  | Jordanou, J. P., Camponogara, E., Antonelo, E. A., & S. de Aguiar, M. A. (2018). Nonlinear Model Predictive Control of an Oil Well with Echo State Networks. IFAC-PapersOnLine, 51, 13 - 18. doi:10.1016/j.ifacol.2018.06.348  Peer Reviewed verified by ORBi |
 | Jordanou, J. P., Antonelo, E. A., Camponogara, E., & S. de Aguiar, M. A. (2017). Recurrent Neural Network based control of an Oil Well. In Brazilian Symposium on Intelligent Automation, Porto Alegre 1-4 October 2017 (pp. 924-931). Peer reviewed |
 | Antonelo, E. A., Camponogara, E., & Foss, B. (2017). Echo State Networks for Data-driven Downhole Pressure Estimation in Gas-lift Oil Wells. Neural Networks, 85, 106--117. doi:10.1016/j.neunet.2016.09.009 Peer reviewed |
 | Antonelo, E. A., Flesch, C., & Filipe, S. (2017). Reservoir Computing for Detection of Steady State in Performance Tests of Compressors. Neurocomputing. doi:10.1016/j.neucom.2017.09.005 Peer Reviewed verified by ORBi |
 | Antonelo, E. A., & State, R. (2017). Recurrent Dynamical Projection for Time series-based Fraud detection. In ICANN 2017, Part II, LNCS 10614. Peer reviewed |
 | Fan, Y., Nowaczyk, S. L., Rögnvaldsson, T., & Antonelo, E. A. (2016). Predicting Air Compressor Failures with Echo State Networks. In Third European Conference of the Prognostics and Health Management Society 2016, Bilbao, Spain, 5-8 July, 2016. Peer reviewed |
 | Antonelo, E. A., & Schrauwen, B. (2015). On Learning Navigation Behaviors for Small Mobile Robots With Reservoir Computing Architectures. IEEE Transactions on Neural Networks and Learning Systems, 26 (4), 763-780. doi:10.1109/TNNLS.2014.2323247 Peer reviewed |
 | Antonelo, E. A., & Camponogara, E. (2015). An Echo State Network-based Soft Sensor of Downhole Pressure for a Gas-lift Oil Well. In L. Iliadis & C. Jayne, Engineering Applications of Neural Networks (pp. 379-389). Springer. doi:10.1007/978-3-319-23983-5_35 Peer reviewed |
 | Antonelo, E. A., Camponogara, E., & Plucenio, A. (2015). System Identification of a Vertical Riser Model with Echo State Networks. IFAC-PapersOnLine, 48 (6), 304-310. doi:10.1016/j.ifacol.2015.08.048 Peer Reviewed verified by ORBi |
 | Antonelo, E. A., & Schrauwen, B. (2012). Learning Slow Features with Reservoir Computing for Biologically-inspired Robot Localization. Neural Networks, 25 (1), 178-190. doi:10.1016/j.neunet.2011.08.004 Peer reviewed |
 | Antonelo, E. A. (2011). Reservoir Computing Architectures for Modeling Robot Navigation Systems [Doctoral thesis, UGent - Universiteit Gent]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/36469 |
 | Antonelo, E. A., Depeweg, S., & Schrauwen, B. (2011). Learning navigation attractors for mobile robots with reinforcement learning and reservoir computing. In Proceedings of the X Brazilian Congress on Computational Intelligence (CBIC). Peer reviewed |
 | Antonelo, E. A., & Schrauwen, B. (2010). Supervised Learning of Internal Models for Autonomous Goal-oriented Robot Navigation using Reservoir Computing. In 2010 IEEE International Conference on Robotics and Automation (pp. 2959-2964). doi:10.1109/ROBOT.2010.5509212 Peer reviewed |
 | Antonelo, E. A., Schrauwen, B., & Stroobandt, D. (2009). Unsupervised Learning in Reservoir Computing: Modeling Hippocampal Place Cells for Small Mobile Robots. In C. Alippi, M. Polycarpou, C. Panayiotou, ... G. Ellinas, Artificial Neural Networks -- ICANN 2009 (pp. 747--756). Berlin, Heidelberg, Unknown/unspecified: Springer-Verlag. doi:10.1007/978-3-642-04274-4_77 Peer reviewed |
 | Antonelo, E. A., & Schrauwen, B. (2009). Towards Autonomous Self-localization of Small Mobile Robots using Reservoir Computing and Slow Feature Analysis. In Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 3818-3823). doi:10.1109/ICSMC.2009.5346617 Peer reviewed |
 | Waegeman, T., Antonelo, E. A., wyffels, F., & Schrauwen, B. (2009). Modular reservoir computing networks for imitation learning of multiple robot behaviors. In Proc. of the 2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation - (CIRA) (pp. 27-32). doi:10.1109/CIRA.2009.5423194 Peer reviewed |
 | Antonelo, E. A., & Schrauwen, B. (2009). On Different Learning Approaches with Echo State Networks for Localization of Small Mobile Robots. In Proceedings of the IX Brazilian Conference on Neural Networks. SBRN. doi:10.21528/CBRN2009-067 Peer reviewed |
 | Antonelo, E. A., Schrauwen, B., & Stroobandt, D. (2008). Event detection and localization for small mobile robots using reservoir computing. Neural Networks, 21 (6), 862--871. doi:10.1016/j.neunet.2008.06.010 Peer reviewed |
 | Antonelo, E. A., Schrauwen, B., & Stroobandt, D. (2008). Mobile Robot Control in the Road Sign Problem using Reservoir Computing Networks. In Proceedings of the IEEE Int. Conf. on Robotics and Automation (ICRA) (pp. 911-916). IEEE. doi:10.1109/ROBOT.2008.4543321 Peer reviewed |
 | Antonelo, E. A., Schrauwen, B., & Stroobandt, D. (2008). Modeling Multiple Autonomous Robot Behaviors and Behavior Switching with a Single Reservoir Computing Network. In Proceedings of the 2008 IEEE International Conference on Systems, Man and Cybernetics (pp. 1843-1848). doi:10.1109/ICSMC.2008.4811557 Peer reviewed |
 | Antonelo, E. A., Schrauwen, B., & Stroobandt, D. (2008). Imitation Learning of an Intelligent Navigation System for Mobile Robots using Reservoir Computing. In Proceedings of the 10th Brazilian Symposium on Neural Networks (SBRN) (pp. 93-98). Salvador, Unknown/unspecified: IEEE. doi:10.1109/SBRN.2008.32 Peer reviewed |
 | Antonelo, E. A., Schrauwen, B., & Campenhout, J. V. (2007). Generative Modeling of Autonomous Robots and their Environments using Reservoir Computing. Neural Processing Letters, 26 (3), 233--249. doi:10.1007/s11063-007-9054-9 Peer reviewed |
 | Antonelo, E. A., Schrauwen, B., Dutoit, X., Stroobandt, D., & Nuttin, M. (2007). Event detection and localization in mobile robot navigation using reservoir computing. In Artificial Neural Networks -- ICANN 2007. Springer-Verlag. doi:10.1007/978-3-540-74695-9_68 Peer reviewed |
 | Antonelo, E. A., Schrauwen, B., & Stroobandt, D. (2007). Experiments with Reservoir Computing on the road sign problem. In Proceedings of the VIII Brazilian Congress on Neural Networks (CBRN). doi:10.21528/CBRN2007-047 Peer reviewed |
 | Antonelo, E. A., Baerlvedt, A.-J., Rognvaldsson, T., & Figueiredo, M. (2006). Modular Neural Network and Classical Reinforcement Learning for Autonomous Robot Navigation: Inhibiting Undesirable Behaviors. In The 2006 IEEE International Joint Conference on Neural Network Proceedings (pp. 498-505). doi:10.1109/IJCNN.2006.246723 Peer reviewed |
 | Antonelo, E. A. (2006). A Neural Reinforcement Learning Approach for Behavior Acquisition in Intelligent Autonomous Systems [Bachelor/master dissertation, Halmstad University]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/36484 |
 | Calvo, R., Figueiredo, M., & Antonelo, E. A. (2005). Evolutionary fuzzy system for architecture control in a constructive neural network. In 2005 International Symposium on Computational Intelligence in Robotics and Automation (pp. 541-546). IEEE. doi:10.1109/CIRA.2005.1554333 Peer reviewed |
 | Antonelo, E. A., Figueiredo, M., Baerlvedt, A.-J., & Calvo, R. (2005). Intelligent autonomous navigation for mobile robots: spatial concept acquisition and object discrimination. In Proceedings of the 6th IEEE International Symposium on Computational Intelligence in Robotics and Automation (pp. 553-557). doi:10.1109/CIRA.2005.1554335 Peer reviewed |