Timothée Masquelier
Timothée Masquelier
CNRS Researcher (DR2), Cerco (CNRS-UT3), TMBI (Univ. Toulouse)
Verified email at - Homepage
Cited by
Cited by
Deep learning in spiking neural networks
A Tavanaei, M Ghodrati, SR Kheradpisheh, T Masquelier, A Maida
Neural Networks 111, 47-63, 2019
STDP-based spiking deep convolutional neural networks for object recognition
SR Kheradpisheh, M Ganjtabesh, SJ Thorpe, T Masquelier
Neural Networks, 2017
Unsupervised learning of visual features through spike timing dependent plasticity
T Masquelier, SJ Thorpe
PLoS Computational Biology 3 (2), e31, 2007
On spike-timing-dependent-plasticity, memristive devices, and building a self-learning visual cortex
C Zamarreño-Ramos, LA Camuñas-Mesa, JA Pérez-Carrasco, ...
Frontiers in neuroscience 5, 2011
STDP and STDP variations with memristors for spiking neuromorphic learning systems
T Serrano-Gotarredona, T Masquelier, T Prodromakis, G Indiveri, ...
Frontiers in Neuroscience 7, 2013
Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks
W Fang, Z Yu, Y Chen, T Masquelier, T Huang, Y Tian
arXiv preprint arXiv:2007.05785, 2020
Competitive STDP-based spike pattern learning
T Masquelier, R Guyonneau, SJ Thorpe
Neural computation 21 (5), 1259-1276, 2009
Deep residual learning in spiking neural networks
W Fang, Z Yu, Y Chen, T Huang, T Masquelier, Y Tian
Thirty-Fifth Conference on Neural Information Processing Systems, 2021
Spike timing dependent plasticity finds the start of repeating patterns in continuous spike trains
T Masquelier, R Guyonneau, SJ Thorpe
PloS one 3 (1), e1377, 2008
Temporal backpropagation for spiking neural networks with one spike per neuron
SR Kheradpisheh, T Masquelier
International Journal of Neural Systems, 2020
Bio-inspired digit recognition using reward-modulated spike-timing-dependent plasticity in deep convolutional networks
M Mozafari, M Ganjtabesh, A Nowzari-Dalini, SJ Thorpe, T Masquelier
Pattern Recognition 94, 87-95, 2019
Deep networks can resemble human feed-forward vision in invariant object recognition
SR Kheradpisheh, M Ghodrati, M Ganjtabesh, T Masquelier
Scientific reports 6 (1), 32672, 2016
Oscillations, phase-of-firing coding, and spike timing-dependent plasticity: an efficient learning scheme
T Masquelier, E Hugues, G Deco, SJ Thorpe
The Journal of Neuroscience 29 (43), 13484-13493, 2009
First-spike-based visual categorization using reward-modulated STDP
M Mozafari, SR Kheradpisheh, T Masquelier, A Nowzari-Dalini, ...
IEEE transactions on neural networks and learning systems 29 (12), 6178-6190, 2018
Bio-inspired unsupervised learning of visual features leads to robust invariant object recognition
SR Kheradpisheh, M Ganjtabesh, T Masquelier
Neurocomputing 205, 382-392, 2016
Spyketorch: Efficient simulation of convolutional spiking neural networks with at most one spike per neuron
M Mozafari, M Ganjtabesh, A Nowzari-Dalini, T Masquelier
Frontiers in neuroscience 13, 625, 2019
Relative spike time coding and STDP-based orientation selectivity in the early visual system in natural continuous and saccadic vision: a computational model
T Masquelier
Journal of computational neuroscience 32 (3), 425-441, 2012
SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence
W Fang, Y Chen, J Ding, Z Yu, T Masquelier, D Chen, L Huang, H Zhou, ...
Science Advances 9 (40), eadi1480, 2023
Neural variability, or lack thereof
T Masquelier
Frontiers in computational neuroscience 7, 7, 2013
Bs4nn: Binarized spiking neural networks with temporal coding and learning
SR Kheradpisheh, M Mirsadeghi, T Masquelier
Neural Processing Letters, 1-19, 2021
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