CUDA implementation of Self-Organizing Map in C++

Moka is an application tool developed for the GraphESN-SOM machine learning model.

Growing Hierarchical Self-Organizing Map (GHSOM) implementation in C++

C++での自己組織化マップ

Self-organizing maps implementation.

Parallelization of the self-organizing map (Kohhonen )

Self Organizing Map (SOM) is a type of Artificial Neural Network (ANN) that is trained using an unsupervised, competitive learning to produce a low dimensional, discretized representation (feature map) of higher dimensional data.

Neural network with learning without a teacher, performing the task of visualization and clustering.

Efficient Self-Organizing Map for Sparse Data

EdgeSOM: Distributed Hierarchical Edge-driven IoT Data Analytics Framework

A composable container for Adaptive ROS 2 Node computations. Select between FPGA, CPU or GPU at run-time.

C++ implementation of SOM(self-organizing map)

TRIQS-based Stochastic Optimization Method for Analytic Continuation