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BC
Bruno Cessac
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Documents
Présentation
Publications
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Exact computation of the Maximum Entropy Potential of spiking neural networksmodelsPhysical Review E , 2014, 89 (052117), pp.13
Article dans une revue
hal-01095599v1
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Parameter Estimation for Spatio-Temporal Maximum Entropy Distributions: Application to Neural Spike TrainsEntropy, 2014, 16 (4), pp.2244-2277. ⟨10.3390/e16042244⟩
Article dans une revue
hal-01096213v1
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Spike train statistics: from mathematical models to software to experiments6th Workshop in Computational Neuroscience in Marseille, Mar 2014, Marseille, France
Communication dans un congrès
hal-01095746v1
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Effects of Cellular Homeostatic Intrinsic Plasticity on Dynamical and Computational Properties of Biological Recurrent Neural NetworksLACONEU 2014, Jan 2014, Valparaiso, Chile. 1 page
Communication dans un congrès
hal-01095601v1
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Neural Networks DynamicsLACONEU 2014, Jan 2014, Valparaiso, Chile
Communication dans un congrès
hal-01095600v1
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From Habitat to Retina: Neural Population Coding using Natural MoviesPoster de conférence hal-01095781v1 |
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Can We Hear the Shape of a Maximum Entropy Potential From Spike Trains?Poster de conférence hal-01095760v1 |