| Markovian architectural bias of recurrent neural networks P Tino, M Cernansky, L Benusková IEEE Transactions on Neural Networks 15 (1), 6-15, 2004 | 212 | 2004 |
| Simple recurrent network trained by RTRL and extended Kalman filter algorithms M Cernansky Neural Network World 13 (3), 223-234, 2003 | 46 | 2003 |
| Performance evaluations of IPTables firewall solutions under DDoS attacks M Šimon, L Huraj, M Čerňanský Journal of Applied Mathematics, Statistics and Informatics 11 (2), 35-45, 2015 | 42 | 2015 |
| Predictive modeling with echo state networks M Čerňanský, P Tiňo International Conference on Artificial Neural Networks, 778-787, 2008 | 38 | 2008 |
| Feed-forward echo state networks M Cernansky, M Makula Proceedings. 2005 IEEE International Joint Conference on Neural Networks
, 2005 | 31 | 2005 |
| Organization of the state space of a simple recurrent network before and after training on recursive linguistic structures M Čerňanský, M Makula, Ľ Beňušková Neural Networks 20 (2), 236-244, 2007 | 30 | 2007 |
| Training recurrent neural network using multistream extended Kalman filter on multicore processor and CUDA enabled graphic processor unit M Čerňanský International Conference on Artificial Neural Networks, 381-390, 2009 | 22 | 2009 |
| Comparison of echo state networks with simple recurrent networks and variable-length Markov models on symbolic sequences M Čerňanský, P Tiňo International Conference on Artificial Neural Networks, 618-627, 2007 | 15 | 2007 |
| On using of Turing machine simulators in teaching of theoretical computer science M Čerňanský, M Nehéz, D Chudá, I Polický Aplimat-Journal of Applied Methematics 1, 301-312, 2008 | 6 | 2008 |
| Approaches based on Markovian architectural bias in recurrent neural networks M Makula, M Čerňanský, Ľ Beňušková SOFSEM 2004: Theory and Practice of Computer Science: 30th Conference on
, 2004 | 5 | 2004 |
| Processing Symbolic Sequences by Recurrent Neural Networks Trained by Kalman Filter-Based Algorithms M Cernanský, M Makula, L Benušková SOFSEM, 2004 | 5 | 2004 |
| Finite-state Reber automaton and the recurrent neural networks trained in supervised and unsupervised manner M Cernansky, L Benusková Lecture Notes in Computer Science (см. в книгах) 2130, 0737-0737, 2001 | 4 | 2001 |
| P.: ext Correction Using Approaches Based on Markovian Architectural Bias M Cernanský, M Makula, P Trebatický, P Lacko Proceedings of the 10th International Conference on Engineering Applications
, 2007 | 3 | 2007 |
| On using of random access machine simulators in teaching of theoretical computer science D Chudá, M Nehéz, M Čerňanský Proceedings of the International Conference on Computer Systems and
, 2009 | 2 | 2009 |
| Improving the state space organization of untrained recurrent networks M Čerňanský, M Makula, Ľ Beňušková International Conference on Neural Information Processing, 671-678, 2008 | 2 | 2008 |
| Controlled DDoS attack on IPv4/IPv6 network using distributed computing infrastructure M Čerňanský, L Huraj, M Šimon Journal of Information and Organizational Sciences 44 (2), 297-316, 2020 | 1 | 2020 |
| Processing Symbolic Sequences Using Echo-State Networks M Cernansky, P Tino, RM French, E Thomas NCPW10: Tenth Neural Computation and Psychology Workshop, 2008 | 1 | 2008 |
| Processing Symbolic Sequences Using Echo-State Networks M ČERŇANSKÝ, P TIŇO From Associations To Rules: Connectionist Models of Behavior and Cognition
, 2008 | 1 | 2008 |
| Finite-State Reber Automaton and the Recurrent Neural Networks Trained in Supervised and Unsupervised Manner M Cerňanský, L Benuškov International Conference on Artificial Neural Networks, 737-742, 2001 | 1 | 2001 |
| Multi-reservoir Echo State Networks with Encoders M Čerňanský, ID Luptáková Computer Science On-line Conference, 480-489, 2022 | | 2022 |
