Awesome

Convolutional Neural Tangent Kernel (CNTK)

This repository contains the code for Convolutional Neural Tangent Kernel (CNTK) in the following paper

On Exact Computation with an Infinitely Wide Neural Net (NeurIPS 2019)

Citation

@inproceedings{arora2019exact,
  title={On exact computation with an infinitely wide neural net},
  author={Arora, Sanjeev and Du, Simon S. and Hu, Wei and Li, Zhiyuan and Salakhutdinov, Ruslan and Wang, Ruosong},
  booktitle={Thirty-third Conference on Neural Information Processing Systems},
  year={2019}
}

Usage

Require Python 2.7 and CUDA.

Install CuPy.
Download CIFAR-10.

wget https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz; tar zxvf cifar-10-python.tar.gz

Parallelize Line 143-146 in CNTK.py according to your specific computing enviroment to utilize multiple GPUs.

To reproduce results in Table 1 in our paper:

For column CNTK-V:

python CNTK.py --gap no --fix no --depth DEPTH

where DEPTH is 3, 4, 6, 11 or 21.

For column CNTK-GAP:

python CNTK.py --gap yes --fix yes --depth DEPTH

where DEPTH is 3, 4, 6, 11 or 21.