Echo State Gaussian Process

@article{Chatzis2011EchoSG,
  title={Echo State Gaussian Process},
  author={Sotirios P. Chatzis and Y. Demiris},
  journal={IEEE Transactions on Neural Networks},
  year={2011},
  volume={22},
  pages={1435-1445}
}
  • S. ChatzisY. Demiris
  • Published 1 September 2011
  • Computer Science
  • IEEE Transactions on Neural Networks
Echo state networks (ESNs) constitute a novel approach to recurrent neural network (RNN) training, with an RNN (the reservoir) being generated randomly, and only a readout being trained using a simple computationally efficient algorithm. ESNs have greatly facilitated the practical application of RNNs, outperforming classical approaches on a number of benchmark tasks. In this paper, we introduce a novel Bayesian approach toward ESNs, the echo state Gaussian process (ESGP). The ESGP combines the… 

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