mgr Dawid Rymarczyk
Jednostki:
- Wydział Matematyki i Informatyki UJ
- Instytut Informatyki i Matematyki Komputerowej
- Katedra Uczenia Maszynowego
Publikacje:
11.
Dawid Rymarczyk, Daniel Dobrowolski, Tomasz Danel
ProGReST: Prototypical Graph Regression Soft Trees for Molecular Property Prediction, SIAM International Conference on Data Mining [SDM], (2023),
10.
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts, IEEE Workshop on Applications of Computer Vision [WACV](MAIN), (2023),
9.
Bartosz Zieliński, Adriana Borowa, Dawid Rymarczyk, Dorota Ochońska, Agnieszka Sroka-Oleksiak, Monika Brzychczy-Włoch
8.
Automating Patient-Level Lung Cancer Diagnosis in Different Data Regimes, International Conference on Neural Information Processing [ICONIP](MAIN), (2022),
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.
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), (2022),
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.
ProtoPShare: Prototypical Parts Sharing for Similarity Discovery in Interpretable Image Classification, ACM International Conference on Knowledge Discovery and Data Mining [KDD](MAIN), (2021), 1420-1430
3.
Deep learning classification of bacteria clones explained by persistence homology, IEEE International Joint Conference on Neural Networks [IJCNN], (2021), 1-8
2.
Kernel Self-Attention for Weakly-supervised Image Classification using Deep Multiple Instance Learning, IEEE Workshop on Applications of Computer Vision [WACV], (2021), 1720-1729
1.
Monika Brzychczy-Włoch, Adam Piekarczyk, Dawid Rymarczyk, Agnieszka Sroka-Oleksiak, Bartosz Zieliński