Publications

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Conference Proceedings
Jaeger, H., Adaptive nonlinear system identification with echo state networks, : MIT Press Cambridge, MA, pp. 593–600, 2003.
Jaeger, H., "Adaptive nonlinear system identification with echo state networks", In: Advances in Neural Information Processing Systems: MIT Press, Cambridge, MA, , pp. 593-600, 2003, 2002.
Journal Article
Jaeger, H., "Echo state network", Scholarpedia, vol. 2, no. 9, pp. 2330, 2007.
Jaeger, H., and H. Haas, "Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless telecommunication", Science, vol. 304, no. 5667, pp. 78–80, April 2, 2004.
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.
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., 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)
Report
Jaeger, H., Discovering multiscale dynamical features with hierarchical Echo State Networks, : Jacobs University Bremen, 2007.
Li, J., and H. Jaeger, "Minimal Energy Control of an ESN Pattern Generator", Jacobs University Technical Report, no. 26: Jacobs University Bremen, 2011. Abstract
Jaeger, H., "Short term memory in echo state networks", GMD Report 152: German National Research Center for Information Technology, 2001.
Lukoševičius, M., D. Popovici, H. Jaeger, and U. Siewert, Time warping invariant echo state networks, , no. 2: Jacobs University Bremen, May, 2006.
Jaeger, H., "Tutorial on training recurrent neural networks, covering {BPTT}, {RTRL}, {EKF} and the ``echo state network'' approach", GMD Report 159: German National Research Center for Information Technology, pp. 48 pp., 2002.
Jaeger, H., "The ``echo state'' approach to analysing and training recurrent neural networks - with an Erratum note", GMD Report 148: German National Research Center for Information Technology, 2001.