Guillaume BELLEC

About Guillaume BELLEC

Guillaume BELLEC, With an exceptional h-index of 10 and a recent h-index of 10 (since 2020), a distinguished researcher at École Polytechnique Fédérale de Lausanne, specializes in the field of computational neuroscience, machine learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Fast learning without synaptic plasticity in spiking neural networks

Trial matching: capturing variability with data-constrained spiking neural networks

Spiking Music: Audio Compression with Event Based Auto-encoders

Corrigendum to'An exact mapping from ReLU networks to spiking neural networks'[Neural Networks Volume 168 (2023) Pages 74-88]

An exact mapping from ReLU networks to spiking neural networks

Are training trajectories of deep single-spike and deep ReLU network equivalent?

GateON: an unsupervised method for large scale continual learning

Mesoscopic modeling of hidden spiking neurons

Guillaume BELLEC Information

University

Position

___

Citations(all)

1648

Citations(since 2020)

1593

Cited By

524

hIndex(all)

10

hIndex(since 2020)

10

i10Index(all)

11

i10Index(since 2020)

10

Email

University Profile Page

Google Scholar

Guillaume BELLEC Skills & Research Interests

computational neuroscience

machine learning

Top articles of Guillaume BELLEC

Fast learning without synaptic plasticity in spiking neural networks

Scientific Reports

2024/4/12

Trial matching: capturing variability with data-constrained spiking neural networks

Advances in neural information processing systems

2024/2/13

Spiking Music: Audio Compression with Event Based Auto-encoders

arXiv preprint arXiv:2402.01571

2024/2/2

Guillaume Bellec
Guillaume Bellec

H-Index: 9

Corrigendum to'An exact mapping from ReLU networks to spiking neural networks'[Neural Networks Volume 168 (2023) Pages 74-88]

Neural networks: the official journal of the International Neural Network Society

2023/11/13

An exact mapping from ReLU networks to spiking neural networks

Neural Networks

2023/11/1

Are training trajectories of deep single-spike and deep ReLU network equivalent?

arXiv preprint arXiv:2306.08744

2023/6/14

GateON: an unsupervised method for large scale continual learning

arXiv preprint arXiv:2306.01690

2023/6/2

Guillaume Bellec
Guillaume Bellec

H-Index: 9

Wulfram Gerstner
Wulfram Gerstner

H-Index: 50

Mesoscopic modeling of hidden spiking neurons

Advances in Neural Information Processing Systems

2022

Guillaume Bellec
Guillaume Bellec

H-Index: 9

Wulfram Gerstner
Wulfram Gerstner

H-Index: 50

Local plasticity rules can learn deep representations using self-supervised contrastive predictions

Thirty-Fifth Conference on Neural Information Processing Systems, 2021

2021/11/30

Spike frequency adaptation supports network computations on temporally dispersed information

Elife

2021/7/26

Fitting summary statistics of neural data with a differentiable spiking network simulator

Advances in Neural Information Processing Systems

2021/6/18

Revisiting the role of synaptic plasticity and network dynamics for fast learning in spiking neural networks

bioRxiv

2021/1/27

Spike-frequency adaptation contributes long short-term memory to networks of spiking neurons

2020/9/29

A solution to the learning dilemma for recurrent networks of spiking neurons

Nature Communications

2020/7/17

See List of Professors in Guillaume BELLEC University(École Polytechnique Fédérale de Lausanne)

Co-Authors

academic-engine