7 citations · 17 across the 12 of their papers we have counts for
6 papers · 1 filter
Design of Experiment in Complex Systems based on Computational Taxonomy
Eric Goldman, Fushing Hsieh
Via Computational Taxonomy (CT), we develop Design of Experiment(DoE) based on rigorously redefined constituting ingredients of complex system dynamics: randomness, nonlinearity an…
Structure-Preserving Visualization of Complex Systems through Discrete Approximation: An Application to Argo Data
Shang-Ying Shiu, Fushing Hsieh, Ting-Li Chen
This paper presents a framework for constructing structure-preserving representations of complex systems through discrete approximation, and demonstrates its use in studying the ve…
Learned practical guidelines for evaluating Conditional Entropy and Mutual Information in discovering major factors of response-vs-covariate dynamics
Ting-Li Chen, Hsieh Fushing, Elizabeth P. Chou
We reformulate and reframe a series of increasingly complex parametric statistical topics into a framework of response-vs-covariate (Re-Co) dynamics that is described without any e…
Multiscale major factor selections for complex system data with structural dependency and heterogeneity
Hsieh Fushing, Elizabeth Chou, Ting-Li Chen
Based on structured data derived from large complex systems, we computationally further develop and refine a major factor selection protocol by accommodating structural dependency…
An Encoding Approach for Stable Change Point Detection
Xiaodong Wang, Fushing Hsieh
Without imposing prior distributional knowledge underlying multivariate time series of interest, we propose a nonparametric change-point detection approach to estimate the number o…
Discovering Multiple Phases of Dynamics by Dissecting Multivariate Time Series
Xiaodong Wang, Fushing Hsieh
We proposed a data-driven approach to dissect multivariate time series in order to discover multiple phases underlying dynamics of complex systems. This computing approach is devel…