1 Definition and the explicit solution for square loss

2 Kernel convergence

3 Finite-width corrections

4 Computing the limit kernel  
4.1 Fully-connected nets  
4.2 Convolutional nets  
4.3 Computing the expectations  
4.4 NTK for attention layers  

5 Computational aspects  
5.1 Inference optimizations  
5.2 Computing the empirical kernel  

6 Applications  
6.1 A kernel method  
6.2 Pathology analysis  
6.3 A theoretical tool  

7 Standard parameterization and kernel evolution

8 Beyond NTK  
8.1 NNGP kernel  
8.2 Label-aware NTK  

9 Limits of applicability

10 Conclusions