Figure : Active learning scheme. Models are trained to reproduce free energies computed by MD. At each iteration a batch of ligands is selected to be added to the training set based on their predicted free energies according to the previous iteration's models. Iterative training of the models with an increasing training dataset improves prediction accuracy: most of the top binders are identified by probing only a small part of the whole chemical library.