These are some paper implementations and other code snippets to help me learn more about Neural Tangent Kernels. Most of this is from existing implementations and I am maintaining this just for learning purposes.
The notebooks currently in the repository are for -
- Eignedecomposition of the empirical NTK
- Training Neural Networks (non-linear) and Linear models (after linearization) on binary eigenfunctions of the NTK at initialization
- The training and loss landscape of the linear models at initialization vs neural networks vs linear model with kernel extracted after non-linear pretraining