Introduction There is an increasing trend to apply machine learning for molecule-property prediction to avoid the expense of experiments or reduce the tremendous computational costs required for accurate quantum-chemical calculations.
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Federated learning of molecular properties with graph neural networks in a heterogeneous setting.
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