eXTraAI: EXplainable and TRAnsparent Artificial Intelligence
What We Do

Our group works on next generation of explainers for predictive models. This will be a disruptive change in the way how machine learning models are created, deployed, and maintained.
Grants

,,MLGenSig: Machine Learning Methods for building the Integrated Genetic Signatures''

,,DALEX: Descriptive mAchine Learning EXplanations''
Publications
Key works
Recent contributions
Dalex: Explainers for complex predictive models in R (2018) Biecek, P., 2018, Journal of Machine Learning Research http://www.jmlr.org/papers/volume19/18-416/18-416.pdf
survxai: an R package for structure-agnostic explanations of survival models, Aleksandra Grudziaz, Alicja Gosiewska, Przemyslaw Biecek (2018), Journal of Open Source Software https://www.theoj.org/joss-papers/joss.00961/10.21105.joss.00961.pdf
iBreakDown: Uncertainty of Model Explanations for Non-additive Predictive Models, Alicja Gosiewska, Przemyslaw Biecek 2019, ARXIV: arXiv:1903.11420v1, https://arxiv.org/abs/1903.11420
Extended 3D and 4D cumulative plots for evaluation of unmatched incurred sample reanalysis, Piotr Rudzki, Michał Kaza, Przemysław Biecek (2018), Bioanalysis https://www.future-science.com/doi/abs/10.4155/bio-2017-0210
SMAD7 is a novel independent predictor of survival in patients with cutaneous melanoma, Kaczorowski M, Biecek P, Donizy P, Pieniazek M, Matkowski R, Halon A (2019), Translational Research https://www.ncbi.nlm.nih.gov/pubmed/30342000
more...
more publications
Team

Przemysław Biecek

Hubert Baniecki
Member

Weronika Hryniewska
Member

Alicja Gosiewska
Member

Katarzyna Kobylińska
Member

Anna Kozak
Member

Wojciech Kretowicz
Member

Michał Kuźba
Member

Szymon Maksymiuk
Member

Tomasz Mikołajczyk
Member

Katarzyna Woźnica
Member

Have a Project in Mind?
Please get in touch with the head of the group.