ML4Higgs - Success and Future Prospects by Nick Smith

Explore the successes and future prospects of machine learning applications in Higgs boson physics in this comprehensive conference talk. Delve into the cutting-edge techniques and methodologies used to analyze data from the Large Hadron Collider (LHC) in the search for the Higgs boson. Gain insights into how machine learning algorithms have revolutionized particle physics research, improving classification, identification, and estimation strategies. Discover the potential impact of deep learning and artificial intelligence on future high-energy physics experiments, including the High Luminosity LHC. Learn about the challenges and opportunities in processing and interpreting the massive datasets generated by modern particle accelerators. Understand the importance of machine learning in pushing the boundaries of our understanding of fundamental physics and the potential for discovering new phenomena beyond the Standard Model.