| Processing of missing data by neural networks M Śmieja, Ł Struski, J Tabor, B Zieliński, P Spurek Advances in neural information processing systems 31, 2018 | 146 | 2018 |
| Spatial graph convolutional networks T Danel, P Spurek, J Tabor, M Śmieja, Ł Struski, A Słowik, Ł Maziarka International Conference on Neural Information Processing, 668-675, 2020 | 84* | 2020 |
| Protopshare: Prototypical parts sharing for similarity discovery in interpretable image classification D Rymarczyk, Ł Struski, J Tabor, B Zieliński Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 71 | 2021 |
| Interpretable image classification with differentiable prototypes assignment D Rymarczyk, Ł Struski, M Górszczak, K Lewandowska, J Tabor, ... European Conference on Computer Vision, 351-368, 2022 | 64 | 2022 |
| A classification-based approach to semi-supervised clustering with pairwise constraints M Śmieja, Ł Struski, MAT Figueiredo Neural Networks 127, 193-203, 2020 | 40 | 2020 |
| Generalized RBF kernel for incomplete data M Śmieja, Ł Struski, J Tabor, M Marzec Knowledge-Based Systems 173, 150-162, 2019 | 32 | 2019 |
| Protopshare: Prototype sharing for interpretable image classification and similarity discovery D Rymarczyk, Ł Struski, J Tabor, B Zieliński arXiv preprint arXiv:2011.14340, 2020 | 20 | 2020 |
| Lossy compression approach to subspace clustering Ł Struski, J Tabor, P Spurek Information Sciences 435, 161-183, 2018 | 18 | 2018 |
| Protoseg: Interpretable semantic segmentation with prototypical parts M Sacha, D Rymarczyk, Ł Struski, J Tabor, B Zieliński Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 16 | 2023 |
| Pharmacoprint: a combination of a pharmacophore fingerprint and artificial intelligence as a tool for Computer-aided drug design D Warszycki, Ł Struski, M Smieja, R Kafel, R Kurczab Journal of chemical information and modeling 61 (10), 5054-5065, 2021 | 16 | 2021 |
| Hyperpocket: Generative point cloud completion P Spurek, A Kasymov, M Mazur, D Janik, SK Tadeja, J Tabor, T Trzciński 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022 | 13 | 2022 |
| Estimating conditional density of missing values using deep gaussian mixture model M Przewięźlikowski, M Śmieja, Ł Struski Neural Information Processing: 27th International Conference, ICONIP 2020 …, 2020 | 11 | 2020 |
| Iterative imputation of missing data using auto-encoder dynamics M Śmieja, M Kołomycki, Ł Struski, M Juda, MAT Figueiredo International Conference on Neural Information Processing, 258-269, 2020 | 9 | 2020 |
| Locogan—locally convolutional gan Ł Struski, S Knop, P Spurek, W Daniec, J Tabor Computer Vision and Image Understanding 221, 103462, 2022 | 8 | 2022 |
| Virtual reality-based parallel coordinates plots enhanced with explainable ai and data-science analytics for decision-making processes S Bobek, SK Tadeja, Ł Struski, P Stachura, T Kipouros, J Tabor, ... Applied Sciences 12 (1), 331, 2021 | 8 | 2021 |
| Semi-supervised model-based clustering with controlled clusters leakage M Śmieja, Ł Struski, J Tabor Expert Systems with Applications 85, 146-157, 2017 | 7 | 2017 |
| ProMIL: Probabilistic multiple instance learning for medical imaging Ł Struski, D Rymarczyk, A Lewicki, R Sabiniewicz, J Tabor, B Zieliński arXiv preprint arXiv:2306.10535, 2023 | 4 | 2023 |
| MisConv: Convolutional Neural Networks for Missing Data M Przewięźlikowski, M Śmieja, Ł Struski, J Tabor Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | 4 | 2022 |
| Processing of incomplete images by (graph) convolutional neural networks T Danel, M Śmieja, Ł Struski, P Spurek, Ł Maziarka International Conference on Neural Information Processing, 512-523, 2020 | 4 | 2020 |
| Can auto-encoders help with filling missing data? M Śmieja, M Kołomycki, Ł Struski, M Juda, MAT Figueiredo ICLR 2020 Workshop on Integration of Deep Neural Models and Differential …, 2020 | 4 | 2020 |
Jacek TaborProfesor informatyki, Uniwersytet JagiellońskiZweryfikowany adres z ii.uj.edu.pl
