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Is there a scaling complexity of measurement for MAP to be optimal?
How does OLS look like in the graph?
To what extent can we extrapolate these analytical linear network dynamics to the local behavior of nonlinear networks? If so, can we develop an "atlas" of linear regimes to generalize the global behavior of nonlinear networks?
feels something like loss landscape having troughs inside troughs inside troughs
mines just more of a comment about multi scale structure..
Would there some benefit to more than two types of cells?
Isn’t this equivalent to standard Boltzmann machines? I mean the probabilistic difference to hopfield
Apologies if you already stated this, but how do you add or program-in a "memory" to the BEC?
Is it a 3-D Ising Model??
To clarify, I mean a specific memory, i.e., add a new minimum.