Evaluating Uncertainty-Based Active Learning for Accelerating the Generalization of Molecular Property Prediction
February 15, 2024
February 15, 2024
WASHINGTON, Feb. 15 (TNSres) -- The U.S. Department of Energy's Pacific Northwest National Laboratory issued the following abstract of a journal article:
Deep learning models have proven to be a powerful tool for the prediction of molecular properties for applications including drug design and the development of energy storage materials. However, in order to learn accurate and robust structure-property mappings, these models require large amounts of data which can be a challeng . . .
Deep learning models have proven to be a powerful tool for the prediction of molecular properties for applications including drug design and the development of energy storage materials. However, in order to learn accurate and robust structure-property mappings, these models require large amounts of data which can be a challeng . . .