| Theoretical behavior of XAI methods in the presence of suppressor variables R Wilming, L Kieslich, B Clark, S Haufe International Conference on Machine Learning, 37091-37107, 2023 | 10 | 2023 |
| Benchmarking the influence of pre-training on explanation performance in MR image classification M Oliveira, R Wilming, B Clark, C Budding, F Eitel, K Ritter, S Haufe Frontiers in Artificial Intelligence 7, 1330919, 2024 | 8 | 2024 |
| XAI-TRIS: non-linear image benchmarks to quantify false positive post-hoc attribution of feature importance B Clark, R Wilming, S Haufe Machine Learning 113 (9), 6871-6910, 2024 | 5 | 2024 |
| Xai-tris: non-linear benchmarks to quantify ml explanation performance B Clark, R Wilming, S Haufe arXiv preprint arXiv:2306.12816, 2023 | 5 | 2023 |
| GECOBench: A gender-controlled text dataset and benchmark for quantifying biases in explanations R Wilming, A Dox, H Schulz, M Oliveira, B Clark, S Haufe arXiv preprint arXiv:2406.11547, 2024 | 2 | 2024 |
| Metrology for artificial intelligence in medicine H Rabus, N Agarwal, A Boubekki, YB Varolgünes, B Clark, C Elster, ... Measurement: Sensors, 101789, 2025 | | 2025 |
| EXACT: Towards a platform for empirically benchmarking Machine Learning model explanation methods B Clark, R Wilming, A Dox, P Eschenbach, S Hached, DJ Wodke, ... Measurement: Sensors, 101794, 2025 | | 2025 |
| Explainable AI needs formal notions of explanation correctness S Haufe, R Wilming, B Clark, R Zhumagambetov, D Panknin, A Boubekki arXiv preprint arXiv:2409.14590, 2024 | | 2024 |
| XAI Methods in the Presence of Suppressor Variables: A Theoretical Consideration R Wilming, L Kieslich, B Clark, S Haufe KI 2023: Advances in Artificial Intelligence, 265, 2023 | | 2023 |
| Benchmark data to study the influence of pre-training on explanation performance in MR image classification M Oliveira, R Wilming, B Clark, C Budding, F Eitel, K Ritter, S Haufe arXiv preprint arXiv:2306.12150, 2023 | | 2023 |
| Position: XAI needs formal notions of explanation correctness S Haufe, R Wilming, B Clark, R Zhumagambetov, D Panknin, A Boubekki Interpretable AI: Past, Present and Future, 0 | | |
| The effect of whitening on explanation performance B Clark, S Karastoyanov, R Wilming, S Haufe Interpretable AI: Past, Present and Future, 0 | | |
Stefan HaufeTechnische Universität Berlin, Physikalisch-Technische Bundesanstalt, Charité - Universitätsmedizinכתובת אימייל מאומתת בדומיין tu-berlin.de
