  The goal of machine learning is to facilitate a computer to execute a
specific task without explicit instruction by an external party. Quantum
foundations seeks 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, we compile the representative
works done so far at the interface of machine learning and quantum foundations.
We conclude the survey with potential future directions.
