Publications

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A
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.
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)
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, and D. Stroobandt, "Imitation Learning of an Intelligent Navigation System for Mobile Robots using Reservoir Computing", 10th Brazilian Symposium on Neural Networks (SBRN), 2008.
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)
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.
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)
Antonelo, E A., B. Schrauwen, and D. Stroobandt, "Event detection and localization for small mobile robots using reservoir computing", Neural Networks, vol. 21, pp. 862–871, 2008. Abstract  Download: robotlocalization_antonelo_nn2008_0.pdf (2.68 MB)
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.
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)
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.
Atiya, A. F., and A. G. Parlos, "New Results on Recurrent Network Training: unifying the Algorithms and Accelerating Convergence", IEEE Transactions on Neural Networks, vol. 11, no. 3, pp. 697–709, 2000.
B
Bernacchia, A., H. Seo, D. Lee, and X-J. Wang, "A reservoir of time constants for memory traces in cortical neurons", Nature Neuroscience, vol. 14, no. 3, pp. 366-372, 02/2011.
Bertschinger, N., and T. Natschläger, "Real-time computation at the edge of chaos in recurrent neural networks", Neural Computation, vol. 16, no. 7, Cambridge, MA, USA, MIT Press, pp. 1413–1436, 2004.
Buehner, M., and P. Young, "A Tighter Bound for the Echo State Property", Neural Networks, IEEE Transactions on, vol. 17, no. 3, pp. 820-824, 2006.
Buesing, L., and W. Maass, "Simplified rules and theoretical analysis for information bottleneck optimization and PCA with spiking neurons", NIPS 2007: Advances in Neural Information Processing Systems, vol. 20: MIT Press, 2008, 2007. Abstract
Buesing, L., B. Schrauwen, and R. Legenstein, "Connectivity, Dynamics and Memory in Reservoir Computing with Binary and Analog Neurons", Neural Computation, In Press. Abstract
Buesing, L., and W. Maass, "A spiking neuron as information bottleneck", Neural Computation, vol. 22, 2010. Abstract
Buonomano, D., and W. Maass, "State-dependent computations: Spatiotemporal processing in cortical networks", Nature Reviews Neuroscience, vol. 10, no. 2, pp. 113-125, 2009. Abstract
Bush, K. A., and C. W. Anderson, "Exploiting Iso-error Pathways in the N, k-plane to Improve Echo State Network Performance", Proceedings of the 2006 Conference of Neural Informations Processing Systems (submitted), 2006.
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.
D
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)
Daukantas, S., M. Lukoševičius, V. Marozas, and A. Lukoševičius, "Comparison of ``black box'' and ``gray box'' methods for lost data reconstruction in multichannel signals", Proceedings of the 14th International Conference ``Biomedical Engineering'', Kaunas, pp. 135-138, 2010.
Defour, J., Spraakherkenning met reservoir computing, : Universiteit Gent, 2006.