Machine Learning in Theoretical and Experimental High Energy Physics

Explore the evolution and impact of machine learning in high energy physics through this comprehensive lecture. Discover how machine learning techniques have been utilized in experimental high energy physics since the 1990s, leading to groundbreaking discoveries such as the Higgs boson. Gain insights into the integral role of machine learning in data acquisition and analysis workflows for high energy physics experiments. Learn about the emerging applications of machine learning tools for theoretical physicists and their potential to revolutionize the field. Understand the significant contributions machine learning is expected to make in the ongoing search for new physics, shaping the future of high energy physics research.

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