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CPS1488 Willem van den B. et al.
5. Furrer, R., M. G. Genton, and D. Nychka (2006). Covariance tapering for
interpolation of large spatial datasets. Journal of Computational and
Graphical Statistics 15(3), 502–523.
6. Gehre, M. and B. Jin (2014). Expectation propagation for nonlinear
inverse problems – with an application to electrical impedance
tomography. Journal of Computational Physics 259, 513–535.
7. Gelman, A., A. Vehtari, P. Jyl¨anki, C. Robert, N. Chopin, and J. P.
Cunningham (2014). Expectation propagation as a way of life.
arXiv:1412.4869v3.
8. Gianniotis, N. (2019). Mixed variational inference. arXiv:1901.04791v1.
9. Kaipio, J. and E. Somersalo (2005). Statistical and Computational Inverse
Problems. Springer-Verlag.
10. Minka, T. P. (2001). Expectation propagation for approximate Bayesian
inference. In Proceedings of the Seventeenth Conference on Uncertainty
in Artificial Intelligence, pp. 362–369.
11. Reid, A., S. O’Callaghan, E. V. Bonilla, L. McCalman, T. Rawling, and F.
Ramos (2013). Bayesian joint inversions for the exploration of earth
resources. In Proceedings of the Twenty-Third International Joint
Conference on Artificial Intelligence, pp. 2877–2884.
12. Steinberg, D. M. and E. V. Bonilla (2014). Extended and unscented
Gaussian processes. In Advances in Neural Information Processing
Systems 27, pp. 1251–1259.
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