Transfer learning enables the molecular transformer to predict regio- and stereoselective reactions on carbohydrates

Abstract

Organic reactions can readily be learned by deep learning models, however, stereochemistry is still a challenge. Here, the authors fine tune a general model using a small dataset, then predict and validate experimentally regio- and stereo-selectivity for various carbohydrates transformations.