The goal of machine learning is to facilitate a computer to execute a specific task without explicit instruction by an external party. Quantum foundations seek to explain the conceptual and mathematical edifice of quantum theory. Recently, ideas from machine learning have successfully been applied to different problems in quantum foundations. Here, the authors compile the representative works done so far at the interface of machine learning and quantum foundations. The authors conclude the survey with potential future directions.
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