SPIDeC methods achieve arbitrarily high-order accuracy for positive dynamical systems while unconditionally preserving positivity and equilibria via a multiplicative Volterra structure, and they are L-stable with asymptotic logarithmic contractivity under Gauss-Radau nodes.
A Boot-Strapping Technique to Design Unconditionally Positive Dense Output Formulae for Modified Patankar-Runge-Kutta Methods
2 Pith papers cite this work. Polarity classification is still indexing.
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Uses MPRK solvers and WENO post-processing to optimize time-varying hyperparameters in existing COVID-19 models and reports 5-day forecasts within 10% error for a Ghana case study.
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Stable Positive Integral Deferred Correction Methods for Positive Dynamical Systems
SPIDeC methods achieve arbitrarily high-order accuracy for positive dynamical systems while unconditionally preserving positivity and equilibria via a multiplicative Volterra structure, and they are L-stable with asymptotic logarithmic contractivity under Gauss-Radau nodes.
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Using Machine Learning to Enhance Hyperparameter Optimization in Pandemic Modeling: Case study of COVID-19 Dynamics in Ghana
Uses MPRK solvers and WENO post-processing to optimize time-varying hyperparameters in existing COVID-19 models and reports 5-day forecasts within 10% error for a Ghana case study.