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Dawid Rymarczyk
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2020 – today
- 2024
- [c14]Mikolaj Sacha, Bartosz Jura
, Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski:
Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations. AAAI 2024: 21563-21573 - [c13]Szymon Oplatek, Dawid Rymarczyk
Revisiting FunnyBirds Evaluation Framework for Prototypical Parts Networks. xAI (1) 2024: 57-68 - [i15]Mateusz Pach, Dawid Rymarczyk, Koryna Lewandowska, Jacek Tabor, Bartosz Zielinski:
LucidPPN: Unambiguous Prototypical Parts Network for User-centric Interpretable Computer Vision. CoRR abs/2405.14331 (2024) - [i14]Szymon Oplatek, Dawid Rymarczyk, Bartosz Zielinski:
Revisiting FunnyBirds evaluation framework for prototypical parts networks. CoRR abs/2408.11401 (2024) - 2023
- [j1]Adriana Borowa
Identifying Bacteria Species on Microscopic Polyculture Images Using Deep Learning. IEEE J. Biomed. Health Informatics 27(1): 121-130 (2023) - [c12]Adam Pardyl
CompLung: Comprehensive Computer-Aided Diagnosis of Lung Cancer. ECAI 2023: 1835-1842 - [c11]Lukasz Struski
ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging. ECAI 2023: 2210-2217 - [c10]Dawid Rymarczyk, Joost van de Weijer, Bartosz Zielinski, Bartlomiej Twardowski:
ICICLE: Interpretable Class Incremental Continual Learning. ICCV 2023: 1887-1898 - [c9]Dawid Rymarczyk, Daniel Dobrowolski, Tomasz Danel
ProGReST: Prototypical Graph Regression Soft Trees for Molecular Property Prediction. SDM 2023: 379-387 - [c8]Mikolaj Sacha, Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski:
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts. WACV 2023: 1481-1492 - [i13]Mikolaj Sacha, Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski:
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts. CoRR abs/2301.12276 (2023) - [i12]Dawid Rymarczyk, Joost van de Weijer, Bartosz Zielinski, Bartlomiej Twardowski:
ICICLE: Interpretable Class Incremental Continual Learning. CoRR abs/2303.07811 (2023) - [i11]Lukasz Struski, Dawid Rymarczyk, Arkadiusz Lewicki, Robert Sabiniewicz, Jacek Tabor, Bartosz Zielinski:
ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging. CoRR abs/2306.10535 (2023) - [i10]Mikolaj Sacha, Bartosz Jura, Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski:
Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations. CoRR abs/2308.08162 (2023) - [i9]Jan Olszewski, Dawid Rymarczyk, Piotr Wójcik, Mateusz Pach, Bartosz Zielinski:
Token Recycling for Efficient Sequential Inference with Vision Transformers. CoRR abs/2311.15335 (2023) - 2022
- [c7]Dawid Rymarczyk
Interpretable Image Classification with Differentiable Prototypes Assignment. ECCV (12) 2022: 351-368 - [c6]Adam Pardyl
Automating Patient-Level Lung Cancer Diagnosis in Different Data Regimes. ICONIP (7) 2022: 13-24 - [c5]Dawid Rymarczyk
ProtoMIL: Multiple Instance Learning with Prototypical Parts for Whole-Slide Image Classification. ECML/PKDD (1) 2022: 421-436 - [i8]Dawid Rymarczyk, Daniel Dobrowolski, Tomasz Danel:
ProGReST: Prototypical Graph Regression Soft Trees for Molecular Property Prediction. CoRR abs/2210.03745 (2022) - 2021
- [c4]Adriana Borowa
Deep learning classification of bacteria clones explained by persistence homology. IJCNN 2021: 1-8 - [c3]Dawid Rymarczyk
ProtoPShare: Prototypical Parts Sharing for Similarity Discovery in Interpretable Image Classification. KDD 2021: 1420-1430 - [c2]Dawid Rymarczyk
Comparison of Supervised and Self-Supervised Deep Representations Trained on Histological Images. MedInfo 2021: 1052-1053 - [c1]Dawid Rymarczyk, Adriana Borowa, Jacek Tabor, Bartosz Zielinski:
Kernel Self-Attention for Weakly-supervised Image Classification using Deep Multiple Instance Learning. WACV 2021: 1720-1729 - [i7]Dawid Rymarczyk, Aneta Kaczynska, Jaroslaw Kraus, Adam Pardyl, Bartosz Zielinski:
ProtoMIL: Multiple Instance Learning with Prototypical Parts for Fine-Grained Interpretability. CoRR abs/2108.10612 (2021) - [i6]Dawid Rymarczyk, Lukasz Struski, Michal Górszczak, Koryna Lewandowska, Jacek Tabor, Bartosz Zielinski:
Interpretable Image Classification with Differentiable Prototypes Assignment. CoRR abs/2112.02902 (2021) - 2020
- [i5]Bartosz Zielinski, Agnieszka Sroka-Oleksiak, Dawid Rymarczyk, Adam Piekarczyk, Monika Brzychczy-Wloch:
Deep learning approach to describe and classify fungi microscopic images. CoRR abs/2005.11772 (2020) - [i4]Dawid Rymarczyk, Jacek Tabor, Bartosz Zielinski:
Kernel Self-Attention in Deep Multiple Instance Learning. CoRR abs/2005.12991 (2020) - [i3]Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski:
ProtoPShare: Prototype Sharing for Interpretable Image Classification and Similarity Discovery. CoRR abs/2011.14340 (2020) - [i2]Adriana Borowa, Dawid Rymarczyk, Dorota Ochonska, Monika Brzychczy-Wloch, Bartosz Zielinski:
Classifying bacteria clones using attention-based deep multiple instance learning interpreted by persistence homology. CoRR abs/2012.01189 (2020)
2010 – 2019
- 2019
- [i1]Bartosz Zielinski, Agnieszka Sroka-Oleksiak, Dawid Rymarczyk, Adam Piekarczyk, Monika Brzychczy-Wloch:
Deep learning approach to description and classification of fungi microscopic images. CoRR abs/1906.09449 (2019)
Coauthor Index
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