
Natural Graph Networks with Taco Cohen - #440
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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Symmetries in Machine Learning
This chapter explores the intersection of physics and machine learning, focusing on the role of symmetry in enhancing neural network architectures. It discusses the implications of equivariant neural networks and how principles from physics can address data limitations in recognition tasks. Additionally, the chapter examines natural graph networks, emphasizing their ability to process data flexibly while maintaining meaningful predictions.
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