This project aims not only to learn representations, but also to develop generative models that use learning‑to‑structure to improve efficiency, generalisation, and the ability to express and estimate uncertainty.

This two-stage training process, whilst pragmatic, raises some deep questions: why can't we train a one-step generator directly, without needing to first train a diffusion model?