Neural Tangent Kernel: A theoretical view of Deep Learning Theory
A theoretical overview of the Neural Tangent Kernel and what it reveals about training dynamics and the behavior of wide neural networks.
In 2018 (a bit too old for now), a paper by Arthur Jacot, Franck Gabriel, and Clément Hongler dropped a theoretical study on the deep learning community. Their work on Neural Tangent Kernels (NTKs) showed that neural networks, under certain conditions, behave exactly like classical kernel method, a connection that was both surprising and profound.
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