Laurent U. Perrinet
Orcid: 0000-0002-9536-010X
According to our database1,
Laurent U. Perrinet
authored at least 48 papers
between 2001 and 2024.
Collaborative distances:
Collaborative distances:
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Online presence:
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on zbmath.org
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on twitter.com
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on orcid.org
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on github.com
On csauthors.net:
Bibliography
2024
Neuromorph. Comput. Eng., 2024
CoRR, 2024
CoRR, 2024
2023
Biol. Cybern., October, 2023
Learning heterogeneous delays in a layer of spiking neurons for fast motion detection.
Biol. Cybern., October, 2023
Time-to-Contact Map by Joint Estimation of Up-to-Scale Inverse Depth and Global Motion using a Single Event Camera.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Proceedings of the Artificial Neural Networks and Machine Learning, 2023
Proceedings of the Artificial Neural Networks and Machine Learning, 2023
2022
Pooling strategies in V1 can account for the functional and structural diversity across species.
PLoS Comput. Biol., 2022
What You See Is What You Transform: Foveated Spatial Transformers as a bio-inspired attention mechanism.
Proceedings of the International Joint Conference on Neural Networks, 2022
Learning hetero-synaptic delays for motion detection in a single layer of spiking neurons.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022
2021
Sparse deep predictive coding captures contour integration capabilities of the early visual system.
PLoS Comput. Biol., 2021
Proceedings of the 18th International Conference on Content-Based Multimedia Indexing, 2021
2020
Humans adapt their anticipatory eye movements to the volatility of visual motion properties.
PLoS Comput. Biol., 2020
Proceedings of the Active Inference - First International Workshop, 2020
2019
2018
Neural Comput., 2018
M<sup>2</sup>APix: A Bio-Inspired Auto-Adaptive Visual Sensor for Robust Ground Height Estimation.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2018
2017
2016
Proceedings of the 6th European Workshop on Visual Information Processing, 2016
2015
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Proceedings of the 23rd European Signal Processing Conference, 2015
2014
Signature of an anticipatory response in area VI as modeled by a probabilistic model and a spiking neural network.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014
2013
Anisotropic connectivity implements motion-based prediction in a spiking neural network.
Frontiers Comput. Neurosci., 2013
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2013
2012
Neural Comput., 2012
Complex dynamics in recurrent cortical networks based on spatially realistic connectivities.
Frontiers Comput. Neurosci., 2012
2010
Functional consequences of correlated excitatory and inhibitory conductances in cortical networks.
J. Comput. Neurosci., 2010
A novel bio-inspired static image compression scheme for noisy data transmission over low-bandwidth channels.
Proceedings of the IEEE International Conference on Acoustics, 2010
2008
Frontiers Neuroinformatics, 2008
2007
Sparse Approximation of Images Inspired from the Functional Architecture of the Primary Visual Areas.
EURASIP J. Adv. Signal Process., 2007
2005
Proceedings of the Artificial Neural Networks: Biological Inspirations, 2005
2004
IEEE Trans. Neural Networks, 2004
Finding independent components using spikes: A natural result of hebbian learning in a sparse spike coding scheme.
Nat. Comput., 2004
Sparse spike coding in an asynchronous feed-forward multi-layer neural network using matching pursuit.
Neurocomputing, 2004
Neurocomputing, 2004
2002
Proceedings of the 10th Eurorean Symposium on Artificial Neural Networks, 2002
2001
Networks of integrate-and-fire neuron using rank order coding A: How to implement spike time dependent Hebbian plasticity.
Neurocomputing, 2001
Networks of integrate-and-fire neurons using Rank Order Coding B: Spike timing dependent plasticity and emergence of orientation selectivity.
Neurocomputing, 2001