- 9
BC
Bruno Cessac
9
Documents
Présentation
Publications
- 7
- 9
- 7
- 7
- 4
- 1
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
|
|
Exact computation of the Maximum Entropy Potential of spiking neural networksmodelsPhysical Review E , 2014, 89 (052117), pp.13
Article dans une revue
hal-01095599v1
|
Confronting mean-field theories to measurements a perspective from neuroscienceConfronting mean-field theories to measurements a perspective from neuroscience, Jan 2015, Paris, France
Communication dans un congrès
hal-01225619v1
|
|
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
|
|
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
|
|
Neural Networks DynamicsLACONEU 2014, Jan 2014, Valparaiso, Chile
Communication dans un congrès
hal-01095600v1
|
|
Can We Hear the Shape of a Maximum Entropy Potential From Spike Trains?Poster de conférence hal-01095760v1 |
|
From Habitat to Retina: Neural Population Coding using Natural MoviesPoster de conférence hal-01095781v1 |
|
Spike Train Statistics from Empirical Facts to Theory: The Case of the RetinaFrédéric Cazals and Pierre Kornprobst. Modeling in Computational Biology and Biomedicine: A Multidisciplinary Endeavor, Springer, 2013
Chapitre d'ouvrage
hal-00640507v1
|