dr inż. Dawid Rymarczyk

Jednostki:

  • Wydział Matematyki i Informatyki UJ
  • Instytut Informatyki i Matematyki Komputerowej
  • Katedra Informatyki Stosowanej

Publikacje:

20.
Bartosz Zieliński, Jan Olszewski, Dawid Rymarczyk, Piotr Wójcik, Mateusz Pach
TORE: Token Recycling in Vision Transformers for Efficient Active Visual Exploration, IEEE Workshop on Applications of Computer Vision [WACV](MAIN), (2025),
19.
Bartosz Zieliński, Szymon Opłatek, Dawid Rymarczyk
Revisiting FunnyBirds Evaluation Framework for Prototypical Parts Networks, Communications in Computer and Information Science vol. 2153 (2024), 57-68
18.
Bartosz Zieliński, Tomasz Michalski, Dawid Rymarczyk, Daniel Barczyk
ProtoNCD: Prototypical Parts for Interpretable Novel Class Discovery, European Symposium on Artificial Neural Networks [ESANN], (2024),
17.
Bartosz Zieliński, Adriana Borowa, Dawid Rymarczyk, Marek Żyła, Marek Kańduła, Ana Sánchez-Fernández, Krzysztof Rataj, Łukasz Struski, Jacek Tabor
Decoding Phenotypic Screening: A Comparative Analysis of Image Representations, Computational and Structural Biotechnology Journal vol. 23 (2024), 1181-1188
16.
Bartosz Zieliński, Mikołaj Sacha, Bartosz Jura, Dawid Rymarczyk, Łukasz Struski, Jacek Tabor
Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations, National Conference of the American Association for Artificial Intelligence [AAAI](MAIN) vol. 38 (19) (2024), 21563 - 21573
15.
Bartosz Zieliński, 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, Louis R. Ghanem, Aleksandar Stojmirovic
Deep learning models capture histological disease activity in Crohn’s Disease and Ulcerative Colitis with high fidelity, Journal of Crohns & Colitis vol. 20 (2023), 1-11
14.
Bartosz Zieliński, Łukasz Struski, Dawid Rymarczyk, Arkadiusz Lewicki, Robert Sabiniewicz, Jacek Tabor
ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging, European Conference on Artificial Intelligence [ECAI] vol. 372 (2023), 2210 - 2217
13.
Bartosz Zieliński, Adam Pardyl, Dawid Rymarczyk, Joanna Jaworek-Korjakowska, Dariusz Kucharski, Andrzej Brodzicki, Julia Lasek, Zofia Schneider, Iwona Kucybała, Andrzej Urbanik, Rafał Obuchowicz, Zbisław Tabor
CompLung: Comprehensive Computer-Aided Diagnosis of Lung Cancer, European Conference on Artificial Intelligence [ECAI] vol. 372 (2023), 1835 - 1842
12.
Bartosz Zieliński, Dawid Rymarczyk, Joost van de Weijer , Bartłomiej Twardowski
ICICLE: Interpretable Class Incremental Continual Learning, IEEE International Conference on Computer Vision [ICCV](MAIN) vol. 2023 (2023), 1887-1898
11.
Dawid Rymarczyk, Daniel Dobrowolski, Tomasz Danel
ProGReST: Prototypical Graph Regression Soft Trees for Molecular Property Prediction, SIAM International Conference on Data Mining [SDM] vol. 978-1-61197-765-3 (2023), 379 - 387
10.
Mikołaj Sacha, Dawid Rymarczyk, Łukasz Struski, Jacek Tabor, Bartosz Zieliński
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts, IEEE Workshop on Applications of Computer Vision [WACV](MAIN) vol. 2023 (2023), 1481-1492
9.
Bartosz Zieliński, Adriana Borowa, Dawid Rymarczyk, Dorota Ochońska, Agnieszka Sroka-Oleksiak, Monika Brzychczy-Włoch
Identifying bacteria species on microscopic polyculture images using deep learning, IEEE Journal of Biomedical and Health Informatics vol. 27 (1) (2023), 121-130
8.
Bartosz Zieliński, Adam Pardyl, Dawid Rymarczyk, Zbisław Tabor
Automating Patient-Level Lung Cancer Diagnosis in Different Data Regimes, International Conference on Neural Information Processing [ICONIP](MAIN) vol. Communications in Computer and Information Science 1794 (2022), 13–24
7.
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) vol. Lecture Notes in Computer Science 13672 (2022), 351-368
6.
Bartosz Zieliński, Dawid Rymarczyk, Aneta Kaczyńska, Jarosław Kraus, Adam Pardyl, Marek Skomorowski
ProtoMIL: Multiple Instance Learning with Prototypical Parts for Whole-Slide Image Classification, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database [ECML PKDD](MAIN) vol. Lecture Notes in Computer Science 13713 (2022), 421-436
5.
Adriana Borowa, Anna Bracha, Maurycy Chronowski, Wojciech Ozimek, Dawid Rymarczyk, Bartosz Zieliński
Comparison of Supervised and Self-supervised Deep Representations Trained on Histological Image, World Congress on Medical and Health Informatics [MEDINFO] vol. Studies in Health Technology and Informatics 290 (2021), 1052-1053
4.
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) vol. 9781450383325 (2021), 1420-1430
3.
Adriana Borowa, Monika Brzychczy-Włoch, Dorota Ochońska, Dawid Rymarczyk, Bartosz Zieliński
Deep learning classification of bacteria clones explained by persistence homology, IEEE International Joint Conference on Neural Networks [IJCNN] vol. 978-1-6654-3900-8 (2021), 1-8
2.
Adriana Borowa, Dawid Rymarczyk, Jacek Tabor, Bartosz Zieliński
Kernel Self-Attention for Weakly-supervised Image Classification using Deep Multiple Instance Learning, IEEE Workshop on Applications of Computer Vision [WACV] vol. 978-1-6654-0477-8 (2021), 1720-1729
1.
Monika Brzychczy-Włoch, Adam Piekarczyk, Dawid Rymarczyk, Agnieszka Sroka-Oleksiak, Bartosz Zieliński
Deep learning approach to describe and classify fungi microscopic images, PLoS One vol. 15(6) (2020), 1-16

Granty (realizowane po maju 2009 roku)