Review for NeurIPS paper: Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel

Additional Feedback: Minor issues *Visualization method of Figure 1: I am not sure how the authors depict this paper. Is it based on PCA of trajectories? It is also unclear why linear lines give these trajectories. It is just a linear regression with the Taylorized model (2). More technically speaking, when we use data-dependent NTK in a linearized model, the positive definiteness of this NTK is non-trivial and the equivalence to the kernel regression becomes unclear.