https://arxiv.org/pdf/2304.14767.pdf
I am pretty much over my head in this literature, but continue to be fascinated as I watch people who are not try to untangle some explanatory power in their models...
The details of this analysis or framing this as /information flow/ rather than /static data/structure/ is reminiscent of some very nascent work we *tried* to do 15 years ago, attempting to analyze/understand huge Systems Dynamics models of Critical Infrastructure joined together/coupled to try to predict the potential for cascading failures through these coupled systems. The representation *as* SD models were natural for this framing but we made only the tiniest progress IMO in extracting hints of *explanatory* narratives. I was primarily doing visualization on those tasks but tried to focus on clustering of the Dual Graph/Network to find structure in the *flow* during extreme events rather than in the engineered/designed structure of the network itself.
I know there are others on this list who have worked with complex, dynamic networks (I'm thinking of Frank's colleagues and Causal Discovery in Graphical Models, various project Glen has alluded to, and a wide variety of problems Stephen has related to me over the years, but I'm sure there are plenty of others)... I'm curious if anyone else is wading in this deep (and more to the point, finding any traction)?
From the paper:
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