Understanding Policy Diffusion in the U.S.: An Information-Theoretical Approach to Unveil Connectivity Structures in Slowly Evolving Complex Systems
From MaRDI portal
Publication:3188149
DOI10.1137/15M1041584zbMath1377.37120WikidataQ42641127 ScholiaQ42641127MaRDI QIDQ3188149
Maurizio Porfiri, Geronimo Jimenez, James MacInko, Ross P. Anderson, Diana Silver, Jin Yung Bae
Publication date: 17 August 2016
Published in: SIAM Journal on Applied Dynamical Systems (Search for Journal in Brave)
Measures of information, entropy (94A17) Dynamical systems in optimization and economics (37N40) Connectivity (05C40)
Related Items (3)
Inference of time-varying networks through transfer entropy, the case of a Boolean network model ⋮ An information-theoretic approach to study fluid–structure interactions ⋮ Topological features determining the error in the inference of networks using transfer entropy
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Detecting Causality in Complex Ecosystems
- A survey of graph edit distance
- Reliability of inference of directed climate networks using conditional mutual information
- On the connectivity of random m-orientable graphs and digraphs
- Complex networks: structure and dynamics
- Causation entropy identifies indirect influences, dominance of neighbors and anticipatory couplings
- Revealing networks from dynamics: an introduction
- Information flow between subspaces of complex dynamical systems
- Deriving Information about Architecture from Activity Patterns in Coupled Cell Systems
- Estimation of Entropy and Mutual Information
- Inferring network topology from complex dynamics
- On the Efficacy of State Space Reconstruction Methods in Determining Causality
- Causal Network Inference by Optimal Causation Entropy
- Excitable Nodes on Random Graphs: Relating Dynamics to Network Structure
- Elements of Information Theory
This page was built for publication: Understanding Policy Diffusion in the U.S.: An Information-Theoretical Approach to Unveil Connectivity Structures in Slowly Evolving Complex Systems