Deepsets, Graph Neural Networks, and Transformers in High Energy Physics - Lecture 6

Explore advanced machine learning techniques in this lecture focusing on Deepsets, Graph Neural Networks, and Transformers with applications in High Energy Physics. Delve into the intricacies of these powerful algorithms and their potential to revolutionize data analysis in particle physics research. Gain insights from expert Sanmay Ganguly as he discusses the implementation and practical applications of these cutting-edge methods in the context of analyzing complex particle collision data from experiments like the Large Hadron Collider. Learn how these advanced neural network architectures can be leveraged to improve classification, identification, and characterization of particle interactions, potentially uncovering new physics phenomena. Enhance your understanding of state-of-the-art machine learning approaches and their role in pushing the boundaries of high energy physics research.