Herbert Jaeger

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Mantas LukoševičiusKaunas University of TechnologyVerified email at ktu.lt
Harald HaasThe University of EdinburghVerified email at ed.ac.uk
Benjamin SchrauwenProfessor of Machine Learning, Ghent UniversityVerified email at ugent.be
Paul PloegerProfessor for Autonomous SystemsVerified email at h-brs.de
Manjunath GUniversity of PretroriaVerified email at up.ac.za
Stefan KiebelProfessor of Neuroimaging, Technische Universität Dresden, GermanyVerified email at tu-dresden.de
Michael ThonJacobs University BremenVerified email at jacobs-university.de
jose principeprofessor of ECE, U. of FloridaVerified email at cnel.ufl.edu
Wolfgang MaassProfessor of Computer Science, Graz University of TechnologyVerified email at igi.tugraz.at
Andreas KollingAmazon RoboticsVerified email at amazon.com
Joachim HertzbergUniversity of Osnabrück and DFKI, OsnabrückVerified email at uos.de
Razvan PascanuResearch Scientist at Google DeepMindVerified email at google.com
Luc SteelsICREA - Institut de Biologia Evolutiva (UPF-CSIC)Verified email at upf.edu
Ted BriscoeProfessor of Computational Linguistics, MBZUAIVerified email at mbzuai.ac.ae
Gerhard JägerProfessor für Allgemeine Sprachwissenschaft, TübingenVerified email at uni-tuebingen.de
Jochen TrieschFrankfurt Institute for Advanced StudiesVerified email at fias.uni-frankfurt.de
Giovanni IndiveriUniversità di Genova, Italia (since December 1st, 2019, previously at Università del Salento, Italy)Verified email at unige.it
Douglas EckGoogle Research, Brain TeamVerified email at google.com

Herbert Jaeger

Rijksuniversiteit Groningen

Verified email at rug.nl - Homepage

Recurrent neural networks machine learning stochastic dynamical systems theory of non-symbolic computing


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The “echo state” approach to analysing and training recurrent neural networks-with an erratum note H Jaeger Bonn, Germany: German National Research Center for Information Technology …, 2001	3902	2001
Harnessing nonlinearity: Predicting chaotic systems and saving energy in wireless communication H Jaeger, H Haas science 304 (5667), 78-80, 2004	3628	2004
Reservoir computing approaches to recurrent neural network training M Lukoševičius, H Jaeger Computer science review 3 (3), 127-149, 2009	2746	2009
Tutorial on training recurrent neural networks, covering BPPT, RTRL, EKF and the" echo state network" approach H Jaeger GMD-Forschungszentrum Informationstechnik 5 (1), 2002	1382	2002
Optimization and applications of echo state networks with leaky-integrator neurons H Jaeger, M Lukoševičius, D Popovici, U Siewert Neural networks 20 (3), 335-352, 2007	930	2007
Short term memory in echo state networks. gmd-report 152 H Jaeger GMD-German National Research Institute for Computer Science (2002), 2002	868*	2002
Adaptive nonlinear system identification with echo state networks H Jaeger Advances in neural information processing systems 15, 2002	791	2002
Re-visiting the echo state property IB Yildiz, H Jaeger, SJ Kiebel Neural networks 35, 1-9, 2012	455	2012
Reservoir computing trends M Lukoševičius, H Jaeger, B Schrauwen KI-Künstliche Intelligenz 26, 365-371, 2012	417	2012
Echo state network H Jaeger scholarpedia 2 (9), 2330, 2007	396	2007
Observable operator models for discrete stochastic time series H Jaeger Neural computation 12 (6), 1371-1398, 2000	244	2000
Echo state property linked to an input: Exploring a fundamental characteristic of recurrent neural networks G Manjunath, H Jaeger Neural computation 25 (3), 671-696, 2013	212	2013
Special issue on echo state networks and liquid state machines. H Jaeger, W Maass, J Principe Elsevier Science, 2007	205	2007
Reservoir riddles: suggestions for echo state network research H Jaeger Proceedings. 2005 IEEE International Joint Conference on Neural Networks …, 2005	144	2005
Dual dynamics: Designing behavior systems for autonomous robots H Jaeger, T Christaller Artificial Life and Robotics 2, 108-112, 1998	130	1998
Controlling recurrent neural networks by conceptors H Jaeger arXiv preprint arXiv:1403.3369, 2014	123	2014
Discovering multiscale dynamical features with hierarchical echo state networks H Jaeger Jacobs University Bremen, 2007	118	2007
Overcoming catastrophic interference using conceptor-aided backpropagation X He, H Jaeger International Conference on Learning Representations, 2018	104	2018
A neurodynamical model for working memory R Pascanu, H Jaeger Neural networks 24 (2), 199-207, 2011	101	2011
Long short-term memory in echo state networks: Details of a simulation study H Jaeger Jacobs University Bremen, 2012	82	2012

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