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From Prediction to Action: Critical Role of Performance Estimation for Machine-Learning-Driven Materials Discovery
Materials discovery driven by statistical property models is an iterative decision process, during which an initial data collection is extended with new data proposed by a model-informed acquisition function--with the goal to maximize a certain "reward" over time, such as the maximum property value discovered so far.
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