My contribution to the scientific community.
2024
- Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations Mikołaj Sacha, Bartosz Jura, Dawid Rymarczyk, Łukasz Struski, Jacek Tabor, Bartosz Zieliński AAAI 2024 LINK
- Decoding Phenotypic Screening: A Comparative Analysis of Image Representations. Adriana Borowa, Dawid Rymarczyk, Marek Żyła, Maciej Kańduła, Ana Sanchez-Fernandez, Łukasz Struski, Jacek Tabor, Bartosz Zieliński Computational and Structural Biotechnology Journal. 2024
- Revisiting FunnyBirds evaluation framework for prototypical parts networks. Szymon Opłatek, Dawid Rymarczyk, Bartosz Zieliński World Conference on eXplainable Artificial Intelligence (xAI). 2024
2023
- ICICLE: Interpretable Class Incremental Continual Learning Dawid Rymarczyk, Joost van de Weijer, Bartosz Zieliński, Bartłomiej Twardowski ICCV 2023 LINK
- Deep learning models capture histological disease activity in Crohn’s Disease and Ulcerative Colitis with high fidelity Dawid Rymarczyk, Weiwei Schultz, Adriana Borowa, Joshua Friedman, Tomasz Danel, Patrick Branigan, Michał Chałupczak, Anna Bracha, Tomasz Krawiec, Michał Warchoł, Katherine Li, Gert De Hertogh, Bartosz Zieliński, Louis R. Ghanem, Aleksandar Stojmirovic Journal of Crohn's and Colitis. 2023.
- CompLung: Comprehensive Computer-Aided Diagnosis of Lung Cancer Adam Pardyl, Dawid Rymarczyk, Joanna Jaworek-Korjakowska, Dariusz Kucharski, Andrzej Brodzicki, Julia Lasek, Zofia Schneider, Iwona Kucybała, Andzrej Urbanik, Rafał Obuchowicz, Zbisław Tabor, Bartosz Zieliński ECAI 2023
- ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging Łukasz Struski, Dawid Rymarczyk, Arkadiusz Lewicki, Robert Sabiniewicz, Jacek Tabor, Bartosz Zieliński ECAI 2023 LINK
- ProGReST: Prototypical Graph Regression Soft Trees for Molecular Property Prediction Dawid Rymarczyk, Daniel Dobrowolski, Tomasz Danel SDM 2023 LINK
- ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts, Mikołaj Sacha, Dawid Rymarczyk, Łukasz Struski, Jacek Tabor, Bartosz Zieliński WACV 2023
2022
- Interpretable image classification with differentiable prototypes assignment Dawid Rymarczyk, Łukasz Struski, Michał Górszczak, Koryna Lewandowska, Jacek Tabor, Bartosz Zieliński ECCV 2022 LINK
- ProtoMIL: Multiple instance learning with prototypical parts for fine-grained interpretability Dawid Rymarczyk, Adam Pardyl, Jarosław Kraus, Aneta Kaczyńska, Marek Skomorowski, Bartosz Zieliński ECML PKDD 2022 LINK
- Identifying bacteria species on microscopic polyculture images using deep learning. Adriana Borowa, Dawid Rymarczyk, Dorota Ochońska, Agnieszka Sroka-Oleksiak, Monika-Brzychczy-Włoch, Bartosz Zieliński IEEE Journal of Biomedical and Health Informatics. LINK
- Automating Patient-Level Lung Cancer Diagnosis in Different Data Regimes. Adam Pardyl, Dawid Rymarczyk, Zbisław Tabor, Bartosz Zieliński ICONIP 2022.
2021
- Comparison of Supervised and Self-Supervised Deep Representations Trained on Histological Images Dawid Rymarczyk, Adriana Borowa, Anna Bracha, Maurycy Chronowski, Bartosz Zieliński MedInfo 2021 LINK
- Protopshare: Prototypical parts sharing for similarity discovery in interpretable image classification Dawid Rymarczyk, Łukasz Struski, Jacek Tabor, Bartosz Zieliński KDD 2021 LINK
- Deep learning classification of bacteria clones explained by persistence homology Adriana Borowa, Dawid Rymarczyk, Dorota Ochońska, Monika Brzychczy-Włoch, Bartosz Zieliński IJCNN 2021 LINK
- Kernel self-attention for weakly-supervised image classification using deep multiple instance learning Dawid Rymarczyk, Adriana Borowa, Jacek Tabor, Bartosz Zieliński WACV 2021 LINK
2020
- Deep learning approach to describe and classify fungi microscopic images Bartosz Zieliński, Agnieszka Sroka-Oleksiak, Dawid Rymarczyk, Adam Piekarczyk, Monika Brzychczy-Włoch PLoS ONE 15 (6) LINK