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Nicolas Frémaux
Nicolas Frémaux
PhD student, Brain Mind Institiute, Ecole Polytechnique de Lausanne
Verified email at epfl.ch
Title
Cited by
Cited by
Year
Neuromodulated spike-timing-dependent plasticity, and theory of three-factor learning rules
N Frémaux, W Gerstner
Frontiers in neural circuits 9, 85, 2016
4212016
Reinforcement learning using a continuous time actor-critic framework with spiking neurons
N Frémaux, H Sprekeler, W Gerstner
PLoS computational biology 9 (4), e1003024, 2013
2052013
Functional requirements for reward-modulated spike-timing-dependent plasticity
N Frémaux, H Sprekeler, W Gerstner
Journal of Neuroscience 30 (40), 13326-13337, 2010
1722010
Spike-based reinforcement learning in continuous state and action space: when policy gradient methods fail
E Vasilaki, N Frémaux, R Urbanczik, W Senn, W Gerstner
PLoS computational biology 5 (12), e1000586, 2009
1482009
Reward-based learning under hardware constraints—using a RISC processor embedded in a neuromorphic substrate
S Friedmann, N Frémaux, J Schemmel, W Gerstner, K Meier
Frontiers in Neuroscience 7, 160, 2013
412013
Perceptual learning, roving and the unsupervised bias
MH Herzog, KC Aberg, N Frémaux, W Gerstner, H Sprekeler
Vision research 61, 95-99, 2012
392012
Models of Reward-Modulated Spike-Timing-Dependent Plasticity
N Frémaux
EPFL, 2013
12013
Reward-modulated spike timing-dependent plasticity requires a reward-prediction system
N Frémaux, H Sprekeler, W Gerstner
Front. Neurosci. Conference Abstract: Computational and Systems Neuroscience, 2010
2010
Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy
E Vasilaki, N Frémaux, R Urbanczik, W Senn, W Gerstner
2009
LCN
L Badel, MLLR Barry, S Becker, G Bellec, JM Brea, EW Bumbacher, ...
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