Nov 29, 2023 · In this paper, we scale up machine learning for materials exploration through large-scale active learning, yielding the first models that ...
This collection brings together the latest computational and experimental advances in machine learning and big data-driven approaches for high-throughput ...
This book covers novel methods in machine learning and data-driven modeling applied to the field of glass science.
Oct 5, 2022 · Applying the machine learning algorithm to more complex systems could lead to broad impact on the discovery and design of useful materials.
Machine learning is applied in materials design and discovery mainly to solve problems of regression, classification, clustering and probability estimation. In ...
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Jun 14, 2023 · Abstract:We introduce M^2Hub, a toolkit for advancing machine learning in materials discovery. Machine learning has achieved remarkable ...
Feb 18, 2021 · This Machine Learning Special Topic collection presents a representative sample of the latest ML related research being pursued within the broader physics and ...
Based on material databases, machine learning constructs models for specific material properties and quickly achieves the prediction of material properties, ...
In this paper, we review this research paradigm of applying machine learning in material discovery, including data preprocessing, feature engineering, machine ...
The main aim in this Perspective paper is to introduce knowledge discovery as a potential tool for fields of chemistry and materials sciences.
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