Publications

Export 13 results:
Sort by: [ Author (Asc)] Title Type Year
Filters: Author is Jaeger, Herbert  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
J
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., "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., Adaptive nonlinear system identification with echo state networks, : MIT Press Cambridge, MA, pp. 593–600, 2003.
Jaeger, H., "Echo state network", Scholarpedia, vol. 2, no. 9, pp. 2330, 2007.
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.
Jaeger, H., "Short term memory in echo state networks", GMD Report 152: German National Research Center for Information Technology, 2001.
Jaeger, H., Discovering multiscale dynamical features with hierarchical Echo State Networks, : Jacobs University Bremen, 2007.
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.
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.
L
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., 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., 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., D. Popovici, H. Jaeger, and U. Siewert, Time warping invariant echo state networks, , no. 2: Jacobs University Bremen, May, 2006.