120 citations · 183 across the 5 of their papers we have counts for
5 papers
Mining United Nations General Assembly Debates
Mateusz Grzyb, Mateusz Krzyziński, Bartłomiej Sobieski +4
This project explores the application of Natural Language Processing (NLP) techniques to analyse United Nations General Assembly (UNGA) speeches. Using NLP allows for the efficient…
Interpretable Machine Learning for Survival Analysis
Sophie Hanna Langbein, Mateusz Krzyziński, Mikołaj Spytek +3
With the spread and rapid advancement of black box machine learning models, the field of interpretable machine learning (IML) or explainable artificial intelligence (XAI) has becom…
survex: an R package for explaining machine learning survival models
Mikołaj Spytek, Mateusz Krzyziński, Sophie Hanna Langbein +3
Due to their flexibility and superior performance, machine learning models frequently complement and outperform traditional statistical survival models. However, their widespread a…
Challenges facing the explainability of age prediction models: case study for two modalities
Mikolaj Spytek, Weronika Hryniewska-Guzik, Jaroslaw Zygierewicz +2
The prediction of age is a challenging task with various practical applications in high-impact fields like the healthcare domain or criminology. Despite the growing number of model…
SurvSHAP(t): Time-dependent explanations of machine learning survival models
Mateusz Krzyziński, Mikołaj Spytek, Hubert Baniecki +1
Machine and deep learning survival models demonstrate similar or even improved time-to-event prediction capabilities compared to classical statistical learning methods yet are too…