It's only an analogy, but it does suggest at least that the interesting details of the dynamics aren't embedded in the topology of the system. It's more complicated than that.
It's only an analogy, but it does suggest at least that the interesting details of the dynamics aren't embedded in the topology of the system. It's more complicated than that.
I wasn't familiar with the term "equivariance" but I "woke up" to this sort of approach to understanding deep neural networks when I read this paper, which shows how restricted boltzman machines have an exact mapping to the renormalization group approach used to study phase transitions in condensed matter and high energy physics:
https://arxiv.org/abs/1410.3831
At high enough energy, everything is symmetric. As energy begins to drain from the system, eventually every symmetry is broken. All fine structure emerges from the breaking of some symmetries.
I'd love to get more in the weeds on this work. I'm in my own local equilibrium of sorts doing much more mundane stuff.