M. Filippone, R. Engler. Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE), January 2015. arXiv:1501.05427. [ bib | pdf | http | code ]

M. Filippone and M. Girolami. Pseudo-marginal Bayesian inference for Gaussian processes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(11):2214-2226, 2014. [ bib | pdf | http | code ]

M. Filippone, M. Zhong, and M. Girolami. A comparative evaluation of stochastic-based inference methods for Gaussian process models. Machine Learning, 93(1):93-114, 2013. [ bib | pdf | http | code ]