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pdf:docinfo:title: Interpretable Machine Learning for Materials Design
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subject: Comparison of various machine learning models with respect to accuracy and interpretability in materials design.
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cp:subject: Comparison of various machine learning models with respect to accuracy and interpretability in materials design.
pdf:docinfo:subject: Comparison of various machine learning models with respect to accuracy and interpretability in materials design.
pdf:docinfo:creator: James Dean, Matthias Scheffler, Tom Purcell, Sergey V Barabash, Rahul Bhowmik, Timur Bazhirov
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Author: James Dean, Matthias Scheffler, Tom Purcell, Sergey V Barabash, Rahul Bhowmik, Timur Bazhirov
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Keywords: machine learning, materials science, chemistry, interpretability, inverse design
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dc:creator: James Dean, Matthias Scheffler, Tom Purcell, Sergey V Barabash, Rahul Bhowmik, Timur Bazhirov
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title: Interpretable Machine Learning for Materials Design
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