We present a Bayesian framework for discovering this system of differential equations under assumptions that align with real-life scenarios, including the availability of relatively sparse data.
We propose a multivariate replicated batch means (RBM) estimator that utilizes information across multiple chains in order to estimate the asymptotic covariance matrix.
