Publications

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L
Legenstein, R., H. Markram, and W. Maass, "Input prediction and autonomous movement analysis in recurrent circuits of spiking neurons", Reviews in the Neurosciences (Special Issue on Neuroinformatics of Neural and Artificial Computation), vol. 14, no. 1-2, pp. 5-19, 2003. Abstract
Li, J., and H. Jaeger, "Minimal Energy Control of an ESN Pattern Generator", Jacobs University Technical Report, no. 26: Jacobs University Bremen, 2011. Abstract
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., 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., Echo state networks with trained feedbacks, , no. 4: Jacobs University Bremen, February, 2007.
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., and V. Marozas, "Noninvasive Fetal QRS Detection using Echo State Network", Computing in Cardiology 2013, vol. 40, Zaragoza, Spain, pp. 205-208, 2013.  Download: FQRS_ESN.pdf (252.39 KB)
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., "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)
M
Maass, W., "Liquid Computing", Computability in Europe 2007 - CiE'07: Springer (Berlin), 2007. Abstract
Maass, W., P. Joshi, and E. D. Sontag, "Principles of real-time computing with feedback applied to cortical microcircuit models", NIPS 2005: Advances in Neural Information Processing Systems, vol. 18, Cambridge, MA, MIT Press, pp. 835–842, 2006, 2005. Abstract
Maass, W., "On the computational power of neural microcircuit models: Pointers to the literature", International Conference on Artificial Neural Networks - ICANN 2002, vol. 2415: Springer, pp. 254-256, 2002.
Maass, W., T. Natschlaeger, and H. Markram, "A model for real-time computation in generic neural microcircuits", NIPS 2002: Advances in Neural Information Processing Systems, vol. 15: MIT Press, pp. 213–220, 2003, 2002. Abstract
Maass, W., R. Legenstein, and H. Markram, "A new approach towards vision suggested by biologically realistic neural microcircuit models", Biologically Motivated Computer Vision BMCV 2002, vol. 2525: Springer, pp. 282-293, 2002. Abstract
Maass, W., and H. Markram, "On the computational power of recurrent circuits of spiking neurons", Journal of Computer and System Sciences, vol. 69, no. 4, pp. 593-616, 2004. Abstract