  Here, we demonstrate how machine learning enables the prediction of
comonomers reactivity ratios based on the molecular structure of monomers. We
combined multi-task learning, multi-inputs, and Graph Attention Network to
build a model capable of predicting reactivity ratios based on the monomers
chemical structures.
