Injecting Domain Knowledge from Empirical Interatomic Potentials to Neural Networks for Predicting Material Properties

The dataset is generated using an active learning strategy. Then, an ensemble of models are trained on the data and new configurations are selected to be further labelled by DFT based on the uncertainty obtained from the ensemble. This process is iterated multiple times. We show the selected EIPs used in our experiments and their accuracy in Table 2 for reference. Table 2: EIPs used in experiments and their accuracy.