Lapuschkin | | |
Moin NabiResearch Scientist at AppleVerified email at uw.edu
