Year |
Citation |
Score |
2023 |
Fang W, Chen Y, Ding J, Yu Z, Masquelier T, Chen D, Huang L, Zhou H, Li G, Tian Y. SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence. Science Advances. 9: eadi1480. PMID 37801497 DOI: 10.1126/sciadv.adi1480 |
0.353 |
|
2022 |
Bonilla L, Gautrais J, Thorpe S, Masquelier T. Analyzing time-to-first-spike coding schemes: A theoretical approach. Frontiers in Neuroscience. 16: 971937. PMID 36225737 DOI: 10.3389/fnins.2022.971937 |
0.762 |
|
2021 |
Debat G, Chauhan T, Cottereau BR, Masquelier T, Paindavoine M, Baures R. Event-Based Trajectory Prediction Using Spiking Neural Networks. Frontiers in Computational Neuroscience. 15: 658764. PMID 34108870 DOI: 10.3389/fncom.2021.658764 |
0.381 |
|
2020 |
Kheradpisheh SR, Masquelier T. Temporal Backpropagation for Spiking Neural Networks with One Spike per Neuron. International Journal of Neural Systems. 2050027. PMID 32466691 DOI: 10.1142/S0129065720500276 |
0.812 |
|
2019 |
Mozafari M, Ganjtabesh M, Nowzari-Dalini A, Masquelier T. SpykeTorch: Efficient Simulation of Convolutional Spiking Neural Networks With at Most One Spike per Neuron. Frontiers in Neuroscience. 13: 625. PMID 31354403 DOI: 10.3389/Fnins.2019.00625 |
0.719 |
|
2019 |
Tavanaei A, Ghodrati M, Kheradpisheh SR, Masquelier T, Maida A. Deep learning in spiking neural networks. Neural Networks : the Official Journal of the International Neural Network Society. 111: 47-63. PMID 30682710 DOI: 10.1016/J.Neunet.2018.12.002 |
0.816 |
|
2019 |
Mozafari M, Ganjtabesh M, Nowzari-Dalini A, Thorpe SJ, Masquelier T. Bio-inspired digit recognition using reward-modulated spike-timing-dependent plasticity in deep convolutional networks Pattern Recognition. 94: 87-95. DOI: 10.1016/J.Patcog.2019.05.015 |
0.737 |
|
2018 |
Masquelier T, Kheradpisheh SR. Optimal Localist and Distributed Coding of Spatiotemporal Spike Patterns Through STDP and Coincidence Detection. Frontiers in Computational Neuroscience. 12: 74. PMID 30279653 DOI: 10.3389/Fncom.2018.00074 |
0.805 |
|
2018 |
Chauhan T, Masquelier T, Montlibert A, Cottereau BR. Emergence of binocular disparity selectivity through Hebbian learning. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. PMID 30242050 DOI: 10.1523/JNEUROSCI.1259-18.2018 |
0.421 |
|
2018 |
Mozafari M, Kheradpisheh SR, Masquelier T, Nowzari-Dalini A, Ganjtabesh M. First-Spike-Based Visual Categorization Using Reward-Modulated STDP. Ieee Transactions On Neural Networks and Learning Systems. PMID 29993898 DOI: 10.1109/Tnnls.2018.2826721 |
0.812 |
|
2018 |
Tavanaei A, Masquelier T, Maida A. Representation learning using event-based STDP. Neural Networks : the Official Journal of the International Neural Network Society. 105: 294-303. PMID 29894846 DOI: 10.1016/j.neunet.2018.05.018 |
0.569 |
|
2018 |
Huth J, Masquelier T, Arleo A. Convis: A Toolbox to Fit and Simulate Filter-Based Models of Early Visual Processing. Frontiers in Neuroinformatics. 12: 9. PMID 29563867 DOI: 10.3389/Fninf.2018.00009 |
0.612 |
|
2017 |
Kheradpisheh SR, Ganjtabesh M, Thorpe SJ, Masquelier T. STDP-based spiking deep convolutional neural networks for object recognition. Neural Networks : the Official Journal of the International Neural Network Society. 99: 56-67. PMID 29328958 DOI: 10.1016/J.Neunet.2017.12.005 |
0.823 |
|
2017 |
Ashtiani MN, Kheradpisheh SR, Masquelier T, Ganjtabesh M. Object Categorization in Finer Levels Relies More on Higher Spatial Frequencies and Takes Longer. Frontiers in Psychology. 8: 1261. PMID 28790954 DOI: 10.3389/Fpsyg.2017.01261 |
0.746 |
|
2017 |
Deneux T, Masquelier T, Bermudez MA, Masson GS, Deco G, Vanzetta I. Visual stimulation quenches global alpha range activity in awake primate V4: a case study. Neurophotonics. 4: 031222. PMID 28680907 DOI: 10.1117/1.Nph.4.3.031222 |
0.339 |
|
2017 |
Masquelier T. STDP allows close-to-optimal spatiotemporal spike pattern detection by single coincidence detector neurons. Neuroscience. PMID 28668487 DOI: 10.1016/j.neuroscience.2017.06.032 |
0.494 |
|
2017 |
Rubchinsky LL, Ahn S, Klijn W, Cumming B, Yates S, Karakasis V, Peyser A, Woodman M, Diaz-Pier S, Deraeve J, Vassena E, Alexander W, Beeman D, Kudela P, Boatman-Reich D, ... ... Masquelier T, et al. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 2 Bmc Neuroscience. 18. DOI: 10.1186/S12868-017-0371-2 |
0.71 |
|
2017 |
Thorpe S, Yousefzadeh A, Martin J, Masquelier T. Unsupervised learning of repeating patterns using a novel STDP based algorithm Journal of Vision. 17: 1079. DOI: 10.1167/17.10.1079 |
0.738 |
|
2016 |
Kheradpisheh SR, Ghodrati M, Ganjtabesh M, Masquelier T. Humans and Deep Networks Largely Agree on Which Kinds of Variation Make Object Recognition Harder. Frontiers in Computational Neuroscience. 10: 92. PMID 27642281 DOI: 10.3389/Fncom.2016.00092 |
0.753 |
|
2016 |
Kheradpisheh SR, Ghodrati M, Ganjtabesh M, Masquelier T. Deep Networks Can Resemble Human Feed-forward Vision in Invariant Object Recognition. Scientific Reports. 6: 32672. PMID 27601096 DOI: 10.1038/Srep32672 |
0.756 |
|
2016 |
Masquelier T, Portelli G, Kornprobst P. Microsaccades enable efficient synchrony-based coding in the retina: a simulation study. Scientific Reports. 6: 24086. PMID 27063867 DOI: 10.1038/Srep24086 |
0.403 |
|
2016 |
Kheradpisheh SR, Ganjtabesh M, Masquelier T. Bio-inspired unsupervised learning of visual features leads to robust invariant object recognition Neurocomputing. 205: 382-392. DOI: 10.1016/J.Neucom.2016.04.029 |
0.796 |
|
2014 |
Masquelier T. Oscillations can reconcile slowly changing stimuli with short neuronal integration and STDP timescales. Network (Bristol, England). 25: 85-96. PMID 24571100 DOI: 10.3109/0954898X.2014.881574 |
0.531 |
|
2014 |
Masquelier T, Portelli G, Kornprobst P. Microsaccades enable efficient synchrony-based visual feature learning and detection Bmc Neuroscience. 15. DOI: 10.1186/1471-2202-15-S1-P121 |
0.44 |
|
2014 |
Portelli G, Barrett J, Sernagor E, Masquelier T, Kornprobst P. Rapid neural coding in the mouse retina with the first wave of spikes Bmc Neuroscience. 15. DOI: 10.1186/1471-2202-15-S1-P120 |
0.304 |
|
2013 |
Masquelier T, Deco G. Network bursting dynamics in excitatory cortical neuron cultures results from the combination of different adaptive mechanisms. Plos One. 8: e75824. PMID 24146781 DOI: 10.1371/Journal.Pone.0075824 |
0.38 |
|
2013 |
Masquelier T. Neural variability, or lack thereof. Frontiers in Computational Neuroscience. 7: 7. PMID 23444270 DOI: 10.3389/fncom.2013.00007 |
0.4 |
|
2013 |
Serrano-Gotarredona T, Masquelier T, Prodromakis T, Indiveri G, Linares-Barranco B. STDP and STDP variations with memristors for spiking neuromorphic learning systems. Frontiers in Neuroscience. 7: 2. PMID 23423540 DOI: 10.3389/Fnins.2013.00002 |
0.782 |
|
2013 |
Masquelier T, Gilson M. Optimal spike pattern v.s. noise separation by neurons equipped with STDP Bmc Neuroscience. 14. DOI: 10.1186/1471-2202-14-S1-P142 |
0.489 |
|
2012 |
Masquelier T. Relative spike time coding and STDP-based orientation selectivity in the early visual system in natural continuous and saccadic vision: a computational model. Journal of Computational Neuroscience. 32: 425-41. PMID 21938439 DOI: 10.1007/s10827-011-0361-9 |
0.447 |
|
2011 |
Gilson M, Masquelier T, Hugues E. STDP allows fast rate-modulated coding with Poisson-like spike trains. Plos Computational Biology. 7: e1002231. PMID 22046113 DOI: 10.1371/journal.pcbi.1002231 |
0.523 |
|
2011 |
Masquelier T, Albantakis L, Deco G. The timing of vision - how neural processing links to different temporal dynamics. Frontiers in Psychology. 2: 151. PMID 21747774 DOI: 10.3389/Fpsyg.2011.00151 |
0.454 |
|
2011 |
Zamarreño-Ramos C, Camuñas-Mesa LA, Pérez-Carrasco JA, Masquelier T, Serrano-Gotarredona T, Linares-Barranco B. On spike-timing-dependent-plasticity, memristive devices, and building a self-learning visual cortex. Frontiers in Neuroscience. 5: 26. PMID 21442012 DOI: 10.3389/Fnins.2011.00026 |
0.784 |
|
2011 |
Deco G, Buehlmann A, Masquelier T, Hugues E. The role of rhythmic neural synchronization in rest and task conditions. Frontiers in Human Neuroscience. 5: 4. PMID 21326617 DOI: 10.3389/Fnhum.2011.00004 |
0.454 |
|
2010 |
Masquelier T, Serre T, Thorpe S, Poggio T. Learning simple and complex cells-like receptive fields from natural images: a plausibility proof Journal of Vision. 7: 81-81. DOI: 10.1167/7.9.81 |
0.478 |
|
2010 |
Masquelier T, Thorpe SJ. Learning to recognize objects using waves of spikes and spike timing-dependent plasticity Proceedings of the International Joint Conference On Neural Networks. DOI: 10.1109/IJCNN.2010.5596934 |
0.545 |
|
2009 |
Masquelier T, Hugues E, Deco G, Thorpe SJ. Oscillations, phase-of-firing coding, and spike timing-dependent plasticity: an efficient learning scheme. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 29: 13484-93. PMID 19864561 DOI: 10.1523/Jneurosci.2207-09.2009 |
0.651 |
|
2009 |
Masquelier T, Guyonneau R, Thorpe SJ. Competitive STDP-based spike pattern learning. Neural Computation. 21: 1259-76. PMID 19718815 DOI: 10.1162/neco.2008.06-08-804 |
0.805 |
|
2009 |
Gilson M, Masquelier T, Hugues E, Burkittt AN. Pattern learning using spike-timing-dependent plasticity: a theoretical approach Bmc Neuroscience. 10. DOI: 10.1186/1471-2202-10-S1-P199 |
0.526 |
|
2008 |
Masquelier T, Guyonneau R, Thorpe SJ. Spike timing dependent plasticity finds the start of repeating patterns in continuous spike trains. Plos One. 3: e1377. PMID 18167538 DOI: 10.1371/journal.pone.0001377 |
0.794 |
|
2007 |
Masquelier T, Thorpe SJ. Unsupervised learning of visual features through spike timing dependent plasticity. Plos Computational Biology. 3: e31. PMID 17305422 DOI: 10.1371/journal.pcbi.0030031 |
0.682 |
|
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