Jérémie Cabessa
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| Cabessa J, Tchaptchet A. (2020) Automata complete computation with Hodgkin-Huxley neural networks composed of synfire rings. Neural Networks : the Official Journal of the International Neural Network Society. 126: 312-334 |
| Cabessa J. (2019) Turing complete neural computation based on synaptic plasticity. Plos One. 14: e0223451 |
| Cabessa J, Finkel O. (2019) Computational capabilities of analog and evolving neural networks over infinite input streams Journal of Computer and System Sciences. 101: 86-99 |
| Cabessa J, Villa AEP. (2018) Attractor dynamics of a Boolean model of a brain circuit controlled by multiple parameters. Chaos (Woodbury, N.Y.). 28: 106318 |
| Cabessa J, Villa AE. (2016) Expressive power of first-order recurrent neural networks determined by their attractor dynamics Journal of Computer and System Sciences. 82: 1232-1250 |
| Cabessa J, Siegelmann HT. (2014) The super-Turing computational power of plastic recurrent neural networks. International Journal of Neural Systems. 24: 1450029 |
| Cabessa J, Villa AE. (2014) An attractor-based complexity measurement for Boolean recurrent neural networks. Plos One. 9: e94204 |
| Cabessa J, Siegelmann HT. (2012) The computational power of interactive recurrent neural networks. Neural Computation. 24: 996-1019 |
| Cabessa J, Villa AE. (2012) The expressive power of analog recurrent neural networks on infinite input streams Theoretical Computer Science. 436: 23-34 |
| Cabessa J, Siegelmann HT. (2011) Evolving recurrent neural networks are super-Turing Proceedings of the International Joint Conference On Neural Networks. 3200-3206 |