Machine learning and the physical sciences

@article{Carleo2019MachineLA,
  title={Machine learning and the physical sciences},
  author={Giuseppe Carleo and Ignacio I. Cirac and Kyle Cranmer and Laurent Daudet and Maria Schuld and Naftali Tishby and Leslie Vogt-Maranto and Lenka Zdeborov'a},
  journal={Reviews of Modern Physics},
  year={2019},
  volume={91},
  pages={045002}
}
Machine learning (ML) encompasses a broad range of algorithms and modeling tools used for a vast array of data processing tasks, which has entered most scientific disciplines in recent years. This article reviews in a selective way the recent research on the interface between machine learning and the physical sciences. This includes conceptual developments in ML motivated by physical insights, applications of machine learning techniques to several domains in physics, and cross fertilization… 

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