| Radial-based undersampling for imbalanced data classification M Koziarski Pattern Recognition 102, 107262, 2020 | 235 | 2020 |
| Image recognition with deep neural networks in presence of noise – Dealing with and taking advantage of distortions M Koziarski, B Cyganek Integrated Computer-Aided Engineering 24 (4), 337-349, 2017 | 208 | 2017 |
| Combined cleaning and resampling algorithm for multi-class imbalanced data with label noise M Koziarski, M Woźniak, B Krawczyk Knowledge-Based Systems 204, 106223, 2020 | 175 | 2020 |
| Radial-Based Oversampling for noisy imbalanced data classification M Koziarski, B Krawczyk, M Woźniak Neurocomputing 343, 19-33, 2019 | 171 | 2019 |
| Radial-Based Oversampling for multiclass imbalanced data classification B Krawczyk, M Koziarski, M Woźniak IEEE Transactions on Neural Networks and Learning Systems, 2019 | 142 | 2019 |
| CCR: A Combined Cleaning and Resampling Algorithm for Imbalanced Data Classification M Koziarski, M Woźniak International Journal of Applied Mathematics and Computer Science 27 (4 …, 2017 | 129 | 2017 |
| Impact of Low Resolution on Image Recognition with Deep Neural Networks: An Experimental Study M Koziarski, B Cyganek International Journal of Applied Mathematics and Computer Science 28 (4 …, 2018 | 120 | 2018 |
| CSMOUTE: Combined synthetic oversampling and undersampling technique for imbalanced data classification M Koziarski 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 72 | 2021 |
| Towards foundational models for molecular learning on large-scale multi-task datasets D Beaini, S Huang, JA Cunha, Z Li, G Moisescu-Pareja, O Dymov, ... ICLR 2024, 2023 | 59 | 2023 |
| DiagSet: a dataset for prostate cancer histopathological image classification M Koziarski, B Cyganek, P Niedziela, B Olborski, Z Antosz, M Żydak, ... Scientific Reports 14 (1), 6780, 2024 | 54 | 2024 |
| Potential anchoring for imbalanced data classification M Koziarski Pattern Recognition 120, 108114, 2021 | 52 | 2021 |
| RGFN: Synthesizable Molecular Generation Using GFlowNets M Koziarski, A Rekesh, D Shevchuk, A van der Sloot, P Gaiński, Y Bengio, ... NeurIPS 2024, 2024 | 37 | 2024 |
| Crystal-GFN: sampling crystals with desirable properties and constraints M AI4Science, A Hernandez-Garcia, A Duval, A Volokhova, Y Bengio, ... NeurIPS 2023 Workshop on AI for Accelerated Materials Design, 2023 | 36* | 2023 |
| Radial-based approach to imbalanced data oversampling M Koziarski, B Krawczyk, M Woźniak International Conference on Hybrid Artificial Intelligence Systems, 318-327, 2017 | 34 | 2017 |
| Multicriteria classifier ensemble learning for imbalanced data W Węgier, M Koziarski, M Woźniak IEEE Access 10, 16807-16818, 2022 | 26 | 2022 |
| Towards equilibrium molecular conformation generation with GFlowNets A Volokhova, M Koziarski, A Hernández-García, CH Liu, S Miret, P Lemos, ... Digital Discovery 3 (5), 1038-1047, 2024 | 24 | 2024 |
| Analysis of group evolution prediction in complex networks S Saganowski, P Bródka, M Koziarski, P Kazienko PloS one 14 (10), e0224194, 2019 | 24 | 2019 |
| RB-CCR: radial-based combined cleaning and resampling algorithm for imbalanced data classification M Koziarski, C Bellinger, M Woźniak Machine Learning 110 (11), 3059-3093, 2021 | 23 | 2021 |
| The deterministic subspace method for constructing classifier ensembles M Koziarski, B Krawczyk, M Woźniak Pattern Analysis and Applications 20 (4), 981-990, 2017 | 22 | 2017 |
| Convolutional neural network-based classification of histopathological images affected by data imbalance M Koziarski, B Kwolek, B Cyganek International Conference on Pattern Recognition (ICPR), Workshop on Deep …, 2018 | 21 | 2018 |
Michal WozniakWroclaw University of Science and Technology (Politechnika Wrocławska)Verified email at pwr.edu.pl
