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ORCIDMichal Cernanský
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2000 – 2009
- 2009
[c8]Daniela Chudá, Martin Nehéz, Michal Cernanský
:
On using of random access machine simulators in teaching of theoretical computer science. CompSysTech 2009: 84- [c7]Michal Cernanský:
Training Recurrent Neural Network Using Multistream Extended Kalman Filter on Multicore Processor and Cuda Enabled Graphic Processor Unit. ICANN (1) 2009: 381-390 - 2008
- [c6]Michal Cernanský, Peter Tiño:
Predictive Modeling with Echo State Networks. ICANN (1) 2008: 778-787 - [c5]Michal Cernanský, Lubica Benusková:
Training Recurrent Connectionist Models on Symbolic Time Series. ICONIP (1) 2008: 285-292 - [c4]Michal Cernanský, Matej Makula, Lubica Benusková:
Improving the State Space Organization of Untrained Recurrent Networks. ICONIP (1) 2008: 671-678 - 2007
- [j3]Michal Cernanský, Matej Makula, Lubica Benusková:
Organization of the state space of a simple recurrent network before and after training on recursive linguistic structures. Neural Networks 20(2): 236-244 (2007) - [c3]Michal Cernanský, Peter Tiño:
Comparison of Echo State Networks with Simple Recurrent Networks and Variable-Length Markov Models on Symbolic Sequences. ICANN (1) 2007: 618-627 - 2004
- [j2]Peter Tiño, Michal Cernanský, Lubica Benusková:
Markovian architectural bias of recurrent neural networks. IEEE Trans. Neural Networks 15(1): 6-15 (2004) - [c2]Matej Makula, Michal Cernanský, Lubica Benusková:
Approaches Based on Markovian Architectural Bias in Recurrent Neural Networks. SOFSEM 2004: 257-264 - 2003
- [j1]Karel Král, P. Zdenek, Z. Khás, Michal Cernanský:
Optical spectra of quantum dot aggregates in sub-wetting layer region. Microelectron. J. 34(5-8): 583-585 (2003) - 2001
- [c1]Michal Cernanský, Lubica Benusková:
Finite-State Reber Automaton and the Recurrent Neural Networks Trained in Supervised and Unsupervised Manner. ICANN 2001: 737-742
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