Solving the Traveling Salesman Problem using Self-Organizing Maps

:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps

A Python Library for Self Organizing Map (SOM)

Massively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters

Python library for Self-Organizing Maps

Self organizing Kohonen map in Python with periodic boundary conditions

SuSi: Python package for unsupervised, supervised and semi-supervised self-organizing maps (SOM)

:globe_with_meridians: Deep Embedded Self-Organizing Map: Joint Representation Learning and Self-Organization

Pytorch implementation of a Self-Organizing Map

A simple, rectangular self-organizing map with methods similar to clustering methods in Scikit Learn.

A multi-gpu implementation of the self-organizing map in TensorFlow

Self-organizing maps in Go

Python implementation of the Epigenetic Robotic Architecture (ERA). It includes standalone classes for Self-Organizing Maps (SOM) and Hebbian Networks.

Using self-organizing maps for visualization and interpretation of cytometry data

Hierarchical self-organizing maps for unsupervised pattern recognition

Tensorflow implementation of the Kohonen Self Organizing Map

Recursive Self-Organizing Map/Neural Gas.

Self-Organizing Map [https://en.wikipedia.org/wiki/Self-organizing_map] is a popular method to perform cluster analysis. SOM shows two main limitations: fixed map size constraints how the data is being mapped and hierarchical relationships are not easily recognizable. Thus Growing Hierarchical SOM has been designed to overcome this issues

Using Self-Organizing Maps for Travelling Salesman Problem

Pytorch implementation of Self-Organizing Map(SOM). Use MNIST dataset as a demo.

Self-Organizing Maps library of the InTRA research center.

:globe_with_meridians: SOMperf: Self-organizing maps performance metrics and quality indices

Using self-organizing maps for visualization and interpretation of cytometry data

FlowSOM algorithm in Python, using self-organizing maps and minimum spanning tree for visualization and interpretation of cytometry data

openFrameworks addon implementing a self-organizing map

A python library that fits a self-organizing map, a principal curves-like mesh that effectively reduces data to two dimensions.

Rectifying Self Organizing Map

Self-organizing maps (SOM) and k-means clustering for analyzing geospatial data.

TorchSOM is a PyTorch-based library for training Self-Organizing Maps (SOMs), a model trained in an unsupervised manner, that can be used for clustering, dimensionality reduction and data visualization. It is designed to be scalable and user-friendly.

DTW-SOM: Self-organizing map for time-series data