translational-toys

This repository contains workflows for training knowledge graph embedding models on knowledge graphs representing interesting geometries (generated by geometric_graphs) using PyKEEN and animate the evolution of their entity embeddings. Rerun the examples with

$ pip install tox
$ tox

Line

A linear dataset embedded with TransE/SoftPlus Loss by running python cli.py line:

Square Grid in 2D

A square grid dataset embedded with TransE/NSSA Loss by running python cli.py squares:

Additional idea: try training in much higher dimensions, then use ISOMAP to reduce back down to 2D and see how true it is.

Hexagonal Grid in 2D

A hexagonal grid dataset embedded with TransE/SoftPlus Loss by running python cli.py hexagons:

Note the hexagonal grid shape is not learned if there are no constraints on the relations because it's easier to learn different sizes, and just create a square grid. To get this behavior, I ran a modified TransE in which I set the relation constrainer to normalize.

Circle in 2D

TODO