本文是随机矩阵理论系列的第十一篇文章，讲述了随机矩阵与随机过程之间的联系。
Neil Lawrence
Ryan P. Adams, Iain Murray and David JC Mackay, Tractable Nonparametric Bayesian Inference in Poisson Processes with Gaussian Process Intensities, ICML 2009.
Alex Kulesza and Ben Taskar, Structured Determinantal Point Processes, NIPS 2010.
James T. Kwok and Ryan P. Adams, Priors for Diversity in Generative Latent Variable Models, NIPS 2012.
Jasper Snoek, Ryan P. Adams and Richard S. Zemel, A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking Data, NIPS 2013.
Peter J. Forrester and Joel L. Lebowitz, Local Central Limit Theorem for Determinantal Point Processes, J Stat Phys, 2014.
Scott W. Linderman and Ryan P. Adams, Discovering Latent Network Structure in Point Process Data, ICML 2014.
Raja Hafiz Affandi, Emily B. Fox, Ryan P. Adams and Ben Taskar, Learning the Parameters of Determinantal Point Process Kernels, ICML 2014.
Andreas Damianou, Deep Gaussian Processes and Variational Propagation of Uncertainty, PhD Thesis 2015.
Jaehoon Lee, Yasaman Bahri, Roman Novak, Samuel S. Schoenholz, Jeffrey Pennington and Jascha Sohl-Dickstein, DEEP NEURAL NETWORKS AS GAUSSIAN PROCESSES, 2017.