Compressing physical properties of atomic species for improving predictive chemistry

@inproceedings{Herr2018CompressingPP,
  title={Compressing physical properties of atomic species for improving predictive chemistry},
  author={John E. Herr and Kevin J Koh and Kun Yao and John A. Parkhill},
  year={2018}
}
The answers to many unsolved problems lie in the intractable chemical space of molecules and materials. Machine learning techniques are rapidly growing in popularity as a way to compress and explore chemical space efficiently. One of the most important aspects of machine learning techniques is representation through the feature vector, which should contain the most important descriptors necessary to make accurate predictions, not least of which is the atomic species in the molecule or material… 

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