iBreakDown: Uncertainty of Model Explanations for Non-additive Predictive Models A Gosiewska, P Biecek arXiv preprint arXiv:1903.11420, 2019 | 13 | 2019 |
Do not trust additive explanations A Gosiewska, P Biecek arXiv preprint arXiv:1903.11420, 2019 | 5 | 2019 |
auditor: an R Package for Model-Agnostic Visual Validation and Diagnostics A Gosiewska, P Biecek The R Journal 11 (2), 85--98, 2019 | 5 | 2019 |
Models in the wild: On corruption robustness of neural nlp systems B Rychalska, D Basaj, A Gosiewska, P Biecek International Conference on Neural Information Processing, 235-247, 2019 | 4 | 2019 |
SAFE ML: Surrogate Assisted Feature Extraction for Model Learning A Gosiewska, A Gacek, P Lubon, P Biecek arXiv preprint arXiv:1902.11035, 2019 | 2 | 2019 |
Transparency, Auditability and eXplainability of Machine Learning Models in Credit Scoring M Bücker, G Szepannek, A Gosiewska, P Biecek arXiv preprint arXiv:2009.13384, 2020 | | 2020 |
Landscape of R packages for eXplainable Artificial Intelligence S Maksymiuk, A Gosiewska, P Biecek arXiv preprint arXiv:2009.13248, 2020 | | 2020 |
Interpretable Meta-Measure for Model Performance A Gosiewska, K Woznica, P Biecek arXiv preprint arXiv:2006.02293, 2020 | | 2020 |
Lifting Interpretability-Performance Trade-off via Automated Feature Engineering A Gosiewska, P Biecek arXiv preprint arXiv:2002.04267, 2020 | | 2020 |
EPP: interpretable score of model predictive power A Gosiewska, M Bakala, K Woznica, M Zwolinski, P Biecek arXiv preprint arXiv:1908.09213, 2019 | | 2019 |
survxai: an R package for structure-agnostic explanations of survival models A Grudziaz, A Gosiewska, P Biecek Journal of Open Source Software 3 (31), 961, 2018 | | 2018 |