Hopfield network implemented with Python
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Updated
Nov 27, 2020 - Python
Hopfield network implemented with Python
A lightweight and flexible framework for Hebbian learning in PyTorch.
Meta-Learning through Hebbian Plasticity in Random Networks: https://arxiv.org/abs/2007.02686
Python implementation of the Epigenetic Robotic Architecture (ERA). It includes standalone classes for Self-Organizing Maps (SOM) and Hebbian Networks.
NGC-Learn: Neurobiological Learning and Biomimetic Systems Simulation in Python
Code for the assignments for the Computational Neuroscience Course BT6270 in the Fall 2018 semester
NeuroMorphic Predictive Model with Spiking Neural Networks (SNN) using Pytorch
Implementation of Hopfield Neural Network in Python based on Hebbian Learning Algorithm
Studying collective memories of internet users using Wikipedia viewership statistics
PCAnet and different PCA methods, implemented with numpy. Including powerPCA, HebbianPCA, kernelPCA and PCAnet
Code for Limbacher, T. and Legenstein, R. (2020). H-Mem: Harnessing synaptic plasticity with Hebbian Memory Networks
Computational Neuroscience projects.
PyPi Package of Self-Organizing Recurrent Neural Networks (SORN) and Neuro-robotics using OpenAI Gym
A Hedonistic Hebbian Neural Network in python.
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.
In this project, I used Hebbian, Perceptron, Adaline, MultiClassPerceptron and MultiClassAdaline neural networks to implement X and O character recognition.
This is a python implementation of Kuramoto model with adaptive rewiring. Adaptive rewiring is meant to simulate the ebb and flow of social interactions.
unsupervised learning of natural images -- à la SparseNet.
This repository contains basic neural network design concepts like hebbian learning, perceptron rule, filtered learning
Implemented Hierarchical temporal Memory in C on a multicore processor
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