Tamagotchi-style digital pet with a neural network featuring neurogenesis & Hebbian learning
NGC-Learn: Neurobiological Systems Simulation and NeuroAI Design in Python
Meta-Learning through Hebbian Plasticity in Random Networks: https://arxiv.org/abs/2007.02686
Hopfield network implemented with Python
A lightweight and flexible framework for Hebbian learning in PyTorch.
Python implementation of the Epigenetic Robotic Architecture (ERA). It includes standalone classes for Self-Organizing Maps (SOM) and Hebbian Networks.
PyPi Package of Self-Organizing Recurrent Neural Networks (SORN) and Neuro-robotics using OpenAI Gym
NeuroMorphic Predictive Model with Spiking Neural Networks (SNN) using Pytorch
Studying collective memories of internet users using Wikipedia viewership statistics
This repository has implementations of various alternatives to backpropagation for training neural networks.
Code for paper NeurIPS AMHN 2023
Code for the assignments for the Computational Neuroscience Course BT6270 in the Fall 2018 semester
Implementation of Hopfield Neural Network in Python based on Hebbian Learning Algorithm
Code for Limbacher, T. and Legenstein, R. (2020). H-Mem: Harnessing synaptic plasticity with Hebbian Memory Networks
unsupervised learning of natural images -- à la SparseNet.
Computational Neuroscience projects.
Malleable spiking neural network framework and training platform.
A neural network model builder, leveraging a neuro-symbolic interface.
Code for Limbacher, T., Özdenizci, O., & Legenstein, R. (2022). Memory-enriched computation and learning in spiking neural networks through Hebbian plasticity. arXiv preprint arXiv:2205.11276.
Contrastive Hebbian learning on MNIST, reaching ~97% accuracy with a small 784-128-10 MLP.
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