Unsupervised Learning

An adaptive homeostatic algorithm for the unsupervised learning of visual features
The formation of structure in the visual system, that is, of the connections between cells within neural populations, is by large an …
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Role of homeostasis in learning sparse representations
Neurons in the input layer of primary visual cortex in primates develop edge-like receptive fields. One approach to understanding the …
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Role of homeostasis in learning sparse representations
Neural Codes for Adaptive Sparse Representations of Natural Images
I will illustrate in this talk how computational neuroscience may inspire and be inspired by mathematical image processing. Focusing on …
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Neural Codes for Adaptive Sparse Representations of Natural Images
An efficiency razor for model selection and adaptation in the primary visual cortex
We describe the theoretical formulation of a learning algorithm in a model of the primary visual cortex (V1) and present results of the …
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Finding Independent Components using spikes : a natural result of Hebbian learning in a sparse spike coding scheme
To understand possible strategies of temporal spike coding in the central nervous system, we study functional neuromimetic models of …
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A generative model for Spike Time Dependent Hebbian Plasticity
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Apprentissage hebbien d'un reseau de neurones asynchrone a codage par rang
Travail de master sur la STDP.
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