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Explore generative models in this comprehensive lecture by Elham E Khoda and Aishik Ghosh, part of the "Statistical Methods and Machine Learning in High Energy Physics" program at the International Centre for Theoretical Sciences. Delve into the application of deep machine learning techniques in high energy physics research, focusing on the development of generative models for analyzing large-scale experimental data. Learn how these advanced computational methods can be utilized to process petabytes of information from the Large Hadron Collider and other precision experiments, potentially uncovering hints of new physics beyond the Standard Model. Gain insights into classification, identification, characterization, and estimation strategies employed in cutting-edge particle physics searches, and understand the growing importance of artificial intelligence in driving future discoveries in the field.
