Evaluating Scalable Uncertainty Estimation Methods for Deep Learning-Based Molecular Property Prediction

Evaluating Scalable Uncertainty Estimation Methods for Deep Learning-Based Molecular Property Prediction

© 2020 American Chemical Society. Advances in deep neural network (DNN)-based molecular property prediction have recently led to the development of models of remarkable accuracy and generalization ability, with graph convolutional neural networks (GCNNs) reporting state-of-the-art performance for th...

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Bibliographic Details
Main Authors: Scalia, Gabriele, Grambow, Colin A, Pernici, Barbara, Li, Yi-Pei, Green, William H
Other Authors: Massachusetts Institute of Technology. Department of Chemical Engineering
Format: Article
Language:English
Published: American Chemical Society (ACS) 2021
Online Access:https://hdl.handle.net/1721.1/134634

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https://hdl.handle.net/1721.1/134634

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