If anyone else here is working on Deep Learning on/with vector graphics, feel free to ping me.
I am not affiliated with the great work linked here - but I have been working on the general topic as a side project for a few years.
One way is volumetric rendering or distance fields. I've been keeping my eye on NeRF but it seems a long way from being useful for anything realtime.
Vectors and mesh representations seem somewhat neglected and this project has given me some insight into the technical problems.
I've finally got CUDA running on WSL so I intend to start having a play with things. I've also got beta access to GPT-3 and I've been curious if it can do anything interesting in terms of generating structured data. Can it manipulate symbolic scene descriptions or generate meaningful vector paths? A few experiments with SVG haven't been terribly promising.
I'd love to hear your thoughts on the general topic and any suggestions for things to look into.