Most significant publications
- Bartosz Zieliński, Grzegorz Rypeść, Valeriya Khan, Tomasz Trzcinski, Bartłomiej Twardowski, Sebastian Cygert, Divide and not forget: Ensemble of selectively trained experts in Continual Learning, International Conference on Learning Representations [ICLR](MAIN), (2024),
- Dawid Rymarczyk, Łukasz Struski, Michał Górszczak, Koryna Lewandowska, Jacek Tabor, Bartosz Zieliński, Interpretable Image Classification with Differentiable Prototypes Assignment, European Conference on Computer Vision [ECCV](MAIN) Lecture Notes in Computer Science 13672 (2022), 351-368
- Dawid Rymarczyk, Łukasz Struski, Jacek Tabor, Bartosz Zieliński, ProtoPShare: Prototypical Parts Sharing for Similarity Discovery in Interpretable Image Classification, ACM International Conference on Knowledge Discovery and Data Mining [KDD](MAIN) 9781450383325 (2021), 1420-1430
- Marek Śmieja, Łukasz Struski, Jacek Tabor, Bartosz Zieliński, Przemysław Spurek, Processing of missing data by neural networks, Advances in Neural Information Processing Systems 31 (2018), 2719-2729
- Monika Brzychczy-Włoch, Krzysztof Misztal, Dorota Ochońska, Anna Plichta, Przemysław Spurek, Bartosz Zieliński, Deep learning approach to bacterial colony classification, PLoS One 12 (9) (2017), 1-14
Recent publications
- Taras Kutsyk, Honorata Zych, Adam Wróbel, Andrea Bontempelli, Stefano Teso, Andrea Passerini, Bartosz Zieliński, Dawid Rymarczyk, Tailored Reasoning: Human-in-the-Loop for Consistent Prototypical-parts Networks, IEEE Workshop on Applications of Computer Vision [WACV], (2027),
- Adam Pardyl, Dominik Matuszek, Mateusz Przebieracz, Marek Cygan, Bartosz Zieliński, Maciej Wołczyk, FlySearch : exploring how vision-language models explore, Advances in Neural Information Processing Systems [NeurIPS] 38 (2026), 185979-186011
- Adriana Borowa, Bartosz Zieliński, Dawid Rymarczyk, Reducing cost of fluorescent microscopy through dye exclusion, distillation techniques, and deep learning, Scientific Reports (2026),
- Adam Wróbel, Siddhartha Gairola, Jacek Tabor, Bernt Schiele, Bartosz Zieliński, Dawid Rymarczyk, DAVE : Distribution-aware Attribution via ViT Gradient Decomposition, International Conference on Machine Learning [ICML], (2026),
- Bartosz Zieliński, Łukasz Janisiów, Marek Kochańczyk, Tomasz Danel, Enhancing Chemical Explainability Through Counterfactual Masking, National Conference of the American Association for Artificial Intelligence [AAAI](MAIN), (2026),
Interests
deep learning
computer vision
explainable artificial intelligence
medical image analysis
Bartosz Zieliński
academic degree/title Doctor of Science positionresearch and faculty staff member group, university professor
unit
- Division of Applied Computer Science
- Institute of Computer Science and Computational Mathematics
- Group of Machine Learning Research (GMUM)
bartosz.zielinski@uj.edu.pl
www