Regression Prediction of Coupling Reaction Yield Based on Attention-Driven Convolutional Neural Network

Abstract

The traditional method to improve the yield of Buchwald-Hartwig cross coupling reaction is to change the reactants or reaction conditions, but the reaction has many problems, such as harsh reaction conditions, complex synthetic route. In 2018, Doyle reported a yield prediction method based on random forest in Science. However, the predicted value of the regression tree in the random forest is the average value of the target variable of the leaf node, which treats the feature as equally important. We focused on the important characteristic information in order to obtain a more accurate yield prediction value. Therefore, it is of interest to apply some advanced deep learning methods to the performance prediction of chemical reactions, during which less training data may be required.