Krishnapriyan, A. S., Montoya, J., Haranczyk, M., Hummelshøj, J., & Morozov, D. (2021). Machine learning with persistent homology and chemical word embeddings improves prediction accuracy and interpretability in metal-organic frameworks. Nature Portfolio.
Style de citation Chicago (17e éd.)Krishnapriyan, Aditi S., Joseph Montoya, Maciej Haranczyk, Jens Hummelshøj, et Dmitriy Morozov. Machine Learning with Persistent Homology and Chemical Word Embeddings Improves Prediction Accuracy and Interpretability in Metal-organic Frameworks. Nature Portfolio, 2021.
Style de citation MLA (8e éd.)Krishnapriyan, Aditi S., et al. Machine Learning with Persistent Homology and Chemical Word Embeddings Improves Prediction Accuracy and Interpretability in Metal-organic Frameworks. Nature Portfolio, 2021.