A method includes determining a plurality of neural network models each corresponding to one of a plurality of molecular representations, and, for each molecular representation in the plurality of molecular representations, determining, using the neural network model corresponding to the molecular representation, a molecular property prediction result and prediction confidence corresponding to unlabeled data in an unlabeled data set, obtaining at least a portion of the unlabeled data as reference unlabeled data, the reference unlabeled data having corresponding prediction confidence higher than a preset threshold, and determining, based on the reference unlabeled data and a molecular property prediction result corresponding to the reference unlabeled data, pseudo-labeled data of a neural network model corresponding to another molecular representation in the plurality of molecular representations. The method further includes performing training on the plurality of neural network models respectively based on corresponding pseudo-labeled data of the plurality of neural network models.