Timothée Masquelier
Orcid: 0000-0001-8629-9506
According to our database1,
Timothée Masquelier
authored at least 56 papers
between 2007 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Dilated Convolution with Learnable Spacings makes visual models more aligned with humans: a Grad-CAM study.
CoRR, 2024
Brain-inspired Computational Modeling of Action Recognition with Recurrent Spiking Neural Networks Equipped with Reinforcement Delay Learning.
CoRR, 2024
Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
2023
Brain-guided manifold transferring to improve the performance of spiking neural networks in image classification.
J. Comput. Neurosci., November, 2023
Spike time displacement-based error backpropagation in convolutional spiking neural networks.
Neural Comput. Appl., July, 2023
SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence.
CoRR, 2023
CoRR, 2023
Parallel Spiking Neurons with High Efficiency and Long-term Dependencies Learning Ability.
CoRR, 2023
CoRR, 2023
Parallel Spiking Neurons with High Efficiency and Ability to Learn Long-term Dependencies.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
2022
Mitigating Catastrophic Forgetting in Spiking Neural Networks through Threshold Modulation.
Trans. Mach. Learn. Res., 2022
Neural Process. Lett., 2022
Neurocomputing, 2022
Drastically Reducing the Number of Trainable Parameters in Deep CNNs by Inter-layer Kernel-sharing.
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
2021
STiDi-BP: Spike time displacement based error backpropagation in multilayer spiking neural networks.
Neurocomputing, 2021
Frontiers Comput. Neurosci., 2021
Low-Activity Supervised Convolutional Spiking Neural Networks Applied to Speech Commands Recognition.
Proceedings of the IEEE Spoken Language Technology Workshop, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
Fast Threshold Optimization for Multi-Label Audio Tagging Using Surrogate Gradient Learning.
Proceedings of the IEEE International Conference on Acoustics, 2021
2020
Int. J. Neural Syst., 2020
Epileptic Seizure Detection Using a Neuromorphic-Compatible Deep Spiking Neural Network.
Proceedings of the Bioinformatics and Biomedical Engineering, 2020
2019
Bio-inspired digit recognition using reward-modulated spike-timing-dependent plasticity in deep convolutional networks.
Pattern Recognit., 2019
Technical report: supervised training of convolutional spiking neural networks with PyTorch.
CoRR, 2019
S4NN: temporal backpropagation for spiking neural networks with one spike per neuron.
CoRR, 2019
SpykeTorch: Efficient Simulation of Convolutional Spiking Neural Networks with at most one Spike per Neuron.
CoRR, 2019
Proceedings of the Handbook of Memristor Networks., 2019
2018
IEEE Trans. Neural Networks Learn. Syst., 2018
Neural Networks, 2018
Convis: A Toolbox to Fit and Simulate Filter-Based Models of Early Visual Processing.
Frontiers Neuroinformatics, 2018
Optimal Localist and Distributed Coding of Spatiotemporal Spike Patterns Through STDP and Coincidence Detection.
Frontiers Comput. Neurosci., 2018
Combining STDP and Reward-Modulated STDP in Deep Convolutional Spiking Neural Networks for Digit Recognition.
CoRR, 2018
2017
Proceedings of the IEEE International Symposium on Circuits and Systems, 2017
Live demonstration: Hardware implementation of convolutional STDP for on-line visual feature learning.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2017
2016
Bio-inspired unsupervised learning of visual features leads to robust invariant object recognition.
Neurocomputing, 2016
Humans and Deep Networks Largely Agree on Which Kinds of Variation Make Object Recognition Harder.
Frontiers Comput. Neurosci., 2016
STDP allows close-to-optimal spatiotemporal spike pattern detection by single coincidence detector neurons.
CoRR, 2016
Acquisition of visual features through probabilistic spike-timing-dependent plasticity.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016
2015
CoRR, 2015
2013
2012
Relative spike time coding and STDP-based orientation selectivity in the early visual system in natural continuous and saccadic vision: a computational model.
J. Comput. Neurosci., 2012
2011
PLoS Comput. Biol., 2011
2010
Learning to recognize objects using waves of spikes and Spike Timing-Dependent Plasticity.
Proceedings of the International Joint Conference on Neural Networks, 2010
2009
2007
PLoS Comput. Biol., 2007