Facial component extraction and face recognition with support vector machines D Xi, IT Podolak, SW Lee Proceedings of Fifth IEEE International Conference on Automatic Face Gesture …, 2002 | 74 | 2002 |
Cramer-Wold auto-encoder S Knop, P Spurek, J Tabor, I Podolak, M Mazur, S Jastrzebski The Journal of Machine Learning Research 21 (1), 6594-6621, 2020 | 59* | 2020 |
Hierarchical classifier with overlapping class groups IT Podolak Expert Systems with Applications 34 (1), 673-682, 2008 | 43 | 2008 |
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 | 42 | 2021 |
Relative molecule self-attention transformer Ł Maziarka, D Majchrowski, T Danel, P Gaiński, J Tabor, I Podolak, ... Journal of Cheminformatics 16 (1), 3, 2024 | 27 | 2024 |
Machine learning with known input data uncertainty measure WM Czarnecki, IT Podolak IFIP International Conference on Computer Information Systems and Industrial …, 2013 | 25 | 2013 |
Docking-based generative approaches in the search for new drug candidates T Danel, J Łęski, S Podlewska, IT Podolak Drug Discovery Today 28 (2), 103439, 2023 | 24 | 2023 |
Machine Learning-Based Identification of Suicidal Risk in Patients With Schizophrenia Using Multi-Level Resting-State fMRI Features B Bohaterewicz, B Wójcik, A Sobczak, T Marek Frontiers in Neuroscience, 2021 | 23 | 2021 |
Distribution-interpolation trade off in generative models D Leśniak, I Sieradzki, I Podolak International Conference on Learning Representations, 2018 | 21 | 2018 |
Functional graph model of a neural network IT Podolak IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 28 …, 1998 | 20 | 1998 |
Latent translation: Crossing modalities by bridging generative models Y Tian, J Engel arXiv preprint arXiv:1902.08261, 2019 | 19 | 2019 |
A machine learning approach to synchronization of automata I Podolak, A Roman, M Szykuła, B Zieliński Expert Systems with Applications 97, 357-371, 2018 | 15 | 2018 |
Discovering structure in geographical metadata I Podolak, U Demšar Proceedings of the 12th conference in Geoinformatics, 1-7, 2004 | 14 | 2004 |
Generative models with kernel distance in data space S Knop, M Mazur, P Spurek, J Tabor, I Podolak Neurocomputing 487, 119-129, 2022 | 12 | 2022 |
Theoretical foundations and experimental results for a hierarchical classifier with overlapping clusters IT Podolak, A Roman Computational Intelligence 29 (2), 357-388, 2013 | 12 | 2013 |
CORES: fusion of supervised and unsupervised training methods for a multi-class classification problem IT Podolak, A Roman Pattern Analysis and Applications 14, 395-413, 2011 | 11 | 2011 |
Hierarchical estimator S Brodowski, IT Podolak Expert Systems with Applications 38 (10), 12237-12248, 2011 | 11 | 2011 |
Hierarchical classifier IT Podolak, S Biel, M Bobrowski International Conference on Parallel Processing and Applied Mathematics, 591-598, 2005 | 10 | 2005 |
Decoding working memory-related information from repeated psychophysiological EEG experiments using convolutional and contrastive neural networks J Żygierewicz, RA Janik, IT Podolak, A Drozd, U Malinowska, ... Journal of Neural Engineering 19 (4), 046053, 2022 | 9 | 2022 |
A hierarchical classifier with growing neural gas clustering IT Podolak, K Bartocha Adaptive and Natural Computing Algorithms: 9th International Conference …, 2009 | 9 | 2009 |