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Explore machine learning techniques applied to Calabi-Yau metrics in this 34-minute lecture by Magdalena Larfors. Delve into the intersection of advanced mathematics and artificial intelligence as Larfors discusses the application of machine learning algorithms to understand and compute complex geometric structures in Calabi-Yau manifolds. Gain insights into the Landscapia project, which aims to leverage computational methods to tackle challenging problems in string theory and algebraic geometry. Discover how these cutting-edge approaches are revolutionizing our understanding of the mathematical foundations of theoretical physics and potentially opening new avenues for exploring the structure of the universe.
Syllabus
Magdalena Larfors - Machine learning Calabi-Yau metrics (Landscapia)
Taught by
IPhT-TV