1. 1) C. E. Rasmussen and C. K. I. Williams, Gaussian Processes for Machine Learning (The MIT Press, Cambridge, Mass., 2006).
2. 2) A. G. de G. Matthews, M. Rowland, J. Hron, R. E. Turner and Z. Ghahramani, ``Gaussian process behaviour in wide deep neural networks,'' Proc. ICLR (2018).
3. 3) J. Lee, Y. Bahri, R. Novak, S. S. Schoenholz, J. Pennington and J. Sohl-Dickstein, ``Deep neural networks as Gaussian processes,'' Proc. ICLR (2018).
4. 4) R. M. Neal, ``Priors for infinite networks,'' in Bayesian Learning for Neural Networks, Lecture Notes in Statistics, Vol. 118 (Springer, New York, 1996).
5. 5) A. Rahimi and B. Recht, ``Random features for large-scale kernel machines,'' Proc. NIPS, pp. 1177-1184 (2008).