We use an active learning approach for model refinement. For example, MD configurations obtained from the i th DP model (i.e., DP i /MD, 400 K, 2 ns, 0.5 fs timestep, using LAMMPS) are down-selected based on their estimated model uncertainties. Similar to previous work by us and others, we use the ϵ t metric to quantify model uncertainty. Here, ϵ t for a given configuration R R R t is defined by equation 1.