Dawid Rymarczyk

According to our database, Dawid Rymarczyk authored at least 21 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations.

Mikolaj Sacha, Bartosz Jura, Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Identifying Bacteria Species on Microscopic Polyculture Images Using Deep Learning.

Adriana Borowa, Dawid Rymarczyk, Dorota Ochonska, Agnieszka Sroka-Oleksiak, Monika Brzychczy-Wloch, Bartosz Zielinski

IEEE J. Biomed. Health Informatics, 2023

Token Recycling for Efficient Sequential Inference with Vision Transformers.

Jan Olszewski, Dawid Rymarczyk, Piotr Wójcik, Mateusz Pach, Bartosz Zielinski

CoRR, 2023

ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts.

Mikolaj Sacha, Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

ProGReST: Prototypical Graph Regression Soft Trees for Molecular Property Prediction.

Dawid Rymarczyk, Daniel Dobrowolski, Tomasz Danel

Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

ICICLE: Interpretable Class Incremental Continual Learning.

Dawid Rymarczyk, Joost van de Weijer, Bartosz Zielinski, Bartlomiej Twardowski

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging.

Lukasz Struski, Dawid Rymarczyk, Arkadiusz Lewicki, Robert Sabiniewicz, Jacek Tabor, Bartosz Zielinski

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 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 Kucybala, Andrzej Urbanik, Rafal Obuchowicz, Zbislaw Tabor, Bartosz Zielinski

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2022

ProtoMIL: Multiple Instance Learning with Prototypical Parts for Whole-Slide Image Classification.

Dawid Rymarczyk, Adam Pardyl, Jaroslaw Kraus, Aneta Kaczynska, Marek Skomorowski, Bartosz Zielinski

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Automating Patient-Level Lung Cancer Diagnosis in Different Data Regimes.

Adam Pardyl, Dawid Rymarczyk, Zbislaw Tabor, Bartosz Zielinski

Proceedings of the Neural Information Processing - 29th International Conference, 2022

Interpretable Image Classification with Differentiable Prototypes Assignment.

Dawid Rymarczyk, Lukasz Struski, Michal Górszczak, Koryna Lewandowska, Jacek Tabor, Bartosz Zielinski

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

ProtoMIL: Multiple Instance Learning with Prototypical Parts for Fine-Grained Interpretability.

Dawid Rymarczyk, Aneta Kaczynska, Jaroslaw Kraus, Adam Pardyl, Bartosz Zielinski

CoRR, 2021

Kernel Self-Attention for Weakly-supervised Image Classification using Deep Multiple Instance Learning.

Dawid Rymarczyk, Adriana Borowa, Jacek Tabor, Bartosz Zielinski

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Comparison of Supervised and Self-Supervised Deep Representations Trained on Histological Images.

Dawid Rymarczyk, Adriana Borowa, Anna Bracha, Maurycy Chronowski, Wojciech Ozimek, Bartosz Zielinski

Proceedings of the MEDINFO 2021: One World, One Health - Global Partnership for Digital Innovation, 2021

ProtoPShare: Prototypical Parts Sharing for Similarity Discovery in Interpretable Image Classification.

Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Deep learning classification of bacteria clones explained by persistence homology.

Adriana Borowa, Dawid Rymarczyk, Dorota Ochonska, Monika Brzychczy-Wloch, Bartosz Zielinski

Proceedings of the International Joint Conference on Neural Networks, 2021

2020

Classifying bacteria clones using attention-based deep multiple instance learning interpreted by persistence homology.

Adriana Borowa, Dawid Rymarczyk, Dorota Ochonska, Monika Brzychczy-Wloch, Bartosz Zielinski

CoRR, 2020

ProtoPShare: Prototype Sharing for Interpretable Image Classification and Similarity Discovery.

Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski

CoRR, 2020

Kernel Self-Attention in Deep Multiple Instance Learning.

Dawid Rymarczyk, Jacek Tabor, Bartosz Zielinski

CoRR, 2020

Deep learning approach to describe and classify fungi microscopic images.

Bartosz Zielinski, Agnieszka Sroka-Oleksiak, Dawid Rymarczyk, Adam Piekarczyk, Monika Brzychczy-Wloch

CoRR, 2020

2019

Deep learning approach to description and classification of fungi microscopic images.

Bartosz Zielinski, Agnieszka Sroka-Oleksiak, Dawid Rymarczyk, Adam Piekarczyk, Monika Brzychczy-Wloch

CoRR, 2019