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.
Cita Chicago Style (17a ed.)Krishnapriyan, Aditi S., Joseph Montoya, Maciej Haranczyk, Jens Hummelshøj, y Dmitriy Morozov. Machine Learning with Persistent Homology and Chemical Word Embeddings Improves Prediction Accuracy and Interpretability in Metal-organic Frameworks. Nature Portfolio, 2021.
Cita MLA (8a ed.)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.