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Stefan Schliebs
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Span: Spike pattern association neuron for learning spatio-temporal spike patterns
A Mohemmed, S Schliebs, S Matsuda, N Kasabov
International journal of neural systems 22 (04), 1250012, 2012
3312012
Quantum-inspired evolutionary algorithm: A multimodel EDA
MD Platel, S Schliebs, N Kasabov
IEEE Transactions on Evolutionary Computation 13 (6), 1218-1232, 2008
1982008
Evolving spiking neural network—a survey
S Schliebs, N Kasabov
Evolving Systems 4, 87-98, 2013
1822013
Training spiking neural networks to associate spatio-temporal input–output spike patterns
A Mohemmed, S Schliebs, S Matsuda, N Kasabov
Neurocomputing 107, 3-10, 2013
1082013
Integrated feature and parameter optimization for an evolving spiking neural network: Exploring heterogeneous probabilistic models
S Schliebs, M Defoin-Platel, S Worner, N Kasabov
Neural Networks 22 (5-6), 623-632, 2009
982009
A versatile quantum-inspired evolutionary algorithm
MD Platel, S Schliebs, N Kasabov
2007 IEEE Congress on Evolutionary Computation, 423-430, 2007
852007
On the probabilistic optimization of spiking neural networks
S Schliebs, N Kasabov, M Defoin-Platel
International Journal of Neural Systems 20 (06), 481-500, 2010
532010
Integrated feature and parameter optimization for an evolving spiking neural network
S Schliebs, M Defoin-Platel, N Kasabov
Advances in Neuro-Information Processing: 15th International Conference …, 2009
492009
Method for training a spiking neuron to associate input-output spike trains
A Mohemmed, S Schliebs, S Matsuda, N Kasabov
International Conference on Engineering Applications of Neural Networks, 219-228, 2011
382011
Towards spatio-temporal pattern recognition using evolving spiking neural networks
S Schliebs, N Nuntalid, N Kasabov
Neural Information Processing. Theory and Algorithms: 17th International …, 2010
282010
Constructing robust liquid state machines to process highly variable data streams
S Schliebs, M Fiasché, N Kasabov
Artificial Neural Networks and Machine Learning–ICANN 2012: 22nd …, 2012
232012
Bioengineering silicon quantum dot theranostics using a network analysis of metabolomic and proteomic data in cardiac ischemia
F Erogbogbo, J May, M Swihart, PN Prasad, K Smart, S El Jack, D Korcyk, ...
Theranostics 3 (9), 719, 2013
212013
Are probabilistic spiking neural networks suitable for reservoir computing?
S Schliebs, A Mohemmed, N Kasabov
The 2011 International Joint Conference on Neural Networks, 3156-3163, 2011
212011
Reservoir-based evolving spiking neural network for spatio-temporal pattern recognition
S Schliebs, HNA Hamed, N Kasabov
Neural Information Processing: 18th International Conference, ICONIP 2011 …, 2011
202011
Determining factors that influence the dispersal of a pelagic species: A comparison between artificial neural networks and evolutionary algorithms
DR Pontin, S Schliebs, SP Worner, MJ Watts
Ecological Modelling 222 (10), 1657-1665, 2011
162011
Computational modeling with spiking neural networks
S Schliebs, N Kasabov
Springer handbook of bio-/neuroinformatics, 625-646, 2014
152014
SPAN: A neuron for precise-time spike pattern association
A Mohemmed, S Schliebs, N Kasabov
Neural Information Processing: 18th International Conference, ICONIP 2011 …, 2011
152011
Quantum-inspired feature and parameter optimisation of evolving spiking neural networks with a case study from ecological modeling
S Schliebs, MD Platel, S Worner, N Kasabov
2009 international joint conference on neural networks, 2833-2840, 2009
152009
Optimization of spiking neural networks with dynamic synapses for spike sequence generation using PSO
A Mohemmed, S Matsuda, S Schliebs, K Dhoble, N Kasabov
The 2011 International Joint Conference on Neural Networks, 2969-2974, 2011
142011
Ecological informatics for the prediction and management of invasive species
SP Worner, M Gevrey, T Ikeda, G Leday, J Pitt, S Schliebs, S Soltic
Springer handbook of bio-/neuroinformatics, 565-583, 2014
122014
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