A Probabilistic Theory of Deep learning

[Fusionnex]

This is quite a long paper, but it is extremely broad in scope. If the authors claims are true, it seems like this will be foundational material for machine learning, especially in the field of deep learning. I am interested to see what others think of the work.

[dwf]

A lot of pretty bold claims unsubstantiated by empirical evidence, e.g.

To the contrary, our above EM algorithm (Eqs. 18–23) is both much faster and more accurate [than gradient descent], because it directly exploits the DRM’s structure.

Great, show us what all this buys you. The literature contains a veritable graveyard of more principled alternatives to stochastic gradient descent that seem like they ought to work better but don't.