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A general-purpose machine learning framework for predicting properties of inorganic materials

Description:

A very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data. While prior examples have demonstrated successful models for some applications, many more applications exist where machine learning can make a strong impact. To enable faster development...

Keyword:

computational methods, materials for energy and catalysis, and glasses

Creator:

Alok Choudhary, Logan Ward, Christopher Wolverton, and Ankit Agrawal

Owner:

Chris Diaz

Publisher:

Springer Nature

Date Uploaded:

05/08/2017

Date Modified:

05/08/2017

Date Created:

2016-08-26

Resource Type:

Article

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A general-purpose machine learning framework for predicting properties of inorganic materials

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