Publications (with acknowledgements to the project)
Zhiguang Hua, Zhixue Zheng, Elodie Pahon, Marie-Cécile Péra and Fei Gao, Remaining useful life prediction of PEMFC systems under dynamic operating conditions, Energy Conversion and Management 231 (2021) 113825 DOI: 10.1016/j.enconman.2021.113825
Grigoryeva, L., Hart, A., and Ortega, J.-P. [2020] Chaos on compact manifolds: Differentiable synchronizations beyond Takens. Preprint
Cuchiero, C., Gonon, L., Grigoryeva, L., Ortega, J.-P., and Teichmann, J. [2020] Discrete-time signatures and randomness in reservoir computing. Preprint
Grigoryeva, L., and Ortega, J.-P. [2020] Dimension reduction in recurrent networks by canonicalization. Preprint
Gonon, L., Grigoryeva, L., and Ortega, J.-P. [2020] Approximation bounds for random neural networks and reservoir systems. Preprint
Gonon, L. and Ortega, J.-P. [2021] Fading memory echo state networks are universal. To appear in Neural Networks. Paper.
Louis Andreoli, Xavier Porte, Stéphane Chrétien, Maxime Jacquot, Laurent Larger and Daniel Brunner, Boolean learning under noise-perturbations in hardware neural networks, Nanophotonics 2020; 20200171 DOI: 10.1515/nanoph-2020-0171
Gonon, L., Grigoryeva, L., and Ortega, J.-P. [2020] Risk bounds for reservoir computing. Journal of Machine Learning Research, 21(240), 1-61. Paper
Gonon, L., Grigoryeva, L., and Ortega, J.-P. [2020] Memory and forecasting capacities of nonlinear recurrent networks. Physica D, 414, 132721, 1-13. Paper
Gonon, L. and Ortega, J.-P. [2020] Reservoir computing universality with stochastic inputs. IEEE Transactions on Neural Networks and Learning Systems, 31(1), 100-112. Paper
Maktoobi, S.; Froehly, L.; Andreoli, L.; Porte, X.; Jacquot, M.; Larger, L.; Brunner, B.; "Diffractive coupling for photonic networks: how big can we go?," IEEE Journal of Selected Topics in Quantum Electronics 26, 7600108 (2020). DOI:10.1109/JSTQE.2019.2930454.
Y.K. Chembo, D. Brunner, M. Jacquot and L. Larger, "Optoelectronic oscillators with time-delayed feedback", Review of Modern Physics, Vol.91, No.3, 035006 (2019); DOI:10.1103/RevModPhys.91.035006
Penkovsky, B.; Porte, X.; Jacquot, M.; Larger, L.; Brunner, B.; "Coupled nonlinear delay systems as deep convolutional neural networks," Physical Review Letters 123, 054101 (2019). DOI: 10.1103/PhysRevLett.123.054101.
Semenova, N.; Porte, X.; Andreoli, L.; Jacquot, M.; Larger, L.; Brunner, D.; "Fundamental aspects of noise in analog-hardware neural networks," Chaos 29, 103128 (2019). DOI: 10.1063/1.5120824.
Grigoryeva, L. and Ortega, J.-P. [2019] Differentiable reservoir computing. Journal of Machine Learning Research, 20(179), 1-62. Paper
L. Grigoryeva and J.-P. Ortega, "Echo state networks are universal", Neural Networks, Vol. 108, pp. 495-508 (2018); doi: 10.1016/j.neunet.2018.08.025
D. Brunner, B. Penkovsky, R. Levchenko, E. Schöll, L. Larger and Y. Maistrenko, "Two-dimensional spatiotemporal complexity in dual-delayed nonlinear feedback systems: Chimeras and dissipative solitons", Chaos, Vol.28, 103106 (2018); doi: 10.1063/1.5043391 -highlighted paper by the American Institute of Physics (AIP) for Scilight-
L. Grigoryeva and J.-P. Ortega "Universal discrete-time reservoir computers with stochastic inputs and linear readouts using non-homogeneours state-affine systems", Journal of Machine Learning Research, Vol.19, No. 24, pp. 1-40 (2018).
B. Penkovsky, L. Larger, D. Brunner, "Efficient design of hardware-enabled reservoir computing in FPGAs", Journal of Applied Physics, Vol.124, No.16, 162101 (2018); doi: 10.1063/1.503982
D. Brunner, B. Penkovsky, B.A. Marquez, M. Jacquot, I. Fischer, and L. Larger, "Tutorial: Photonic neural networks in delay systems", Journal of Applied Physics, Vol.124, No.15, 152004 (2018); doi: 10.1063/1.5042342D
B. A. Marquez, L. Larger, M. Jacquot, Y. K. Chembo, D. Brunner, "Dynamical complexity and computation in recurrent neural networks beyond their fixed point", Scientific Reports, 8:3319 (2018) doi:10.1038/s41598-018-21624-2
Z. Zheng, S. Morando, M.-C. Péra, D. Hissel, L. Larger, R. Martinenghi and A. Baylon Fuentes, "Brain-inspired computational paradigm dedicated to fault diagnosis of PEM fuel cell stack". International Journal of Hydrogen Energy, vol. 42(8), pp. 5410 - 5425, 2017. doi: 10.1016/j.ijhydene.2016.11.043.
L. Larger, A. Baylón-Fuentes, R. Martinenghi, V.S. Udaltsov, Y.K. Chembo and M. Jacquot, "High-Speed Photonic Reservoir Computing Using a Time-Delay-Based Architecture: Million Words per Second Classification", Physical Review X, vol.7, 011015 (2017). doi: 10.1103/PhysRevX.7.011015. -APS Physics Viewpoint & Research Highlight in Nature-
B. A. Marquez, L. Larger, D. Brunner, Y. K. Chembo, and M. Jacquot, "Interaction between Liénard and Ikeda dynamics in a nonlinear electro-optical oscillator with delayed bandpass feedback", Physical Review E, Vol.94, No.6, 062208 (2016). doi: 10.1103/PhysRevE.94.062208.
L. Grigoryeva, J. Henriques, L. Larger, and J.-P. Ortega "Nonlinear Memory Capacity of Parallel Time-Delay Reservoir Computers in the Processing of Multidimensional Signals", Neural Computations, 28, pp. 1411-1451 (2016). doi:10.1162/NECO_a_00845.
Grigoryeva, L., Henriques, J., Larger, L., and Ortega, J.-P., "Time-delay reservoir computers and high-speed information processing capacity", Proceedings of the IEEE International Conference on Computational Science and Engineering, August 24-26, 2016 - Paris, France. doi:10.1109/CSE-EUC-DCABES.2016.230.
Grigoryeva, L., Henriques, J., and Ortega, J.-P., "Reservoir computing: information processing of stationary signals", Proceedings of the IEEE International Conference on Computational Science and Engineering, August 24-26, 2016 - Paris, France. doi:10.1109/CSE-EUC-DCABES.2016.231. -Best Paper Award-
N. Oliver, L. Larger and I. Fischer, "Consistency in experiments on multistable driven delay systems", Chaos, Vol. 26, 103115 (2016). doi: 10.1063/1.4966021.
L. Grigoryeva, J. Henriques, L. Larger, and J.-P. Ortega "Optimal nonlinear information processing capacity in delay-based reservoir computers", Scientific Reports, 5, Article number: 12858 (2015). doi:10.1038/srep12858.
Conferences
Ortega J.-P., January 2020: London Mathematical Finance Seminar. 1 hour seminar: “Dynamic and Control Theoretical Aspects of Reservoir Computing”. Imperial College. London.
Z. Hua, Z. Zheng, F. Gao, M.-C. Péra, "Challenges of the Remaining Useful Life Prediction for Proton Exchange Membrane Fuel Cells," 45th Annual Conference of the IEEE Industrial Electronics Society (IECON 2019), Lisbon, Portugal.
Brunner, D.; Andreoli, L.; Porte, X.; Jacquot, M.; Reitzenstein, S.; Larger, L.; "Greedy Boolean learning in large photonic neural networks: empirical findings of convergence and scaling," Active Matter and Artificial Intelligence, 2nd of October 2019, CECAM-EPFL, Lausanne, Switzerland.
Brunner, D.; Andreoli, L.; Porte, X.; Jacquot, M.; Larger, L.; "Photonic neural networks scalable in size and learning effort," ECOC, 22nd of September 2019, Dublin, Ireland.
Brunner, D.; Andreoli, L.; Porte, X.; Semenova, N.; Jacquot, M.; Chretien, S.; Reitzenstein, S.; Larger, L.; "General considerations for neural networks implemented in hardware," ML Photonica, 26th of August 2019, Belgrade, Serbia.
Brunner, D.; Andreoli, L.; Chretien, S.; Jacquot, M.; Larger, L.; "General considerations for neural networks implemented in hardware," V Workshop on Dynamical Systems and Brain-Inspired Information Processing, 30th of July 2019, Konstanz, Germany.
L. Larger, "Complexity in nonlinear delay dynamics for chimera states", ICPT School and Workshop on Patterns of Synchrony: Chimera States and Beyond, Trieste (May 8 2019), Italy
L. Larger, "From Reservoir Computing to Chimera States... and Back to RC?", Vth workshop on Dynamical Systems and Brain-Inspired Information Processing, Univ. of Konstanz (29-31 July 2019), Germany
Brunner, D.; Andreoli, L.; Chretien, S.; Jacquot, M.; Larger, L.; "Scaling and cost-function topology of evolutionary Boolean learning in hardware," OSA Nonlinear optics topical meeting (NLO), 16th of July 2019, Waikoloa Village, Hawaii, USA.
Brunner, D.; Andreoli, L.; Porte, X.; Maktoobi, S.; Jacquot, M.; Chretien, S.; Reitzenstein, S.; Larger, L.; "Photonics for neural networks and evolutionary boolean learning", CLEO-Europe / EQEC, June 23rd 2019, Munich, Germany.
Brunner, D.; Maktoobi, S.; Andreoli, L.; Porte, X.; Jacquot, M.; Reitzenstein, S.; Larger, L.; "Limits and Applications of Diffractive Coupling", OSA Mathematics in Imaging 2019, 26th of June 2019, Munich, Germany.
Brunner, D.; Andreoli, L.; Chretien, S.; Jacquot, M.; Larger, L.; "Scaling and cost-function topology of evolutionary Boolean learning in hardware," International Work-Conference on Artificial Neural Networks (IWANN), 12th of June 2019, Gran Canaria, Spain.
Brunner, D.; Andreoli, L.; Chretien, S.; Jacquot, M.; Larger, L.; "Scaling and cost-function topology of evolutionary Boolean learning in hardware," Bits and Brains Workshop (KNAW), 18th of April 2019, Dutch National Academy of Science, Amsterdam, Holland.
Brunner, D.; Andreoli, L.; Maktoobi, S.; Jacquot, M.; Larger, L.; "Greedy Learning in a Large Scale Photonic Network," Neuro-inspired Computation Course, 23rd of March 2019, University of Tokyo, Japan.
Brunner, D.; Andreoli, L.; Maktoobi, S.; Jacquot, M.; Larger, L.; "Reinforcement Learning in a Large Scale Photonic Network" CNC 2019, 20th of March 2019, Atsugi, Japan.
Brunner, D.; Andreoli, L.; Maktoobi, S.; Bueno, J.; Jacquot, M.; Fischer, I.; Larger, L.; "Reinforcement Learning in a Large Scale Photonic Network" SPIE Photonics West, 6th of February 2019, San Francisco, USA. Keynote.
Ortega J.-P., September 2019: Austrian Mathematical Society Annual Meeting. University of Applied Sciences Vorarlberg. Dornbirn. 30 minutes talk: “Dynamic and Control Theoretical Aspects of Reservoir Computing”.
Ortega J.-P., July 2019: V Workshop on Dynamical Systems and Brain-Inspired Information Processing. University of Konstanz. 45 minutes plenary talk: “Dynamic and Control Theoretical Aspects of Reservoir Computing”.
Ortega J.-P., July 2019: International Congress of Industrial and Applied Mathematics (ICIAM), Universi- dad de Valencia. 30 minutes presentation: “Universality theorems in dynamic machine learning with applications to realized covolatilities forecasting”.
Ortega J.-P., May 2019: Quantact Workshop on Financial Mathematics, Université de Montreal. 1 hour plenary talk: “Universality theorems in dynamic machine learning with applications to realized covolatilities forecasting”.
Ortega J.-P., May 2019: SIAM Conference on Financial Mathematics and Engineering, University of Toronto. 30 minutes presentation: “Universality theorems in dynamic machine learning with applica- tions to realized covolatilities forecasting”.
Ortega J.-P., May 2019: Nanyang Technological University. Singapore. 1 hour seminar: “Machine learning of dynamic processes”.
Ortega J.-P., March 2019: DAGSTAT 2019. Munich. Germany. Poster and 20 minutes presentation: “Universality theorems in dynamic machine learning with applications to realized covolatilities forecasting”.
Ortega J.-P., March 2019: Conference “Random Transformations and Invariance in Stochastic Dynamics”. Verona, Italy. 40 minutes presentation. “The universality problem in dynamic machine learning with application to realized covolatilities forecasting”.
Ortega J.-P., February 2019: Alan Turing Institute. London. 90 minutes presentation. “Dynamical systems, learning theory, and information processing”.
Ortega J.-P., February 2019: Symposium on Machine Learning and Dynamical Systems. Imperial College. London. 30 minutes presentation. “Universality theorems in dynamic machine learning”.
L. Larger, "Nonlinear Delay Oscillators", Summer school of the SMYLE Collegium, EPFL, Microcity, Neuchâtel (11-12 October 2018), Switzerland
Mezzi, R.; Morando, S.; Yousfi Steiner, N.; Péra, M.-C.; Hissel, D.; Larger L.; "Multi-Reservoir Echo State Network for Proton Exchange Membrane Fuel Cell Remaining Useful Life prediction", IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society, October 2018. DOI: 10.1109/IECON.2018.8591345
Brunner, D.; Jacquot, M.; Fischer, I.; Reitzenstein, S.; Larger, L.; "Reinforcement Learning in a Large Scale Photonic Network," LAOP, 15th of November 2018, Lima, Peru.
Brunner, D.; Jacquot, M.;Larger, L.; "Tutorial: Reservoir Computing," Spintronics meets Neuromorphics (Spice), 11th of October 2018, Mainz, Germany.
Brunner, D.; Jacquot, M.; Fischer, I.; Larger, L.; "Reinforcement Learning in large scale parallel photonic Reservoirs," CLEO Pacific Rim, 1st of August 2018, Hong Kong, China.
Brunner, D.; Jacquote, M.; Fischer, I.; Larger, L.; "Learning in large scale parallel photonic Reservoirs," Novel frontiers of optics for computing Workshop, Japanese Science and Technology Agency, 18th June 2018, Tokyo, Japan.
Brunner, D.; "Towards next generation learning in photonic systems", École polytechnique fédérale de Lausanne, 8th May 2018, Lausanne, Switzerland.
Brunner, D.; "Reinforcement Learning in a Large Scale Photonic Network", Max Planck Institute For Microstructure Physics, 24th January 2018, Halle, Germany.
Brunner, D.; "Towards Photonic Networks of Micropillar Lasers for Neuromorphic Computing ", Physics of Quantum Electronics, 7-12th January 2018, Snowbird, USA.
L. Larger, A. Baylon-Fuentes, M. Jacquot, D. Brunner, Y.K. Chembo, "Ultra-fast brain-inspired photonic information classification", 6-8 February 2018, OPTRO 2018, Paris, France.
Ortega, J.-P.December 2018: Statistics and Stochastics Seminar. Universität Konstanz. Germany. 60 minutes presentation. “Universality theorems in dynamic machine learning”.
Ortega, J.-P., Computational and Financial Econometrics (CFE’18) December 2018. Pisa. Italy. 30 minutes presentation: “Universality theorems in dynamic machine learning with applications to realized covolatilities forecasting”.
Ortega, J.-P., Journée de l’Association Française pour l’Intelligence Artificielle. Institut Henri Poincaré. Paris, France, September 2018. 45 minutes presentation. “Universality theorems in dynamic machine learning”.
Ortega J.-P., September 2018: Conference “Innovative Research in Mathematical Finance”. CIRM Luminy, France. 60 minutes presentation. “Universality theorems in dynamic machine learning with applications to realized covolatilities forecasting”.
Ortega J.-P., May 2018: Shanghai Jiao Tong University. China. Department of Mathematics. Stochastic Seminar. 60 minutes presentation. “Universality theorems in dynamic machine learning”.
Brunner, D.; "Large scale spatio-temporal networks of nonlinear oscillators for neuromorphic computing," Dynamical Systems and Brain-inspired Information Processing, 6th October 2017, Konstanz, Germany.
L. Larger, A. Baylon-Fuentes, D. Brunner, Y. K. Chembo, M. Jacquot, B. Marquez, and B. Penkovskyi, "Delay dynamics emulating a network: from model to photonic RC", Ivth workshop on Dynamical Systems and Brain-Inspired Information Processing (5-6 October 2017), Konstanz, Germany
Brunner, D; "Photonic networks for Neuromorphic Computing," Frontiers in Optics, 21st September 2017 Washington DC, USA.
Brunner, D.; "High performance neuromorphic computing in random photonic networks," Bernstein Conference, 12th September 2017, Göttingen, Germany.
Brunner, D.; Reitzenstein, S.; Fischer, I.; "Neuromorphic Computing using networks of quantum dot emitters," Dynamical Systems and Brain Inspired Computing Workshop, 31st May 2nd June 2017, Université Libre de Bruxelles, Brussels, Belgium.
L. Larger, "Nonlinear delay differential equations: basic principles, real world, and implementation in photonics", 2nd workshop on Pattern Dynamics in Nonlinear Optical Cavities (PDNOC'17), University of Auckland (6 June 2017), New Zealand
L. Larger, "Exploiting complexity of DDE in photonics: Chaos encryption, pure Radar microwave, and in brain inspired processing", 2nd workshop on Pattern Dynamics in Nonlinear Optical Cavities (PDNOC'17), University Auckland (14 June 2017), New Zealand
L. Larger, "Exploiting complexity of DDE in photonics: Chaos encryption, pure Radar microwave, and in brain inspired processing", 2nd workshop on Pattern Dynamics in Nonlinear Optical Cavities (PDNOC'17), University Auckland (14 June 2017), New Zealand
Brunner, D.;"Large scale spatio-temporal networks of nonlinear oscillators for neuromorphic computing," CNOD Workshop, 18-19th May 2017, Université Côte d’Azur, Sophia Antipolis, France.
Brunner, D.; "Photonic networks for the implementation of Neural Networks," Seminar presentation ETH Zürich, 21 March 2017, Zürich, Switzerland.
Ortega J.-P., September 2017: 7th Workshop on Computational Social Science. Universit ̈at Sankt Gallen. Switzerland. 40 minutes presentation: “Universal discrete-time reservoir computers with stochastic inputs and linear readouts using non-homogeneours state-affine systems”.
Ortega J.-P., July 2017: Universität Freiburg. Department of Mathematics. Stochastic Seminar. 60 minutes presentation. “Time-delay reservoir computers: nonlinear stability of functional differential systems and optimal nonlinear information processing capacity”.
Ortega J.-P., July 2017: Conference “New Trends in Applied Geometric Mechanics – Celebrating Darryl Holm‘s 70th birthday”. ICMAT, Madrid, Spain. 60 minutes invited lecture. “Time-delay reservoir computers: nonlinear stability of functional differential systems and optimal nonlinear information processing capacity”.
Ortega J.-P., ETHZ, Zurich, Switzerland. Department of Mathematics Seminar. 60 minutes presentation, March 2017. “Time-delay reservoir computers: nonlinear stability of functional differential systems and optimal nonlinear information processing capacity”.
Maktoobi, S.; Andreoli, L.; Froehly, L.; Jacquot, M.; Brunner, D.; "Scalable Optical Neural Network via Diffractive Coupling," Cognitive Computing - merging concepts with hardware, 19th of December 2018, Hannover, Germany.
Andreoli, L.; Samenova, N.; Samenov, V.; Maktoobi, S.; Jacquot, M.; Fischer, I.; Larger, L.; Brunner, D.; "Impact and mitigation of noise in analogue spatio - temporal neural network", NOLTA, 4th of September 2018, Terragona, Spain.
Maktoobi, S.; Froehly, L.; Jacquot, M.; Larger, L.; Brunner, D.; "Diffractive coupling for large scale photonic Reservoir Computers," OSA Advanced Photonics Congress, 2-5 July, 2018, Zürich, Switzerland.
Penkovsky, B.; Larger, L.; Maistrenko, Y.; Brunner, D.; “Nonlinear Delayed-feedback Systems: Complex Patterns And Neuromorphic Computing”, ZEA-2, invited seminar, May 15, 2018, Juelich, Germany.
Maktoobi,S.; Froehly, L.; Jacquot, M.; Brunner, D.; "Diffractive Coupling for Optical Neural Network ", 6th International symposium in Optics and its Applications, Poster presentation, 17-20th February 2018, Trento, Italy. Best poster presentation award.
Marquez, B. A.; Suarez-Vargas, J.; Larger, L.; Jacquot, M; Chembo, Y. K.; Brunner, D.; "Embedding in Neural Networks: A-Priori Design of Hybrid Computers for Prediction", 2017 IEEE International Conference on Rebooting Computing (ICRC), Oral presentation, 7-10 November 2017, Washington DC, USA.
Penkovsky, B.; Larger, L.; Brunner, D.; “Network dynamic emulated by large delay systems: From brain-inspired computing to chimera states”, PhysCon 2017, Invited presentation, July 18, 2017, Florence, Italy.
Penkovsky, B.; Brunner, D.; Larger, L.; Maistrenko, Y.; “Chimera States in Nonlinear Systems with Delayed Feedback” at “Complex patterns on networks”, Dynamics Days Europe, June 6, 2017, Szeged, Hungary.
S. Morando, M.-C. Pera, N. Yousfi Steiner, S. Jemei, D. Hissel, L. Larger, "Diagnostic de PEMFC à l'aide de réseaux de neurones à réservoir", GDR Hyspac 2017, Limoges (Mai 2017).
J.-P. Ortega, "Time-delay reservoir computers: nonlinear stability of functional differential systems and optimal nonlinear information processing capacity", ETHZ, Zürich, Switzerland. Department of Mathematics Seminar, March 2017 -invited seminar-
J.-P. Ortega, "Time-delay reservoir computers and high-speed information processing capacity'', Computational and Methodological Statistics Conference (CMStatistics'16). Universidad de Sevilla, Spain, December 2016.
J.-P. Ortega, "A reservoir computing approach to machine learning", Swiss Institute for Empirical Economic Research, Sankt Gallen, Switzerland, Breakfast Seminar, November 2016.
J.-P. Ortega, December 2016: Computational and Methodological Statistics Conference (CMStatistics’16). Universidad de Sevilla. Spain. 30 minutes presentation: “Time-delay reservoir computers and high-speed information processing capacity”.
J.-P. Ortega, November 2016: School of Economics and Political Science, Sankt Gallen, Switzerland. Brown Bag seminar. 60 minutes presentation: “Non-affine GARCH option pricing models, variance dependent kernels, and diffusion limits”.
J.-P. Ortega, September 2016: Statistische Woche. Universität Augsburg. Germany. 30 minutes presen- tation: “Non-affine GARCH option pricing models, variance dependent kernels, and diffusion limits”.
J.-P. Ortega, August 2016: Joint keynote address for the conferences: 19th IEEE International Conference on Computational Science and Engineering (CSE 2016), 15th International Symposium on Dis- tributed Computing and Applications to Business, Engineering and Science (DCABES 2016), and 14th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing (EUC 2016). Ecole de Mines. Paris. One hour presentation: “Time-delay reservoir computers and high-speed information processing capacity”.
D. Brunner, B. Penkovskyi, Y. Maistrenko and L. Larger, "Space-Time analogy in Delay Systems for Chimera States and Reservoir Computing", Yugawara, Japan, NOLTA, nov. 2016 -Talk in invited session-
B. Marquez, L. Larger, D. Brunner, Y.K. Chembo and M. Jacquot, "Interaction between Liénard and Ikeda dynamics in a nonlinear electro-optical oscillator with delayed feedback", Dynamics of Delay Equations, Theory and Applications in WIAS Berlin, Germany, Oct. 2016.
S. Morando, M.-C. Pera, N. Steiner, S. Jemei, D. Hissel and L. Larger, "Fuel Cells fault diagnosis under dynamic load profile using Reservoir Computing", 13th IEEE Vehicle Power and Propulsion Conference (VPPC2016), 6 p., 17-20 October 2016, Hangzhou, China.
B. Penkovsky, D. Brunner, L. Larger, “Towards a Brain-Inspired Computer With a Delay Dynamics” at GDR BioComp, INSA Lyon, October 11, 2016.
J.-P. Ortega, "Time-delay reservoir computers and high-speed information processing capacity", Joint keynote address for the conferences: 19th IEEE International Conference on Computational Science and Engineering (CSE 2016), 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES 2016), and 14th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing (EUC 2016). 24-26 August 2016, Ecole des Mines. Paris, France.
L. Larger, "Oscillator network emulated by photonic delay dynamics", Pattern Dynamics in Nonlinear Optical Cavities (PDNOC'16), Max-Planck-Institut für Physik komplexer Systeme August 15-19, 2016, Dresden, Germany -Invited Talk-
B. Penkovsky, D. Brunner, L. Larger, “Laser Delay Dynamics For Information Processing” at TU Berlin, Germany, July 13, 2016 -Invited seminar-
J.-P. Ortega, "Reservoir computing: a big data compatible machine learning paradigm", Workshop on Computational Social Science. Universität Konstanz, Germany, July 2016.
L. Larger, M. Jacquot, Y.K. Chembo, D. Brunner, "Photonic Nonlinear Transient Computing: A new paradigm for harnessing speed, power, and energy efficiency in future computers", International Conference on Energy, Materials & Photonics (EMP'16), July 11th, 2016 / Troyes, France -Invited Talk-
J.-P. Ortega, IBM Research Lab, Zürich. Switzerland, "Reservoir computing: a big data compatible machine learning paradigm", June 2016 -invited seminar-
B. Penkovsky, D. Brunner, L. Larger, “Toward New General-Purpose Processor With Nonlinear Transient Computing” at Dynamics Days Europe, Corfu, Greece, June 9, 2016.
B. Marquez, L. Larger, D. Brunner, Y.K. Chembo and M. Jacquot, "Bifurcation of spiral-shaped patterns in the phase space of a nonlinear delayed electro-optic system", XXXVI Dynamics Days Europe, Corfu, Greece, June 9 2016.
L. Larger, "Novel brain-inspired computer: photonic harware demonstrating the Reservoir Computing concept", Teratec 2016, 29 Juin 2016 / Palaiseau, France “Architectures de calcul spécialisées : auxiliaires ou challengers ?” -Invited Talk-
L. Larger, "Electro-optic nonlinear delayed feedback systems: From fundamental dynamics to photonic Reservoir Computing", BEYOND! von Neumann Computing, Max Planck Society, ICNS, Harnack Haus Berlin, Germany, May 18-21, 2016 -Invited Talk-
L. Larger, "Processeur photonique bio-inspir\'e : vers un calculateur rapide, puissant, et énergétiquement efficace", IEF / Orsay, Paris XI, France Conférence-Débat "Calcul & Bio-inspiration", 7 Avril 2016 -Invited Talk-
L. Larger, "Chaos communications: From the concept to photonic hardware implementation", 1st international conference on chaotic secure communication, Beijing (20-22 November 2015), China -Invited keynote speaker-
L. Larger, "Nonlinear delay differential equations with a slow integral term: fundamental issues \& applications in photonic", Seminar at TUB: "Synchronization Patterns in Complex Networks: Chimera States and Beyond", TU Berlin (April 28, 2016), Germany -Invited seminar-
L. Larger, B. Marquez, A. Baylón-Fuentes, R. Martinenghi, M. Jacquot, Y. Chembo, V.S. Udaltsov, "Photonic nonlinear delay dynamics for advanced nonlinear processsing: from secure chaos communications to brain-inspired computing", pp. 538-541, paper ID:6263, in proceeding of NOLTA 2015, Hong Kong, China, Dec. 1-4 2015 -Talk in invited session-
L. Grigoryeva, "Capacity of time-delay reservoir computers in the forecasting, filtering, reconstruction, and parallel processing of stochastic stationary and multidimensional signals", Workshop “Dynamical systems and brain-inspired information processing”. Besançon, France, November 3rd, 2015.
J.-P. Ortega, "Time-delay reservoir computers: nonlinear stability of functional differential systems and optimal nonlinear information processing capacity", Conference ``Dynamical Systems and Brain-Inspired Information Processing''. Univ. Franche-Comté, Besançon, France, November 2015.
L. Larger, "Virtual space-time delay dynamics and their chimera states", theme Wave, Soliton and Turbulence in Optical Systems, WIAS, Berlin, 12-14 October 2015, Germany -Invited Talk-
L. Larger, "Reservoir Computing: concepts and hardware implementation in photonic", Workshop du GDR BioComp, Saint-Paul de Vence, 5-8 October 2015, France -Invited Talk-
L. Larger, B. Penkovskyi, Y. Maistrenko, "Virtual space-time delay dynamics and their chimera states", SFB 910 Workshop, Wittenberg, Germany, Sept. 14-16 2015 -Keynote talk-
L. Larger, B. Penkovskyi, Y. Maistrenko, "Chimera states in laser delay dynamics: experiment and modeling", Dynamics Days Europe, Exeter, England, 6-10 September 2015, p.83 -Invited Talk-
L. Larger, "Optoelectronic delay dynamics: cross-fertilization between applications and theory", Dynamics Days Europe, Exeter, England, 6-10 September 2015, p.82 -Invited Talk-
J.-P. Ortega, "Time-delay reservoir computers: nonlinear stability of functional differential systems and optimal nonlinear information processing capacity”, Univ. of Calgary. Seminar of the Mathematics Department, Calgary, Canada, July 2015.
J.-P. Ortega, "Time-delay reservoir computers: nonlinear stability of functional differential systems and optimal nonlinear information processing capacity”, Conference "Classic and Stochastic Geometric Mechanics''. Centre Interfacultaire Bernoulli. EPFL. Lausanne. Switzerland, June 2015 -Opening lecture-
L. Grigoryeva, "Volatility and time series forecasting with non-scalar parametric models and machine-learning based techniques", University of Konstanz, Konstanz, Germany, May 5, 2015.
L. Larger, "Delay dynamics explored through signal and information photonic processing", theme workshop on Delay differential equations in physical sciences and engineering, Fields Institute, Toronto (11-15 Mai 2015), Canada -Invited Talk-
J.-P. Ortega, "Reservoir computing: optimal nonlinear information processing capacity, performance, and universality. Applications to stochastic nonlinear time series forecasting", Univ. Paris-Diderot (Paris VII). Paris. France, February 2015. -invited seminar-
J.-P. Ortega, "Reservoir computing: optimal nonlinear information processing capacity, performance, and universality. Applications to stochastic nonlinear time series forecasting", European Centre for Advanced Research in Economics and Statistics (ECARES). Univ. Libre de Bruxelles, Belgium, February 2015.
L. Grigoryeva, "Reservoir computing: optimal nonlinear information processing capacity, performance, and universality", Applications to stochastic nonlinear time series forecasting. Journée du Laboratoire de Mathématiques, Besançon, France, January 8, 2016.