Fast parameter estimation with PhysicsInformedRegression.jl
Marcus Galea Jacobsen, Jonas Søeborg Nielsen, Albert Brincker Olson
In this talk, we present a fast method for estimating parameters from data, when modeling with differential equations.
PhysicsInformedRegression.jl works as an extension to the SciML ecosystem, specifically for symbolic models. It'll be shown how to apply the provided method on simulated data for certain examples (SIR, enzyme reactions, lotka-volterra and lorenz attractor).