auditor: an R Package for Model-Agnostic Visual Validation and Diagnostic. - Alicja Gosiewska; Przemyslaw Biecek (CoRR, 2018)

survxai: an R package for structure-agnostic explanations of survival models. - Aleksandra Grudziaz; Alicja Gosiewska; Przemyslaw Biecek (J. Open Source Softw., 2018)

Models in the Wild: On Corruption Robustness of Neural NLP Systems. - Barbara Rychalska; Dominika Basaj; Alicja Gosiewska; Przemyslaw Biecek (ICONIP (3), 2019)

SAFE ML: Surrogate Assisted Feature Extraction for Model Learning. - Alicja Gosiewska; Aleksandra Gacek; Piotr Lubon; Przemyslaw Biecek (CoRR, 2019)

iBreakDown: Uncertainty of Model Explanations for Non-additive Predictive Models. - Alicja Gosiewska; Przemyslaw Biecek (CoRR, 2019)

EPP: interpretable score of model predictive power. - Alicja Gosiewska; Mateusz Bakala; Katarzyna Woznica; Maciej Zwolinski; Przemyslaw Biecek (CoRR, 2019)

auditor: an R Package for Model-Agnostic Visual Validation and Diagnostics. - Alicja Gosiewska; Przemyslaw Biecek (R J., 2019)

Lifting Interpretability-Performance Trade-off via Automated Feature Engineering. - Alicja Gosiewska; Przemyslaw Biecek (CoRR, 2020)

Interpretable Meta-Measure for Model Performance. - Alicja Gosiewska; Katarzyna Woznica; Przemyslaw Biecek (CoRR, 2020)

Landscape of R packages for eXplainable Artificial Intelligence. - Szymon Maksymiuk; Alicja Gosiewska; Przemyslaw Biecek (CoRR, 2020)

Enabling Machine Learning Algorithms for Credit Scoring - Explainable Artificial Intelligence (XAI) methods for clear understanding complex predictive models. - Przemyslaw Biecek; Marcin Chlebus; Janusz Gajda; Alicja Gosiewska; Anna Kozak; Dominik Ogonowski; Jakub Sztachelski; Piotr Wojewnik (CoRR, 2021)

Simpler is better: Lifting interpretability-performance trade-off via automated feature engineering. - Alicja Gosiewska; Anna Kozak; Przemyslaw Biecek (Decis. Support Syst., 2021)

Interpretable Meta-Score for Model Performance: Extended Abstract. - Alicja Gosiewska; Katarzyna Woznica; Przemyslaw Biecek (Meta-Knowledge Transfer @ ECML/PKDD, 2022)

Transparency, auditability, and explainability of machine learning models in credit scoring. - Michael Bücker; Gero Szepannek; Alicja Gosiewska; Przemyslaw Biecek (J. Oper. Res. Soc., 2022)

Interpretable meta-score for model performance. - Alicja Gosiewska; Katarzyna Woznica; Przemyslaw Biecek (Nat. Mac. Intell., 2022)

Seeking a Sufficient Data Volume for Railway Infrastructure Component Detection with Computer Vision Models. - Alicja Gosiewska; Zuzanna Baran; Monika Baran; Tomasz Rutkowski (Sensors, 2023)