Autonomous Molecular Design: Then and Now

Deep learning

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Variational Graph Auto-EncodersPreprint

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Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules

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Active Learning with Statistical Models

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Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules.

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Junction Tree Variational Autoencoder for Molecular Graph GenerationPreprint

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The rise of deep learning in drug discovery

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Prediction of Organic Reaction Outcomes Using Machine Learning

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Deep Learning in Drug Discovery

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Flow Chemistry – A Key Enabling Technology for (Multistep) Organic Synthesis

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Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation ModelsPreprint

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Comparison of Support Vector Machine and Artificial Neural Network Systems for Drug/Nondrug Classification

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Why Does Deep and Cheap Learning Work So Well?Preprint

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Neural Networks in Chemistry

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PotentialNet for Molecular Property Prediction

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MolGAN: An implicit generative model for small molecular graphs

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Neural Networks for the Prediction of Organic Chemistry Reactions

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Continuous Flow Synthesis. A Pharma Perspective

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Phoenics: A Bayesian Optimizer for Chemistry

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