Neurocomputation with Geometric Algebra

Steven Shepard @ Redwood Center for Theoretical Neuroscience

This is a page to consolidate information on using Geometric Algebra for computation, specifically for neural networks.

It will distill literature and host some programming examples

Installations

For implementation of GA the main packages needed will be : numpy clifford

simply install clifford and/or numpy with

pip install clifford

pip install numpy

or follow link for alternative download options :[https://clifford.readthedocs.io/en/latest/clifford]

Quick Start example

The first step in computing with GA is to define the GA space. Read this pages on GA Vectors Spaces to understand what is meant here. It may take experimentation to determine which space is ideal for your application. The spaces included in the pacakage are the following: g2 g3 g4 g5

import numpy as np
import clifford as cf

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### Support or Contact
steven[underscore]shepard[at]berkeley[dot]edu