| Molecule attention transformer Ł Maziarka, T Danel, S Mucha, K Rataj, J Tabor, S Jastrzębski arXiv preprint arXiv:2002.08264, 2020 | 213 | 2020 |
| The break-even point on optimization trajectories of deep neural networks S Jastrzebski, M Szymczak, S Fort, D Arpit, J Tabor, K Cho, K Geras arXiv preprint arXiv:2002.09572, 2020 | 177 | 2020 |
| 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 | 161 | 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 | 112* | 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 | 98 | 2021 |
| Hypernetwork functional image representation S Klocek, Ł Maziarka, M Wołczyk, J Tabor, J Nowak, M Śmieja International Conference on Artificial Neural Networks, 496-510, 2019 | 95 | 2019 |
| 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 | 92 | 2022 |
| Cross-entropy clustering J Tabor, P Spurek Pattern Recognition 47 (9), 3046-3059, 2014 | 73 | 2014 |
| Stability of the Cauchy functional equation in quasi-Banach spaces J Tabor Annales Polonici Mathematici 83, 243-255, 2004 | 62 | 2004 |
| On a linear iterative equation J Tabor, J Tabor Results in Mathematics 27, 412-421, 1995 | 60 | 1995 |
| Cramer-wold auto-encoder S Knop, J Tabor, I Podolak, M Mazur Journal of Machine Learning Research 21 (164), 1-28, 2020 | 59* | 2020 |
| Iterative functional equations in the class of Lipschitz functions M Kulczycki, J Tabor Aequationes Mathematicae 64 (1), 24-33, 2002 | 59 | 2002 |
| Kernel self-attention for weakly-supervised image classification using deep multiple instance learning D Rymarczyk, A Borowa, J Tabor, B Zielinski Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021 | 53 | 2021 |
| Takagi functions and approximate midconvexity J Tabor, J Tabor Journal of mathematical analysis and applications 356 (2), 729-737, 2009 | 49 | 2009 |
| Zero time waste: Recycling predictions in early exit neural networks M Wołczyk, B Wójcik, K Bałazy, IT Podolak, J Tabor, M Śmieja, T Trzcinski Advances in Neural Information Processing Systems 34, 2516-2528, 2021 | 43 | 2021 |
| Generalized approximate midconvexity J Tabor, J Tabor Control and Cybernetics 38 (3), 655-669, 2009 | 43 | 2009 |
| Iterative equations in Banach spaces J Tabor, M Żołdak Journal of mathematical analysis and applications 299 (2), 651-662, 2004 | 42 | 2004 |
| Hypernetwork approach to generating point clouds P Spurek, S Winczowski, J Tabor, M Zamorski, M Zięba, T Trzciński arXiv preprint arXiv:2003.00802, 2020 | 40 | 2020 |
| General stability of functional equations of linear type J Tabor, J Tabor Journal of mathematical analysis and applications 328 (1), 192-200, 2007 | 37 | 2007 |
| Generalized RBF kernel for incomplete data M Śmieja, Ł Struski, J Tabor, M Marzec Knowledge-Based Systems 173, 150-162, 2019 | 36 | 2019 |
Przemysław SpurekJagiellonian University, IDEAS NCBRZweryfikowany adres z ii.uj.edu.pl
