Comprehensive Study on Molecular Supervised Learning with Graph Neural Networks
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DOI: 10.1021/acs.jcim.0c00416
Abstract: This work considers strategies to develop accurate and reliable graph neural networks (GNNs) for molecular property predictions. Prediction performance of GNNs is highly sensitive to the change in various parameters due to the inherent challenges… read more here.
Keywords: neural networks; study; graph neural; supervised learning ... See more keywords