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cs.CV2024
InfoDisent: Explainability of Image Classification Models by Information Disentanglement
Łukasz Struski, Dawid Rymarczyk, Jacek Tabor
In this work, we introduce InfoDisent, a hybrid approach to explainability based on the information bottleneck principle. InfoDisent enables the disentanglement of information in t…
cs.CV2024★ 1 cited
LucidPPN: Unambiguous Prototypical Parts Network for User-centric Interpretable Computer Vision
Mateusz Pach, Dawid Rymarczyk, Koryna Lewandowska +2
Prototypical parts networks combine the power of deep learning with the explainability of case-based reasoning to make accurate, interpretable decisions. They follow the this looks…