Jakob A. Meckes

Enabling Data-Efficient Machine Learning through Multi-Target Training Set Design via Greedy Neighborhood Coverage

Machine learning is increasingly used to guide asymmetric catalysis, but each enantioselectivity measurement remains experimentally expensive. Prior work established that predictive accuracy in these datasets is dominated by reactions that are structurally similar to the target, motivating neighborhood-restricted mod...