activity
20142023
most citedProPaLL: Probabilistic Partial Label Learning

1 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV20231 cited

MeVGAN: GAN-based Plugin Model for Video Generation with Applications in Colonoscopy

Łukasz Struski, Tomasz Urbańczyk, Krzysztof Bucki +4

Video generation is important, especially in medicine, as much data is given in this form. However, video generation of high-resolution data is a very demanding task for generative…

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.LG20231 cited

r-softmax: Generalized Softmax with Controllable Sparsity Rate

Klaudia Bałazy, Łukasz Struski, Marek Śmieja +1

Nowadays artificial neural network models achieve remarkable results in many disciplines. Functions mapping the representation provided by the model to the probability distribution…

cs.LG20221 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,…

math.DS2014

On rigorous estimates of eigenspaces and eigenvalues of a matrix

Łukasz Struski, Jacek Tabor, Piotr Zgliczyński

We present a method of cones for rigorous estimations of eigenvectors, eigenspaces and eigenvalues of a matrix. The key notion is the cone-domination and is inspired by ideas from…