2 citations · 3 across the 5 of their papers we have counts for
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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…
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…