Fast and effective molecular property prediction with transferability map
Transfer learning improves molecular property prediction in limited datasets, yet suffers from negative transfer due to insufficient relatedness. We develop a principal gradient-based measurement to evaluate transferability before applying transfer learning, significantly improving the performance.
