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Found 4 papers, 2 papers with code
Greater than the parts: A review of the information decomposition approach to causal emergence
Emergence is a profound subject that straddles many scientific disciplines, including the formation of galaxies and how consciousness arises from the collective activity of neurons.
Towards an extended taxonomy of information dynamics via Integrated Information Decomposition
Complex systems, from the human brain to the global economy, are made of multiple elements that interact in such ways that the behaviour of the `whole' often seems to be more than what is readily explainable in terms of the `sum of the parts.'
Reconciling emergences: An information-theoretic approach to identify causal emergence in multivariate data
The broad concept of emergence is instrumental in various of the most challenging open scientific questions -- yet, few quantitative theories of what constitutes emergent phenomena have been proposed.
Beyond integrated information: A taxonomy of information dynamics phenomena
Most information dynamics and statistical causal analysis frameworks rely on the common intuition that causal interactions are intrinsically pairwise -- every 'cause' variable has an associated 'effect' variable, so that a 'causal arrow' can be drawn between them.
Neurons and Cognition Data Analysis, Statistics and Probability
