• Corpus ID: 9665943

Neural Message Passing for Quantum Chemistry

@article{Gilmer2017NeuralMP,
  title={Neural Message Passing for Quantum Chemistry},
  author={Justin Gilmer and Samuel S. Schoenholz and Patrick F. Riley and Oriol Vinyals and George E. Dahl},
  journal={ArXiv},
  year={2017},
  volume={abs/1704.01212}
}
Supervised learning on molecules has incredible potential to be useful in chemistry, drug discovery, and materials science. [] Key Method In this paper, we reformulate existing models into a single common framework we call Message Passing Neural Networks (MPNNs) and explore additional novel variations within this framework. Using MPNNs we demonstrate state of the art results on an important molecular property prediction benchmark; these results are strong enough that we believe future work should focus on…

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