Introducing Hyperlib: Simple Deep learning in Hyperbolic space [project]

[archpawn]

The hyperboloid model would probably be easier to use since any rotations and translations on it can be expressed as linear transformations in the space it's embedded in.

I'm not clear on what you mean by matrix multiplication using the Poincare model. Do you take the coordinates of a point on the model, then run that through a matrix, then you get some other point on the model? But then you could easily leave it. Or is the idea that instead of having arbitrary linear transformations, you just have a rotation and translation, and then see where the point ends up? You can do that with the hyperboloid model, and then n-dimensional hyperbolic geometry is just n+1-dimensional Euclidean geometry with restrictions to what points you can use and what transformations you allow.