Journals

M. Zhao, H. Jaeger (to appear): Norm Observable Operator Models Neural Computation (Preprint pdf)

M. Zhao, H. Jaeger, M. Thon (to appear): Making The Error Controlling Algorithm of Observable Operator Models Constructive Neural Computation (Preprint pdf)

M. Lukosevicius, H. Jaeger (2009): Reservoir Computing Approaches to Recurrent Neural Network Training Computer Science Review 3(3), 127-149. DOI http://dx.doi.org/10.1016/j.cosrev.2009.03.005 (Preprint pdf)

A. Schönhuth, H. Jaeger (2009): Characterization of ergodic hidden Markov sources. IEEE Transactions on Information Theory, 55(5), 2107-2118. (Preprint pdf)

M. Zhao, H. Jaeger, M. Thon (2009): A Bound on Modeling Error in Observable Operator Models and an Associated Learning Algorithm. Neural Computation, posted online 6/2009, doi:10.1162/neco.2009.01-08-6fi87. (Preprint pdf)

H. Jaeger, M. Lukosevicius, D. Popovici (2007): Optimization and Applications of Echo State Networks with Leaky Integrator Neurons. Neural Networks 20(3), 335-352, 2007. (Preprint pdf) (Matlab 6.5 code for Japanese Vouwel study) (Matlab 6.5 code for parameter optimization by stochastic gradient descent)

H. Jaeger, H. Haas (2004): Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication. Science, April 2, 2004,78-80. Preprint including supplementary online materials (pdf)

H. Jaeger (2000): Observable operator models for discrete stochastic time series. Neural Computation 12(6), 2000, 1371-1398. (pdf)

H. Jaeger, T. Christaller (1998): Dual Dynamics: Designing Behavior Systems for Autonomous Robots. Artificial Life and Robotics 2 (1998), 108-112 (pdf)

H. Jaeger (1998): Today's dynamical systems are too simple. Commentary to Tim van Gelder's BBS target article "The dynamical hypothesis in cognitive science". Behavioral and Brain Sciences 21(5), 1998, p. 643

H. Jaeger (1996): Dynamische Systeme in der Kognitionswissenschaft. Kognitionswissenschaft 5 (4), 1996, 151-174 (pdf)

Proceedings, Collections

H. Jaeger, A. Baronchelli, T. Briscoe, M. H. Christiansen, T. Griffiths, G. Jäger, S. Kirby, N. Komarova, P. J. Richerson, L. Steels, J. Triesch (2009): What can mathematical, computational and robotic models tell us about the origins of syntax? In: D. Bickerton and E. Szathmary (eds.): Biological Foundations and Origin of Syntax, p. 385-410. Strüngmann Forum Reports 3, MIT Press (preprint pdf)

H. Jaeger, D. Eck (2008): Can't Get You Out of My Head: A Connectionist Model of Cyclic Rehearsal. In: I. Wachsmuth, G. Knoblich (eds.): Modeling Communication for Robots and Virtual Humans. Springer LNAI 4930, 310-335 (http://dx.doi.org/10.1007/978-3-540-79037-2_17) (pdf)

H. Jaeger, M. Zhao, K. Kretzschmar, T. Oberstein, D. Popovici, A. Kolling (2006): Learning observable operator models via the ES algorithm. In: S. Haykin, J. Principe, T. Sejnowski, J. McWhirter (eds.), New Directions in Statistical Signal Processing: from Systems to Brain. MIT Press, Cambridge, MA., 417-464 (draft version, pdf) (Matlab code)

H. Jaeger, M. Zhao, A. Kolling (2005): Efficient training of OOMs. Advances in Neural Information Processing Systems 18 (Y. Weiss, B. Schölkopf, J. Platt, eds.), MIT Press, Cambridge, MA., 555-562 (draft version, pdf)

H. Jaeger (2005): Reservoir Riddles: Suggestions for Echo State Network Research (Extended Abstract of Invited Talk) Proceedings of IJCNN 2005, 1460-1462. (paper, pdf) (slides, pdf)

H.-U. Kobialka, H. Jaeger (2003): Experiences Using the Dynamical System Paradigm for Programming RoboCup Robots. In Proc. AMiRE 2003 (2nd International Symposium on Autonomous Minirobots for Research and Edutainment) / U. Rueckert, J. Sitte (Eds), pp 193-202, 2003. (pdf)

H. Jaeger (2002): Adaptive nonlinear system identification with echo state networks. In Advances in Neural Information Processing Systems 15, S. Becker, S. Thrun, K. Obermayer (Eds), (MIT Press, Cambridge, MA, 2003) pp. 593-600 (draft, pdf)

J. Hertzberg, H. Jaeger, F. Schoenherr (2002): Learning to Ground Fact Symbols in Behavior-Based Robot. In: ECAI 2002. Proceedings of the 15th European Conference on Artificial Intelligence. (F. van Harmelen ed.), IOS Press, Amsterdam, pp. 708-712, ISBN 1-58603-257-7, Lyon, France, July, 2002 (pdf)

H. Jaeger (1999): Action selection for delayed, stochastic reward. Proc. 4th Annual Conf. of the German Cognitive Science Society (KogWis99), Infix Verlag, 213-219 (pdf)

H. Jaeger (1999): From continuous dynamics to symbols. In: W. Tschacher, J.-P. Dauwalder: Dynamics, Synergetics, Autonomous Agents. Studies of Nonlinear Phenomena in Life Science Vol. 8, World Scientific 1999, 29-48 (pdf)

A. Bredenfeld, W. Goehring, H. Guenter, H. Jaeger, H.-U. Kobialka, P.-G. Ploeger, P. Schoell, A. Siegberg, A. Streit, C. Verbeek, J. Wilberg (1999): Behavior engineering with "dual dynamics" models and design tools. In: M.M. Veloso, (ed.), Proc. 3rd Int. Workshop on RoboCup at IJCAI-99, IJCAI Press, 57-62 (pdf)

H. Jaeger (1998): A short introduction to observable operator models for stochastic processes. In: Trappl, R. (ed.), proceedings of the Cybernetics and Systems 98 conference, Vol.1, Austrian Society for Cybernetic Studies, 38-43 (pdf)

J. Hertzberg, H. Jaeger, Ph. Morignot, U.R. Zimmer (1998): A Framework for Plan Execution in Behavior-Based Robots. Proc. Joint ISIC/ISAS'98 conference on "Intelligent Control of Complex Systems" (pdf)

H. Jaeger (1998): Multifunctionality: a fundamental property of behavior mechanisms based on dynamical systems. In: R. Pfeifer, B. Blumberg, J.-A. Meyer, and S.W. Wilson (eds.): From animals to animats 5: Proc. of the fifth int. conf. on simulation of adaptive behavior. MIT Press 1998, 286-290 (pdf)

A. Wismueller, H. Jaeger, D.R. Dersch, H. Ritter, G. Palm (1998): Self-organization of feature detectors in time sequences (SOFT) - a neural network approach to multidimensional signal analysis. Proceedings of IEEE World Congress on Computational Intelligence 1998 (WCCI 98), IEEE Computer Society Press 1998

H. Jaeger (1997): An Introduction to Dynamic Symbol Systems. In: Hallam, J. (ed.): Hybrid Problems, Hybrid Solutions. Proceedings of the AISB-95. IOS Press/Ohmsha, Amsterdam 1995, 109-120 (pdf)

Other peer-reviewed publications

H. Jaeger (2007): Echo State Networks. Scholarpedia, 2(9):2330

Technical Reports

M. Lukosevicius, H. Jaeger (2007): Overview of Reservoir Recipes. Jacobs University technical report Nr. 11 (pdf)

H. Jaeger (2007): Discovering multiscale dynamical features with hierarchical Echo State Networks. Jacobs University technical report Nr. 10 (pdf)

M. Zhao, H. Jaeger (2007): Norm observable operator models. Jacobs University technical report Nr. 8 (39 pp.) (pdf)

M. Zhao, H. Jaeger (2007): The Error Controlling Algorithm for Learning OOMs. Jacobs University technical report Nr. 6 (42 pp.) (pdf)

H. Jaeger (2006): Generating exponentially many periodic attractors with linearly growing Echo State Networks. IUB technical report Nr. 3 (26 pp.) (pdf) Matlab code

Mantas Lukosevicius, Dan Popovici, Herbert Jaeger, Udo Siewert (2006): TimeWarping Invariant Echo State Networks. IUB technical report Nr. 2 (15 pp.) (pdf)

H. Jaeger (2002): 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, 2002 (48 pp.) (revised version from March 2005, pdf)

H. Jaeger (2001): Short term memory in echo state networks. GMD Report 152, German National Research Center for Information Technology, 2001 (60 pp.) (pdf)

H. Jaeger(2001): The "echo state" approach to analysing and training recurrent neural networks. GMD Report 148, German National Research Center for Information Technology, 2001 (43 pp.) (pdf) Erratum note

H. Jaeger(2001): Modeling and learning continuous-valued stochastic processes with OOMs. GMD Report 102, German National Research Center for Information Technology, 2001 (30 pp.) (pdf)

H. Jaeger (1999): Characterizing distributions of stochastic processes by linear operators. GMD Report 62, German National Research Center for Information Technology 1999 (27 pp.) (pdf)

H. Jaeger(1998): Observable operator models of stochastic processes: a tutorial. GMD Report 42, German National Research Center for Information Technology 1998. (i) Original version from December 23, 1998 (72pp, pdf) (ii) Update from April 04 (84pp, pdf)

H. Jaeger (1997): Observable Operator Models II: Interpretable models and model induction. Arbeitspapiere der GMD 1083, GMD, St. Augustin 1997 (33 pp) (pdf) Erratum

H. Jaeger (1997): Observable Operator Models and Conditioned Continuation Representations. Arbeitspapiere der GMD 1043, GMD, St. Augustin 1997 (38 pp) (pdf)

H. Jaeger (1996): The Dual Dynamics Design Scheme for Behavior-based Robots: a Tutorial. Arbeitspapiere der GMD 966, GMD, St. Augustin 1996 (23 pp.) (pdf)

H. Jaeger (1995): Dynamische Systeme in der KI und ihren Nachbarwissenschaften. (In German.) Arbeitspapiere der GMD 925, GMD, St. Augustin 1995 (75 pp.) (pdf)

H. Jaeger (1995): Modulated Modules: Designing Behaviors as Dynamical Systems. Arbeitspapiere der GMD 927, GMD, St. Augustin 1995 (23 pp.) (pdf)

H. Jaeger (1995): Identification of Behaviors in an Agent's Phase Space. Arbeitspapiere der GMD 951, GMD, St. Augustin 1995 (37 pp.) (pdf)

PhD Thesis

H. Jaeger (1994): Dynamical Symbol Systems. Ph.D. thesis, Faculty of Technology, University of Bielefeld. 170 pp. (pdf)

Popular

H. Jaeger (2001): Ihre Zahnbuerste, der Urknall und Sie. (In German.) In: von Randow, G. (Hrsg.), Wieviel Koerper braucht der Mensch? Edition Koerber-Stiftung, Hamburg 2001, 22-40. (pdf)

H. Jaeger (1989): Komplexe Systeme - eine Schule der Bescheidenheit. (In German.) Kursbuch 98 "Das Chaos", Kursbuch/Rotbuch Verlag 1989, 149-164