Nature Reviews Physics: Machine learning in theoretical and experimental high energy physics

Machine learning has been used in experimental high energy physics since the 1990s, later enabling the data analysis that made possible the discovery of the Higgs boson. Today machine learning is not only an integral part of the data acquisition and analysis workflows in high energy physics experiments, but it also provides new tools for theorists. Therefore, machine learning is expected to make a large contribution to the ongoing search for new physics.