Review for NeurIPS paper: Stationary Activations for Uncertainty Calibration in Deep Learning

The overall motivation is not clear. It is true that Matern kernels are good at capturing sharp transitions, as shown in Fig 1. There are many other methods to achieve similar, if not better, results. For instance, we can learn kernels [1,2], use deep kernels [2], use spectral mixture kernels [3], use "neural-network kernels" [4], etc. Comparisons with [1]-[5] would provide further insights. Please also report MSE and AUC in addition to the accuracy.