ParameterEstimation.jl: Algebraic Parameter Estimation in ODEs
Parameter estimation for ODEs is a fundamental problem in modeling and dynamics. The algebraic approach in Bassik et al. does not suffer from difficulties inherent in nonlinear optimization (the need for good initial guess, getting stuck in local minima, etc), but degrades severely in the presence of measurement noise. We combined the algebraic approach with Gaussian Process Regression to increase robustness to noise. In this talk, we will demo a Julia implementation of this new algorithm.