André Grüning

Frontiers Comput. Neurosci., 2021

2020

Supervised Learning in Temporally-Coded Spiking Neural Networks with Approximate Backpropagation.

[BibT_eX]

[DOI]

CoRR, 2020

2019

Learning Algorithms and Signal Processing for Brain-Inspired Computing [From the Guest Editors].

[BibT_eX]

[DOI]

Osvaldo Simeone

Bipin Rajendran

Evangelos Eleftheriou

Mike Davies

Sophie Denève

Guang-Bin Huang

IEEE Signal Process. Mag., 2019

An Introduction to Probabilistic Spiking Neural Networks: Probabilistic Models, Learning Rules, and Applications.

[BibT_eX]

[DOI]

IEEE Signal Process. Mag., 2019

An Introduction to Probabilistic Spiking Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2019

2017

An efficient method for online detection of polychronous patterns in spiking neural networks.

[BibT_eX]

[DOI]

Joseph Chrol-Cannon

Yaochu Jin

Neurocomputing, 2017

An Efficient Method for online Detection of Polychronous Patterns in Spiking Neural Network.

[BibT_eX]

[DOI]

Joseph Chrol-Cannon

Yaochu Jin

CoRR, 2017

2016

Optimal Supervised Learning in Spiking Neural Networks for Precise Temporal Encoding.

[BibT_eX]

[DOI]

CoRR, 2016

2015

Learning Spatiotemporally Encoded Pattern Transformations in Structured Spiking Neural Networks.

[BibT_eX]

[DOI]

Neural Comput., 2015

Encoding Spike Patterns in Multilayer Spiking Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2015

Spike-timing neuronal modelling of forgetting in immediate serial recall.

[BibT_eX]

[DOI]

Panagiotis Ioannou

Matthew Casey

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014

Factors Influencing Polychronous Group Sustainability as a Model of Working Memory.

[BibT_eX]

[DOI]

Panagiotis Ioannou

Matthew Casey

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

Classifying Spike Patterns by Reward-Modulated STDP.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

Spiking Neural Networks: Principles and Challenges.

[BibT_eX]

[DOI]

Sander M. Bohté

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Classifying Patterns in a Spiking Neural Network.

[BibT_eX]

[DOI]

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

2013

Supervised Learning in Multilayer Spiking Neural Networks.

[BibT_eX]

[DOI]

Neural Comput., 2013

Learning Temporally Precise Spiking Patterns through Reward Modulated Spike-Timing-Dependent Plasticity.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2013, 2013

2012

Supervised Learning of Logical Operations in Layered Spiking Neural Networks with Spike Train Encoding.

[BibT_eX]

[DOI]

Neural Process. Lett., 2012

Improved spike-timed mappings using a tri-phasic spike timing-dependent plasticity rule.

[BibT_eX]

[DOI]

Scott V. Notley

Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

The emergence of polychronous groups under varying input patterns, plasticity rules and network connectivities.

[BibT_eX]

[DOI]

Joseph Chrol-Cannon

Yaochu Jin

Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Learning Anticipation through Priming in Spatio-temporal Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Neural Information Processing - 19th International Conference, 2012

Pair-Associate Learning with Modulated Spike-Time Dependent Plasticity.

[BibT_eX]

[DOI]

Scott V. Notley

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

Classification of Distorted Patterns by Feed-Forward Spiking Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

Evaluating the Effect of Spiking Network Parameters on Polychronization.

[BibT_eX]

[DOI]

Panagiotis Ioannou

Matthew Casey

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

Neural Networks in Cognitive Science.

[BibT_eX]

[DOI]

Proceedings of the Biologically Inspired Networking and Sensing, 2012

2011

Reference time in SpikeProp.

[BibT_eX]

[DOI]

Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

2010

A distributed model of memory for the McGurk effect.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2010

Supervised Associative Learning in Spiking Neural Network.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks - ICANN 2010, 2010

Modelling the McGurk effect.

[BibT_eX]

[DOI]

Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010

2007

Elman Backpropagation as Reinforcement for Simple Recurrent Networks.

[BibT_eX]

[DOI]

Neural Comput., 2007

2006

Stack-like and queue-like dynamics in recurrent neural networks.

[BibT_eX]

[DOI]

Connect. Sci., 2006

2005

Back-Propagation as Reinforcement in Prediction Tasks.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

2004

Neural networks and the complexity of languages.

[BibT_eX]

[DOI]