82 citations · 92 across the 8 of their papers we have counts for
8 papers
Prof-K: Probabilistic One-Pass Filtering for Efficient Top-k Selection
Tadeusz Dziarmaga, Witold Sikora, Łukasz Struski +2
Top-k selection is a fundamental computational primitive with applications spanning databases, information retrieval, signal processing, and modern machine learning workloads, incl…
Fast LapSum: Exact Differentiable Top- at Million Scale
Łukasz Struski, Joanna Wojciechowicz, Jakub Antczak +3
Selecting the top- elements is a fundamental operation for inducing sparsity in large-scale models and optimization problems, enabling robust expert activation, token routing or…
LaPrune: Controllable Differentiable Sparsity at Million Scale
Jakub Antczak, Joanna Wojciechowicz, Łukasz Struski +1
Top- selection determines which components of a sparse model remain active. Hard selection blocks gradients, while continuous relaxations often couple mask hardness to the selec…
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…
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts
Mikołaj Sacha, Dawid Rymarczyk, Łukasz Struski +2
We introduce ProtoSeg, a novel model for interpretable semantic image segmentation, which constructs its predictions using similar patches from the training set. To achieve accurac…
SONG: Self-Organizing Neural Graphs
Łukasz Struski, Tomasz Danel, Marek Śmieja +2
Recent years have seen a surge in research on deep interpretable neural networks with decision trees as one of the most commonly incorporated tools. There are at least three advant…
ProtoPShare: Prototype Sharing for Interpretable Image Classification and Similarity Discovery
Dawid Rymarczyk, Łukasz Struski, Jacek Tabor +1
In this paper, we introduce ProtoPShare, a self-explained method that incorporates the paradigm of prototypical parts to explain its predictions. The main novelty of the ProtoPShar…
OneFlow: One-class flow for anomaly detection based on a minimal volume region
Łukasz Maziarka, Marek Śmieja, Marcin Sendera +3
We propose OneFlow - a flow-based one-class classifier for anomaly (outlier) detection that finds a minimal volume bounding region. Contrary to density-based methods, OneFlow is co…