This is a matter of ergonomics and how close this thing is to production readiness; there's no reason the neural-net approach couldn't evolve and open up the pa

This is a matter of ergonomics and how close this thing is to production readiness; there's no reason the neural-net approach couldn't evolve and open up the parameters you want to tweak. Neural nets are just functions after all. You can refactor functions to expose params. Without being an expert in this area, I imagine one such way would be to train a second neural net that learns to regress traditional workflow parameters to best approximate the NeRF output, then let a user post-edit those parameters to fine-tune.