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• Deeply learning molecular structure-property relationships using attention- and gate-augmented graph convolutional network
  2018 · 80 citations
• Molecular generative model based on conditional variational autoencoder for de novo molecular design
  2018 · 24 citations
• Uncertainty quantification of molecular property prediction with Bayesian neural networks
  2019 · 15 citations
• Predicting drug-target interaction using 3D structure-embedded graph representations from graph neural networks
  2019 · 5 citations
• Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation
  2021 · 3 citations
• Accurate, reliable and interpretable solubility prediction of druglike molecules with attention pooling and Bayesian learning
  2022 · 3 citations
• Uncertainty quantification of molecular property prediction using Bayesian neural network models
  2019 · 2 citations
• Molecular Generative Model Based On Adversarially Regularized Autoencoder
  2019