Publications

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Daukantas, S., M. Lukoševičius, V. Marozas, and A. Lukoševičius, "Comparison of ``black box'' and ``gray box'' methods for lost data reconstruction in multichannel signals", Proceedings of the 14th International Conference ``Biomedical Engineering'', Kaunas, pp. 135-138, 2010.
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Jaeger, H., M. Lukoševičius, D. Popovici, and U. Siewert, "Optimization and applications of echo state networks with leaky-integrator neurons", Neural Networks, vol. 20, no. 3, pp. 335-352, 2007.
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Lukoševičius, M., and H. Jaeger, "Reservoir computing approaches to recurrent neural network training", Computer Science Review , vol. 3, no. 3, pp. 127-149, August, 2009.
Lukoševičius, M., "A practical guide to applying echo state networks", Neural Networks: Tricks of the Trade, 2, vol. 7700: Springer Berlin Heidelberg, pp. 659-686, 2012.  Download: PracticalESN.pdf (624.47 KB)
Lukoševičius, M., "Reservoir Computing and Self-Organized Neural Hierarchies", School of Engineering and Science, vol. PhD: Jacobs University Bremen, 2012. Abstract  Download: Mantas_Lukosevicius_PhD_thesis.pdf (3.13 MB)
Lukoševičius, M., Echo state networks with trained feedbacks, , no. 4: Jacobs University Bremen, February, 2007.
Lukoševičius, M., H. Jaeger, and B. Schrauwen, "Reservoir Computing Trends", KI - Künstliche Intelligenz, pp. 1-7, 05/2012. Abstract  Download: KI_reservoir_computing.pdf (574.71 KB)
Lukoševičius, M., On self-organizing reservoirs and their hierarchies, , no. 25: Jacobs University Bremen, October, 2010.
Lukoševičius, M., D. Popovici, H. Jaeger, and U. Siewert, Time warping invariant echo state networks, , no. 2: Jacobs University Bremen, May, 2006.
Lukoševičius, M., "Self-organized reservoirs and their hierarchies", Proceedings of the 22nd International Conference on Artificial Neural Networks (ICANN 2012), vol. 7553, Lausanne, Switzerland, Springer, pp. 587-595, 2012.  Download: Self-organized_reservoir_hierarchies_ICANN12.pdf (315.2 KB)