3 citations · 3 across the 7 of their papers we have counts for
9 papers
Scale Partitioning by Incremental Nested Entropy: A Measure-Oriented Theory of Multiscale Structure
Abd AlRahman R. AlMomani
Across complex systems science, networks, spatial structures, populations, spectra, and dynamical flows are often represented by object-level measures such as connectivity, frequen…
Structural Causal Discovery and Predictive Sufficiency in High-Dimensional Dynamical Systems
Abd AlRahman R. AlMomani, Curtis N. James, Christopher C. Hennon +1
High-dimensional environmental systems contain variables that may be predictive, causally informative, physically coupled, or redundant, and these roles need not coincide. We study…
Boltzmann-Shannon Index: A Geometric-Aware Measure of Clustering Balance
Emanuele Bossi, C. Tyler Diggans, Abd AlRahman R. AlMomani
The Boltzmann-Shannon Index (BSI) for clustered continuous data is introduced as a normalized measure that captures the relationship between geometry-based and frequency-based prob…
Generalizing Geometric Partition Entropy for the Estimation of Mutual Information in the Presence of Informative Outliers
C. Tyler Diggans, Abd AlRahman R. AlMomani
The recent introduction of geometric partition entropy brought a new viewpoint to non-parametric entropy quantification that incorporated the impacts of informative outliers, but i…
ERFit: Entropic Regression Fit Matlab Package, for Data-Driven System Identification of Underlying Dynamic Equations
Abd AlRahman AlMomani, Erik Bollt
Data-driven sparse system identification becomes the general framework for a wide range of problems in science and engineering. It is a problem of growing importance in applied mac…
Data-Driven Learning of Boolean Networks and Functions by Optimal Causation Entropy Principle (BoCSE)
Jie Sun, Abd AlRahman AlMomani, Erik Bollt
Boolean functions and networks are commonly used in the modeling and analysis of complex biological systems, and this paradigm is highly relevant in other important areas in data s…