Publications associées à Unsupervised Learning of Phase-Change-Based Neuromorphic Systems

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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

Unsupervised Learning of Phase-Change-Based Neuromorphic Systems

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Path planning versus cue responding: a bioinspired model of switching between navigation strategies

Development and Validation of a Spike Detection and Classification Algorithm Aimed at Implementation on Hardware Devices

Code-specific policy gradient rules for spiking neurons

Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail

Stimulus sampling as an exploration mechanism for fast reinforcement learning

Perceptual learning: why mice do not play backgammon

Networks of mixed canonical-dissipative systems and dynamic hebbian learning

Learning and Predicting Multimodal Daily Life Patterns from Cell Phones

Establishing a Novel Modeling Tool: A Python-based Interface for a Neuromorphic Hardware System

Neuroevolution: from architectures to learning

Path planning versus cue responding: a bioinspired model of switching between navigation strategies

Development and Validation of a Spike Detection and Classification Algorithm Aimed at Implementation on Hardware Devices

Stimulus sampling as an exploration mechanism for fast reinforcement learning

Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail

Learning and Predicting Multimodal Daily Life Patterns from Cell Phones

Perceptual learning: why mice do not play backgammon

Establishing a Novel Modeling Tool: A Python-based Interface for a Neuromorphic Hardware System

Networks of mixed canonical-dissipative systems and dynamic hebbian learning

Neuroevolution: from architectures to learning

Code-specific policy gradient rules for spiking neurons