On Latent Distributions Without Finite Mean in Generative Models. - Damian Lesniak; Igor Sieradzki; Igor T. Podolak (CoRR, 2018)

Distribution-Interpolation Trade off in Generative Models. - Damian Lesniak; Igor Sieradzki; Igor T. Podolak (ICLR (Poster), 2019)

Development of New Methods Needs Proper Evaluation - Benchmarking Sets for Machine Learning Experiments for Class A GPCRs. - Damian Lesniak; Sabina Podlewska; Stanislaw Jastrzebski; Igor Sieradzki; Andrzej J. Bojarski; Jacek Tabor (J. Chem. Inf. Model., 2019)

Explaining Self-Supervised Image Representations with Visual Probing. - Dominika Basaj; Witold Oleszkiewicz; Igor Sieradzki; Michal Górszczak; Barbara Rychalska; Tomasz Trzcinski; Bartosz Zielinski 001 (IJCAI, 2021)

The Monad Platform - Temporal Aspects in Behavioral Modeling. - Barbara Rychalska; Igor Sieradzki; Jacek Dabrowski 004 (ECAI, 2023)

Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations. - Witold Oleszkiewicz; Dominika Basaj; Igor Sieradzki; Michal Górszczak; Barbara Rychalska; Koryna Lewandowska; Tomasz Trzcinski; Bartosz Zielinski 001 (IEEE Access, 2023)

Classification of ROI-based fMRI data in short-term memory tasks using discriminant analysis and neural networks. - Magdalena Fafrowicz; Marcin Tutajewski; Igor Sieradzki; Jeremi K. Ochab; Anna Ceglarek-Sroka; Koryna Lewandowska; Tadeusz Marek; Barbara Sikora-Wachowicz; Igor T. Podolak; Pawel Oswiecimka (Frontiers Neuroinformatics, 2024)