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Benchmarking Active Learning Strategies for Materials Optimization and Discovery
[article]
2022
arXiv
pre-print
Autonomous physical science is revolutionizing materials science. In these systems, machine learning controls experiment design, execution, and analysis in a closed loop. Active learning, the machine learning field of optimal experiment design, selects each subsequent experiment to maximize knowledge toward the user goal. Autonomous system performance can be further improved with implementation of scientific machine learning, also known as inductive bias-engineered artificial intelligence,
arXiv:2204.05838v1
fatcat:fmfm4s3bnbf5patd6u6kp35p2a