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- Segler, M. H. S.; Waller, M. P., Neural-Symbolic Machine Learning for Retrosynthesis and Reaction Prediction. Chemistry – A European Journal 2017, 23 (25), 5966-5971.
- Segler, M. H. S.; Preuss, M.; Waller, M. P., Planning chemical syntheses with deep neural networks and symbolic AI. Nature 2018, 555 (7698), 604-610.
- Schwaller, P.; Gaudin, T.; Lányi, D.; Bekas, C.; Laino, T., “Found in Translation”: predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence models. Chemical Science 2018, 9 (28), 6091-6098.
- Lin, K.; Xu, Y.; Pei, J.; Lai, L., Automatic retrosynthetic route planning using template-free models. Chemical Science 2020, 11 (12), 3355-3364.