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Deepsets, Graph Neural Networks, and Transformers in Machine Learning - Lecture 1

International Centre for Theoretical Sciences via YouTube

Overview

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Explore the foundations of advanced machine learning architectures in this lecture on Deepsets, Graph Neural Networks, and Transformers. Delve into the theoretical underpinnings and practical applications of these powerful models, with a focus on their relevance to High Energy Physics research. Learn how these cutting-edge techniques can be leveraged to analyze complex data structures and extract meaningful insights from large-scale experiments. Gain valuable knowledge to enhance your understanding of modern machine learning approaches and their potential impact on the field of particle physics.

Syllabus

Lectures on Deepsets, Graph Neural Network and Transformers... (Lecture 1) by Sanmay Ganguly

Taught by

International Centre for Theoretical Sciences

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