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Everything about Entropic vector
The entropic vector or entropic function is a concept arising in information theory. It represents the possible values of Shannon's information entropy that subsets of one set of random variables may take. Understanding which vectors are entropic is a way to represent all possible inequalities between entropies of various subsets. For example, for any two random variables, their joint entropy is at most the sum of the entropies of and of : Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Entropic vectorA 5-minute orientation
- Skim a recent paper: Vector-Valued Gaussian Free Field Conditioned to Avoid a Ball: Entropic Repulsion of the Norm and Freezing of SpinsInfluential work since 2022
- Read the landmark paper: UK Regional Nowcasting Using a Mixed Frequency Vector Auto-Regressive Model with Entropic TiltingCited 30 times
- Go sideways: Inequalities in information theoryA closely related topic
- Go sideways: Entropy power inequalityA closely related topic
📖 Definitions
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🗂️ The subject at a glance
🏆 Landmark papers (most cited)
UK Regional Nowcasting Using a Mixed Frequency Vector Auto-Regressive Model with Entropic Tilting
Entropic measurement uncertainty relations for all the infinite components of a spin vector
🆕 Influential since 2022
📚 Books worth reading
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🔗 Related topics
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