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What is Understanding Neural Tangent Kernel Dynamics about?

This document discusses the Neural Tangent Kernel (NTK) and its implications for training dynamics in neural networks, particularly in the infinite width limit where networks behave linearly. It explores how the training of wide neural networks leads to minimal changes in individual weights and presents a mathematical framework for understanding these dynamics. The findings suggest that neural networks can be approximated as linear models, allowing for closed-form solutions for training evolution and predic

Author

Swair Shah

Language

EN