1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CV2023
Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations
Mikołaj Sacha, Bartosz Jura, Dawid Rymarczyk +3
Prototypical parts-based networks are becoming increasingly popular due to their faithful self-explanations. However, their similarity maps are calculated in the penultimate networ…
cs.LG2022★ 1 cited
ProPaLL: Probabilistic Partial Label Learning
Łukasz Struski, Jacek Tabor, Bartosz Zieliński
Partial label learning is a type of weakly supervised learning, where each training instance corresponds to a set of candidate labels, among which only one is true. In this paper,…