Publications associées à Modeling perceptual learning: difficulties and how they can be overcome

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Networks of mixed canonical-dissipative systems and dynamic hebbian learning

Max-Olivier Hongler, Julio Rodriguez

We study the dynamics of a network consisting of N diffusively coupled, stable- limit-cycle oscillators on which individual frequencies are parametrized by

w_k, k = 1, . . . ,N

. We introduce a learning rule which influences the wk by driving the system t ...

2009

Modeling perceptual learning: difficulties and how they can be overcome

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Chattez avec Graph Search

Modeling perceptual learning: why mice do not play backgammon

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An online framework for learning novel concepts over multiple cues

Networks of mixed canonical-dissipative systems and dynamic hebbian learning

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Temporal patterning of 'unlearnable' stimuli types does not always enable learning

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Iterative Learning Control based on Stochastic Approximation

Iterative Learning Control based on Stochastic Approximation

Simulating Learning Dynamics in Project Networks

Modeling perceptual learning: why mice do not play backgammon

Evolutionary Advantages of Neuromodulated Plasticity in Dynamic, Reward- based Scenarios

Networks of mixed canonical-dissipative systems and dynamic hebbian learning

An online framework for learning novel concepts over multiple cues

New Fast Training Algorithm Suitable For Hardware Kohonen Neural Networks Designed For Analysis Of Biomedical Signals

Temporal patterning of 'unlearnable' stimuli types does not always enable learning

Neuroevolution: from architectures to learning

Stress, individual differences, and norepinephrine in reinforcement learning-based prediction of mouse behavior in conditioning and spatial learning