Publications

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Joshi, P., and W. Maass, "Movement generation with circuits of spiking neurons", Neural Computation, vol. 17, no. 8, pp. 1715-1738, 2005. Abstract
Joshi, P., and W. Maass, "Movement generation and control with generic neural microcircuits", BioADIT 2004, Lecture Notes in Computer Science, Lausanne, Springer, 2004. Abstract
Maass, W., "Motivation, theory, and applications of liquid state machines", Computability in Context: Computation and Logic in the Real World: Imperial College Press, 2011. Abstract
Haeusler, S., K. Schuch, and W. Maass, "Motif distribution and computational performance of two data-based cortical microcircuit templates", Journal of Physiology (Paris), vol. 103, no. 1-2, 2009. Abstract
Waegeman, T., E. Antonelo, F. wyffels, and B. Schrauwen, "Modular reservoir computing networks for imitation learning of multiple robot behaviors", Proc. of the IEEE Int. Symp. on Computational Intelligence in Robotics and Automation (CIRA), 2009.  Download: p27.pdf (2.34 MB)
Bush, K., and C. Anderson, "Modeling Reward Functions for Incomplete State Representations via Echo State Networks", Proceedings of the International Joint Conference on Neural Networks, Montreal, Quebec, 2005.
Antonelo, E A., B. Schrauwen, and D. Stroobandt, "Modeling Multiple Autonomous Robot Behaviors and Behavior Switching with a Single Reservoir Computing Network", IEEE International Conference on Man, Systems and Cybernetics, 2008.
Dominey, P. F., M. Arbib, and J-P. Joseph, "A model of corticostriatal plasticity for learning oculomotor associations and sequences", Journal of Cognitive Neuroscience, vol. 7, no. 3, pp. 311-336, 1995. Abstract  Download: dominey1995jocn.pdf (1.09 MB)
Kaske, A., and W. Maass, "A model for the interaction of oscillations and pattern generation with real-time computing in generic neural microcircuit models", Neural Networks, vol. 19, no. 5, pp. 600-609, 2006. Abstract
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
Antonelo, E A., B. Schrauwen, and D. Stroobandt, "Mobile Robot Control in the Road Sign Problem using Reservoir Computing Networks", IEEE Int. Conf. on Robotics and Automation (ICRA), 2008.
Skowronski, M. D., and J. G. Harris, "Minimum mean squared error time series classification using an echo state network prediction model", IEEE International Symposium on Circuits and Systems, 2006.
Li, J., and H. Jaeger, "Minimal Energy Control of an ESN Pattern Generator", Jacobs University Technical Report, no. 26: Jacobs University Bremen, 2011. Abstract
Maass, W., R. Legenstein, and N. Bertschinger, "Methods for estimating the computational power and generalization capability of neural microcircuits", NIPS 2004: Advances in Neural Information Processing Systems, vol. 17: MIT Press, pp. 865-872, 2005, 2004. Abstract
Kulkarni, M., and C. Teuscher, "Memristor-based Reservoir Computing", Proceedings of the IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH'12), pp. 226–232, 2012.
Hermans, M., and B. Schrauwen, "Memory in reservoirs for high dimensional input", IJCNN, Barcelona, Spain, 2010.
Hermans, M., and B. Schrauwen, "Memory in linear neural networks in continuous time", Neural Networks, 2009.  Download: Paper.pdf (834.16 KB)
Massar, M., and S. Massar, "Mean-field theory of echo state networks", PHYSICAL REVIEW E, vol. 87, 2013.  Download: 2013MassarMassarPhysRevE87_042809.pdf (490.19 KB)