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Found 3 papers, 1 papers with code
Physics in the Machine: Integrating Physical Knowledge in Autonomous Phase-Mapping
Application of artificial intelligence (AI), and more specifically machine learning, to the physical sciences has expanded significantly over the past decades.
On-the-fly Closed-loop Autonomous Materials Discovery via Bayesian Active Learning
Active learning - the field of machine learning (ML) dedicated to optimal experiment design, has played a part in science as far back as the 18th century when Laplace used it to guide his discovery of celestial mechanics [1].
Autonomous data-driven design of inorganic materials with AFLOW
The expansion of programmatically-accessible materials data has cultivated opportunities for data-driven approaches.
Materials Science
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