In this article a surprising result is demonstrated using the neural tangent kernel. This kernel is defined as the inner product of the vector of the gradient of an underlying model evaluated at training points. This kernel is used to perform kernel regression. The surprising thing is that the accuracy of that regression is independent of the accuracy of the underlying network.

翻译：在本条中,使用神经相切内核可以展示出一个令人惊讶的结果。该内核被定义为在训练点评价的一个基本模型的梯度矢量的内产物。该内核用于进行内核回归。奇怪的是,这种回归的准确性与基础网络的准确性无关。