4 citations · 7 across the 6 of their papers we have counts for
7 papers
Closed-Form Gaussian Estimators for Multi-Source Partial Information Decomposition
Aobo Lyu, Andrew Clark, Netanel Raviv
Computing multi-source partial information decomposition (PID) for continuous data is hard: existing closed-form Gaussian estimators are restricted to two source variables, while c…
Structural Impossibility of Antichain-Lattice Partial Information Decomposition
Aobo Lyu, Andrew Clark, Netanel Raviv
Partial Information Decomposition (PID) represents multivariate mutual information via antichain-lattice that aims to specify which source groups can recover which informational co…
The Whole Is Less than the Sum of Parts: Subsystem Inconsistency in Partial Information Decomposition
Aobo Lyu, Andrew Clark, Netanel Raviv
Partial Information Decomposition (PID) was proposed by Williams and Beer in 2010 as a tool for analyzing fine-grained interactions between multiple random variables, and has since…
Multivariate Partial Information Decomposition: Constructions, Inconsistencies, and Alternative Measures
Aobo Lyu, Andrew Clark, Netanel Raviv
While mutual information effectively quantifies dependence between two variables, it does not by itself reveal the complex, fine-grained interactions among variables, i.e., how mul…
Explicit Formula for Partial Information Decomposition
Aobo Lyu, Andrew Clark, Netanel Raviv
Mutual information between two random variables is a well-studied notion, whose understanding is fairly complete. Mutual information between one random variable and a pair of other…
Emergence and Causality in Complex Systems: A Survey on Causal Emergence and Related Quantitative Studies
Bing Yuan, Zhang Jiang, Aobo Lyu +6
Emergence and causality are two fundamental concepts for understanding complex systems. They are interconnected. On one hand, emergence refers to the phenomenon where macroscopic p…
System Information Decomposition
Aobo Lyu, Bing Yuan, Ou Deng +2
To characterize the complex higher-order interactions among variables within a system, this study introduces a novel framework, termed System Information Decomposition (SID), aimed…