Publications

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Antonelo, E A., B. Schrauwen, and D. Stroobandt, "Unsupervised Learning in Reservoir Computing: Modeling Hippocampal Place Cells for Small Mobile Robots", International Conference on Artificial Neural Networks (ICANN), 2009.
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Antonelo, E. A., and B. Schrauwen, "Towards Autonomous Self-localization of Small Mobile Robots using Reservoir Computing and Slow Feature Analysis", Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 3818–3823, 2009.  Download: eric_smc2009.pdf (2.76 MB)
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Antonelo, E. A., and B. Schrauwen, "Supervised Learning of Internal Models for Autonomous Goal-oriented Robot Navigation using Reservoir Computing", IEEE International Conference on Robotics and Automation (ICRA), 2009.  Download: icra2010_eric.pdf (1.46 MB)
wyffels, F., B. Schrauwen, and D. Stroobandt, "Stable output feedback in reservoir computing using ridge regression", International Conference on Artificial Neural Networks, 2008.
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Verstraeten, D., "Reservoir Computing: computation with dynamical systems", Electronics and Information Systems, Gent, Ghent University, pp. 190, 2009.  Download: dvrstrae_organic.pdf (7.23 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)
Antonelo, E A., "Reservoir Computing Architectures for Modeling Robot Navigation Systems", Department of Electronic and Information Systems , vol. PhD, Gent, Universiteit Gent, 2011. Abstract  Download: PhD_Eric_final.pdf (21.33 MB)
Verstraeten, D., B. Schrauwen, and J V. Campenhout, "Recognition of Isolated Digits using a Liquid State Machine", Proceedings of SPS-DARTS 2005, pp. 135–138, April, 2005.
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Triefenbach, F., A. Jalalvand, B. Schrauwen, and J-P. Martens, "Phoneme Recognition with Large Hierarchical Reservoirs", Neural Information Processing Systems (NIPS2010) , 2010. Abstract  Download: ftriefen_nips2010.pdf (782.18 KB)
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Hermans, M., and B. Schrauwen, "One Step Backpropagation through time for learning input mapping in reservoir computing applied to speech recognition", ISCAS 2010, Paris, 2010.
Schrauwen, B., L. Buesing, and R. Legenstein, "On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing", NIPS: Vancouver, 2008. Abstract
Verstraeten, D., B. Schrauwen, S. Dieleman, P. Brakel, P. Buteneers, and D. Pecevski, "Oger: Modular Learning Architectures For Large-Scale Sequential Processing", Journal of Machine Learning Research, Submitted.  Download: Verstraeten11.pdf (186.23 KB)
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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)
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.
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.
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)
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Antonelo, E A., and B. Schrauwen, "Learning Slow Features with Reservoir Computing for Biologically-inspired Robot Localization", Neural Networks, In Press. Abstract  Download: eric_nn2011.pdf (2.77 MB)
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Verstraeten, D., B. Schrauwen, and D. Stroobandt, "Isolated word recognition using a Liquid State Machine", Proceedings of the 13th European Symposium on Artificial Neural Networks (ESANN), Evere, D-side Publications, pp. 435–440, May, 2005.
Antonelo, E A., B. Schrauwen, and D. Stroobandt, "Imitation Learning of an Intelligent Navigation System for Mobile Robots using Reservoir Computing", 10th Brazilian Symposium on Neural Networks (SBRN), 2008.
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Schrauwen, B., and L. Buesing, "A hierarchy of recurrent networks for speech recognition", NIPS, Proceedings, Whistler, BC, Canada, pp. 8, 2009.  Download: bschrauw_nips_2009.pdf (103.7 KB)
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Antonelo, E A., B. Schrauwen, and J V. Campenhout, "Generative Modeling of Autonomous Robots and their Environments using Reservoir Computing", Neural Processing Letters, vol. 26, no. 3, pp. 233–249, 2007.
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D'Haene, M., and B. Schrauwen, "Fast and exact simulation methods applied on a broad range of neuron models", NEURAL COMPUTATION, vol. 22, no. 6, pp. 1468-1472, 2010.  Download: NECO-07-09-1070-PDF.pdf (86.6 KB)
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Antonelo, E A., B. Schrauwen, and D. Stroobandt, "Experiments with Reservoir Computing on the road sign problem", VIII Brazilian Congress on Neural Networks (CBRN), 2007.
Antonelo, E A., B. Schrauwen, X. Dutoit, D. Stroobandt, and M. Nuttin, "Event detection and localization in mobile robot navigation using reservoir computing", ICANN, Part II: Springer-Verlag, pp. 660-669, 2007.