DScribe: Library of descriptors for machine learning in materials science-Reference-Cited by-同舟云学术

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DScribe: Library of descriptors for machine learning in materials science

Published:2020-02 Issue: Volume:247 Page:106949
ISSN:0010-4655
Container-title:Computer Physics Communications
language:en
Short-container-title:Computer Physics Communications

Author:

Himanen Lauri,Jäger Marc O.J.,Morooka Eiaki V.,Federici Canova Filippo,Ranawat Yashasvi S.^ORCID,Gao David Z.,Rinke Patrick,Foster Adam S.^ORCID

Funder

Aalto Science-IT project

Jenny and Antti Wihuri Foundation

European Union’s Horizon 2020 research and innovation programme

Publisher

Elsevier BV

Subject

General Physics and Astronomy,Hardware and Architecture

Reference71 articles.

1. Materials informatics: a journey towards material design and synthesis

2. New tool in the box

3. Machine learning in materials design and discovery: Examples from the present and suggestions for the future

4. Machine learning for molecular and materials science

5. Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations

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