Causal Discovery

Causal discovery is the process of inferring the causal structure of a closed system using observational data.

This post outlines how causal discovery is possible using time series data, and explores some novel techniques developed by Jakob Runge and colleagues in a series of papers in Nature Communications, and Science Advances. The team has also created a software package, Tigramite, that implements these methods.

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Collective Intelligence

Our new publication on the wisdom of crowds has come out in Proceedings of the National Academy of Sciences here. There’s a good summary on and the video below.