2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets. - Xiaoxi Wei; A. Aldo Faisal; Moritz Grosse-Wentrup; Alexandre Gramfort; Sylvain Chevallier; Vinay Jayaram; Camille Jeunet; Stylianos Bakas; Siegfried Ludwig; Konstantinos Barmpas; Mehdi Bahri; Yannis Panagakis; et al. (NeurIPS (Competition and Demos), 2021)

n-CPS: Generalising Cross Pseudo Supervision to n networks for Semi-Supervised Semantic Segmentation. - Dominik Filipiak; Piotr Tempczyk; Marek Cygan (CoRR, 2021)

LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood. - Piotr Tempczyk; Rafal Michaluk; Lukasz Garncarek; Przemyslaw Spurek; Jacek Tabor; Adam Golinski (ICML, 2022)

One Simple Trick to Fix Your Bayesian Neural Network. - Piotr Tempczyk; Ksawery Smoczynski; Philip Smolenski-Jensen; Marek Cygan (CoRR, 2022)

Polite Teacher: Semi-Supervised Instance Segmentation With Mutual Learning and Pseudo-Label Thresholding. - Dominik Filipiak; Andrzej Zapala; Piotr Tempczyk; Anna Fensel; Marek Cygan (IEEE Access, 2024)

A Wiener Process Perspective on Local Intrinsic Dimension Estimation Methods. - Piotr Tempczyk; Lukasz Garncarek; Dominik Filipiak; Adam Kurpisz (AAAI, 2025)