dalex: Responsible machine learning with interactive explainability and fairness in Python H Baniecki, W Kretowicz, P Piatyszek, J Wisniewski, P Biecek Journal of Machine Learning Research 22 (214), 1-7, 2021 | 101 | 2021 |
SurvSHAP(t): Time-dependent explanations of machine learning survival models M Krzyziński, M Spytek, H Baniecki, P Biecek Knowledge-Based Systems 262, 110234, 2023 | 31 | 2023 |
The grammar of interactive explanatory model analysis H Baniecki, D Parzych, P Biecek Data Mining and Knowledge Discovery, 1-37, 2023 | 26 | 2023 |
modelStudio: Interactive studio with explanations for ML predictive models H Baniecki, P Biecek Journal of Open Source Software 4 (43), 1798, 2019 | 19 | 2019 |
Multi-omics disease module detection with an explainable greedy decision forest B Pfeifer, H Baniecki, A Saranti, P Biecek, A Holzinger Scientific Reports 12 (1), 1-15, 2022 | 17 | 2022 |
Fooling partial dependence via data poisoning H Baniecki, W Kretowicz, P Biecek Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 16 | 2022 |
Towards evaluating explanations of vision transformers for medical imaging P Komorowski, H Baniecki, P Biecek IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops …, 2023 | 11 | 2023 |
Adversarial attacks and defenses in explainable artificial intelligence: A survey H Baniecki, P Biecek Information Fusion 107, 102303, 2024 | 9 | 2024 |
Performance is not enough: The story told by a Rashomon quartet P Biecek, H Baniecki, M Krzyzinski, D Cook arXiv preprint arXiv:2302.13356, 2023 | 4* | 2023 |
Manipulating SHAP via adversarial data perturbations (student abstract) H Baniecki, P Biecek AAAI Conference on Artificial Intelligence 36 (11), 12907-12908, 2022 | 4 | 2022 |
Hospital length of stay prediction based on multi-modal data towards trustworthy human-AI collaboration in radiomics H Baniecki, B Sobieski, P Bombiński, P Szatkowski, P Biecek International Conference on Artificial Intelligence in Medicine, 65-74, 2023 | 2 | 2023 |
survex: An R package for explaining machine learning survival models M Spytek, M Krzyziński, SH Langbein, H Baniecki, MN Wright, P Biecek Bioinformatics 39 (12), btad723, 2023 | 1 | 2023 |
Responsible prediction making of COVID-19 mortality (student abstract) H Baniecki, P Biecek AAAI Conference on Artificial Intelligence 35 (18), 15755-15756, 2021 | 1 | 2021 |
Interpretable machine learning for survival analysis SH Langbein, M Krzyziński, M Spytek, H Baniecki, P Biecek, MN Wright arXiv preprint arXiv:2403.10250, 2024 | | 2024 |
Red teaming models for hyperspectral image analysis using explainable AI V Zaigrajew, H Baniecki, L Tulczyjew, AM Wijata, J Nalepa, N Longépé, ... ICLR 2024 Workshops, 2024 | | 2024 |
Be careful when evaluating explanations regarding ground truth H Baniecki, M Chrabaszcz, A Holzinger, B Pfeifer, A Saranti, P Biecek arXiv preprint arXiv:2311.04813, 2023 | | 2023 |
Explaining and visualizing black-box models through counterfactual paths B Pfeifer, M Krzyzinski, H Baniecki, A Saranti, A Holzinger, P Biecek arXiv preprint arXiv:2307.07764v3, 2023 | | 2023 |