1 citations · 1 across the 4 of their papers we have counts for
4 papers
CNN-based explanation ensembling for dataset, representation and explanations evaluation
Weronika Hryniewska-Guzik, Luca Longo, Przemysław Biecek
Explainable Artificial Intelligence has gained significant attention due to the widespread use of complex deep learning models in high-stake domains such as medicine, finance, and…
NormEnsembleXAI: Unveiling the Strengths and Weaknesses of XAI Ensemble Techniques
Weronika Hryniewska-Guzik, Bartosz Sawicki, Przemysław Biecek
This paper presents a comprehensive comparative analysis of explainable artificial intelligence (XAI) ensembling methods. Our research brings three significant contributions. First…
Prevention is better than cure: a case study of the abnormalities detection in the chest
Weronika Hryniewska, Piotr Czarnecki, Jakub Wiśniewski +2
Prevention is better than cure. This old truth applies not only to the prevention of diseases but also to the prevention of issues with AI models used in medicine. The source of ma…
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…