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machine learning
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2023 Roadmap on molecular modelling of electrochemical energy materials
Automatic extraction of materials and properties from superconductors scientific liter...
Machine learning approach for the prediction of electron inelastic mean free paths
Essential structural and experimental descriptors for bulk and grain boundary conducti...
Rapid discovery of new Eu2+-activated phosphors with a designed luminescence color usi...
Supercon 2 Dataset
Automatic Extraction of Materials and Properties from Superconductors Scientific Liter...
Automatic Identification and Normalisation of Physical Measurements in Scientific Lite...
SuperMat: Construction of a linked annotated dataset from superconductors-related publ...
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Keyword
machine learning
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superconductors
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Creative Commons BY Attribution 4.0 International
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informatics and data science
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Author
FOPPIANO, Luca
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Kensei Terashima
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Luca Foppiano
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Masashi Ishii
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Pedro Ortiz Suarez
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JSPS
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JST
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Japan Science and Technology Agency
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Journal
DocEng '19: Proceedings of the ACM Symposium on Document Engineering 2019
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Journal of Physics-Energy
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SCIENCE AND TECHNOLOGY OF ADVANCED MATERIALS: METHODS
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