Sampling parameters of ordinary differential equations with Langevin
dynamics that satisfy constraints
Sampling parameters of ordinary differential equations with Langevin
dynamics that satisfy constraints
Fitting models to data to obtain distributions of consistent parameter values is important for uncertainty quantification, model comparison, and prediction. Standard Markov Chain Monte Carlo (MCMC) approaches for fitting ordinary differential equations (ODEs) to time-series data involve proposing trial parameter sets, numerically integrating the ODEs forward in time, and accepting …