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Submitted by admin on Wed, 10/23/2024 - 01:52

Causal determinism, is deeply ingrained with our ability to understand the physical sciences and their explanatory ambitions. Besides understanding phenomena, identifying causal networks is important for effective policy design in nearly any avenue of interest, be it epidemiology, financial regulation, management of climate, etc. This special issue covers several areas where causal inference research intersects with information theory and machine learning.

Negar Kiyavash
Elias Bareinboim
Todd Coleman
Alex Dimakis
Bernhard Schlkopf
Peter Spirtes
Kun Zhang
Robert Nowak