After the series of six posts about Tree-Graph Entropy (starting here), I have prepared a short presentation about Graph Entropy, mainly to clarify the concepts to my own (and to anyone interested) and present some real-world use cases.
One of the most interesting ideas introduced in this presentation is a method for, once you had defined the entropy of all the nodes in a static disrected and acyclic and directed graph (a tree), to easily update all those entropy values as the graph evolves over time, both altering the conditional probability of some connections, as also by adding or taking connections, by considering nodes and connection as cellular automaton that can adjust its internal entropies asynchronously.
You can also jump to the original google slides version if you want to comment on a particular slide.
If this was not enought for you and what to read more weird things about those entropies, you can dive into the unknown realm of negative probabilities entropy here!
Update (24 Oct 2018): this post was referenced in the article "A Brief Review of Generalized Entropies"where the (c, d) exponents of these generalized entropies are calculated.
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