| Learning methods for radial basis function networks R Neruda, P Kudová Future Generation Computer Systems 21 (7), 1131-1142, 2005 | 123 | 2005 |
| Clustering genetic algorithm P Kudova 18th International Workshop on Database and Expert Systems Applications …, 2007 | 67 | 2007 |
| Evolving keras architectures for sensor data analysis P Vidnerova, R Neruda 2017 Federated Conference on Computer Science and Information Systems …, 2017 | 43 | 2017 |
| Vulnerability of classifiers to evolutionary generated adversarial examples P Vidnerová, R Neruda Neural Networks 127, 168-181, 2020 | 26 | 2020 |
| Bang 3: A computational multi-agent system R Neruda, P Krusina, P Kudová, P Rydvan, G Beuster Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent …, 2004 | 18 | 2004 |
| Deep networks with rbf layers to prevent adversarial examples P Vidnerová, R Neruda Artificial Intelligence and Soft Computing: 17th International Conference …, 2018 | 14 | 2018 |
| Evolutionary generation of adversarial examples for deep and shallow machine learning models P Vidnerová, R Neruda Proceedings of the The 3rd Multidisciplinary International Social Networks …, 2016 | 14 | 2016 |
| Evolution Strategies for Deep Neural Network Models Design. P Vidnerová, R Neruda ITAT, 159-166, 2017 | 13 | 2017 |
| Sensor data air pollution prediction by kernel models P Vidnerová, R Neruda 2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid …, 2016 | 12 | 2016 |
| Learning errors by radial basis function neural networks and regularization networks R Neruda, P Vidnerovà International Journal of Grid and Distributed Computing 1 (2), 49-58, 2009 | 12 | 2009 |
| RBF-Keras: An RBF Layer for Keras Library. 2019 P Vidnerová URL https://github. com/PetraVidnerova/rbf_keras, 0 | 12* | |
| Comparison of behavior-based and planning techniques on the small robot maze exploration problem S Slušný, R Neruda, P Vidnerová Neural networks 23 (4), 560-567, 2010 | 11 | 2010 |
| Sum and product kernel regularization networks P Kudová, T Šámalová International Conference on Artificial Intelligence and Soft Computing, 56-65, 2006 | 10 | 2006 |
| Comparison of some approaches to clustering categorical data H Rezankova, D Husek, P Kudova, V Snasel Proceedings in Computational Statistics. COMPSTAT, 607-613, 2006 | 9 | 2006 |
| Evolving sum and composite kernel functions for regularization networks P Vidnerová, R Neruda Adaptive and Natural Computing Algorithms: 10th International Conference …, 2011 | 8 | 2011 |
| Performance comparison of relational reinforcement learning and rbf neural networks for small mobile robots R Neruda, S Slusny, P Vidnerova 2008 Second International Conference on Future Generation Communication and …, 2008 | 8 | 2008 |
| Comparison of RBF network learning and reinforcement learning on the maze exploration problem S Slušný, R Neruda, P Vidnerová International Conference on Artificial Neural Networks, 720-729, 2008 | 8 | 2008 |
| Hybrid learning of RBF networks R Neruda, P Kudová International Conference on Computational Science, 594-603, 2002 | 8 | 2002 |
| Delays, masks, the elderly, and schools: First covid-19 wave in the czech republic L Berec, J Smyčka, R Levínský, E Hromádková, M Šoltés, J Šlerka, ... Bulletin of mathematical biology 84 (8), 75, 2022 | 7 | 2022 |
| Effective automatic method selection for nonlinear regression modeling J Kalina, A Neoral, P Vidnerová International Journal of Neural Systems 31 (10), 2150020, 2021 | 7 | 2021 |
