epfl-lcn Goto Github PK
Name: EPFL-LCN
Type: Organization
Bio: Laboratory of Computational Neuroscience @ EPFL
Location: Lausanne, Switzerland
Blog: http://lcn1.epfl.ch/
Name: EPFL-LCN
Type: Organization
Bio: Laboratory of Computational Neuroscience @ EPFL
Location: Lausanne, Switzerland
Blog: http://lcn1.epfl.ch/
Public code for the paper Muscinelli, Gerstner and Schwalger, ArXiv: 1812.06925v2 (2018)
To optimize a neural net using gradient flow and to visualize its weights at convergence.
Python exercises accompanying the book "Neuronal Dynamics"
Official repository for the sample-and-measure project
Code for the article: Brea J (2017). Is prioritized sweeping the better episodic control? arXiv:1711.06677 [cs.AI]
Module for the NEST simulator (https://github.com/nest/nest-simulator) that adds a combined STDP and structural plasticity synapse model with multiple synaptic contacts.
Feedback-based Online Local Learning Of Weights (FOLLOW)
Public code (julia) for Illing, Gerstner & Brea 2019: Biologically plausible deep learning - but how far can we go with shallow networks?
Public code for Illing, Ventura, Bellec & Gerstner 2021: Local plasticity rules can learn deep representations using self-supervised contrastive predictions
Code for the publication V. Liakoni *, M. Lehmann *, A. Modirshanechi, J. Brea, A. Lutti, W. Gerstner ** , K. Preuschoff **, NeuroImage, 2022
Code for the publication V. Liakoni*, A. Modirshanechi*, W. Gerstner, J. Brea, Neural Computation, 2021
Mesoscopic dynamics of interacting populations of GIF/GLM spiking neurons
Spiking neuronal network simulations (Python, NEST Simulator) for continuous attractor working memory networks with short-term plasticity.
Langevin integrator for SDEs with constant drift and diffusion on continuous intervals with circular boundary conditions.
Code for paper "Nonlinear Hebbian Learning", Plos 2016, Brito & Gerstner
Code for paper "Learning what matters: synaptic plasticity with invariance to input correlations" by Carlos Stein Brito, Wulfram Gerstner
Code and data for the publication Xu*, Modirshanechi*, Lehmann, Gerstner, and Herzog, PLOS Computational Biology (2021)
Auryn: A fast simulator for spiking neural networks with synaptic plasticity
Simulation code from Zenke, F., Agnes, E.J., and Gerstner, W. (2015).
Simulation code from Ziegler, Zenke, Kastner and Gerstner (2015) http://www.jneurosci.org/content/35/3/1319.full
My simulation behind the spiking Hopfield network in the Neuronal Dynamics book (Fig. 17.11)
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