Neural Networks (NNs) in Confinement Fusion

I just found the following paper written in the "Proceedings of the National Academy of Sciences of the USA" (PNAS), which describes the application of machine learning surrogate models for prediction in confinement fusion:

Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, and Brian K. Spears, "Improved surrogates in inertial confinement fusion with manifold and cycle consistencies"

Proceedings of the National Academy of Sciences of the USA (PNAS), 117 (18), 9741-9746, 2020.

1) Link to the paper www, HERE
2) Link to the .pdf file, HERE

It seems some specific types of neural networks may work well in prediction tasks, in these so hard to simulate plasma physics scenarios.

News at the National Ignition Facility (NIF) website, HERE.

[Almost] - Everything / Anything unified in ML?

I would like to think that the idea proposed by Prof. Eric P. Xing about the possibility to set out a standard model in Machine Learning has good chances to be accepted, or at least carefully analyzed.

Have a look at the video below: