Nicholas T. Liesen

An open benchmark for machine learning-based polymer property prediction

Graph-based models provide the lowest errors in property prediction, retain their advantage across the evaluated training-set sizes, and remain robust to increasing repeat-unit complexity, according to the PolyBench26 benchmark.