Explore advanced concepts in tensor networks and their applications to machine learning in this comprehensive lecture by Edwin Miles Stoudenmire from the Flatiron Institute. Delve into the second part of the series, building upon foundational knowledge to examine more complex tensor network structures and their potential for enhancing machine learning algorithms. Gain insights into cutting-edge research that bridges the gap between condensed matter physics and artificial intelligence, uncovering novel approaches to tackle challenging computational problems in both fields.
Tensor Network for Machine Learning Applications - Part 2
ICTP Condensed Matter and Statistical Physics via YouTube
Overview
Syllabus
Tensor network for machine learning applications 2
Taught by
ICTP Condensed Matter and Statistical Physics
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Tensor Network for Machine Learning Applications - Lecture 3
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Tensor Network for Machine Learning Applications - Lecture 1
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