A Transferable Recommender Approach for Selecting the Best Density Functional Approximations in Chemical Discovery

no code implementations • 21 Jul 2022 • Chenru Duan, Aditya Nandy, Ralf Meyer, Naveen Arunachalam, Heather J. Kulik

With electron density fitting and transfer learning, we build a DFA recommender that selects the DFA with the lowest expected error with respect to gold standard but cost-prohibitive coupled cluster theory in a system-specific manner.

Transfer Learning

Representations and Strategies for Transferable Machine Learning Models in Chemical Discovery

no code implementations • 20 Jun 2021 • Daniel R. Harper, Aditya Nandy, Naveen Arunachalam, Chenru Duan, Jon Paul Janet, Heather J. Kulik

To address the common challenge of discovery in a new space where data is limited, we introduce a transfer learning approach in which we seed models trained on a large amount of data from one row of the periodic table with a small number of data points from the additional row.

BIG-bench Machine Learning Transfer Learning