The authors combine topological data analysis and multi-objective Bayesian inference to achieve practical parameter identifiability and identify simpler rules in an agent-based model of zebrafish patterns.
Connecting Agent-Based Models with High-Dimensional Parameter Spaces to Mul- tidimensional Data Using SMoRe ParS: A Surrogate Modeling Approach
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Multi-objective Bayesian inference in an agent-based model of zebrafish patterns via topological data analysis
The authors combine topological data analysis and multi-objective Bayesian inference to achieve practical parameter identifiability and identify simpler rules in an agent-based model of zebrafish patterns.