5. VAMPnets deploy a "fuzzy clustering" of MD trajectories in "n" output states. Each conformation in the MD trajectory has a probability for each of these output states that sum to one. The cluster with the maximum likelihood for each conformation is the one that is assigned to the conformation. Post clustering, conformations within each cluster are further binned based on one of the CVs (dihedral angle, ϕ, in the case of alanine dipeptide and RMSD in the case of chignolin). From each subcluster, a certain number of conformations are selected from each bin to generate a well-sampled initial state sampling for WE simulations. Once the conformations are chosen from these clusters, they are assigned the weights based on their fraction of the population of the cluster to which they belong.