
http://homepages.inf.ed.ac.uk/rbf/CVonl ... 9/ORCHARD/

My interest lies in exploiting message-passing to make fast inference algorithm. A more recent analogue seems to be dynamic bayesian network (DBN), it is remarkably similar to CA and an oscillator in CA corresponds to something like a stable cycle in the DBN. The difference between DBN and MRF is that DBN is embedded in time whereas MRF isn't (though I supposes possible). Anyway it'd be interesting to see how much of the result of CA is transferable to DBN, please comments if you guys have any thought/reference.BlinkerSpawn wrote:The temperature model (and possibly the belief propagation system too, although I don't know how that works) could probably be approximated on the VN neighborhood using states 1,2,...,n to represent temperatures of 1/n,2/n,etc., for some n.
Granted, you'd need a script to generate the necessary transitions and there'd be a lot of them, although you'd have access to the permute symmetry which would save some space.
I'm curious of how it works on the Turbulent phase cyclic cellular automata, where large-scale structure dominates.shouldsee wrote:So excited that I dropped my jaw due to this paper by Cosma Shalizi [1].
accompanying blog
Reference
1. Shalizi, C. R., Haslinger, R., Rouquier, J., Klinkner, K. L. & Moore, C. Automatic filters for the detection of coherent structure in spatiotemporal systems. 1–16 (2006). doi:10.1103/PhysRevE.73.036104