Maxim Samarin

Feature learning and random features in standard finite-width convolutional neural networks: An empirical study

The Neural Tangent Kernel is an important milestone in the ongoing effort to build a theory for deep learning. Its prediction that sufficiently wide neural networks behave as kernel methods, or equivalently as random feature models arising from linearized networks, has been confirmed empirically for…