18 citations · 80 across the 22 of their papers we have counts for
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math.ST2017★ 18 cited
Random forward models and log-likelihoods in Bayesian inverse problems
H. C. Lie, T. J. Sullivan, A. L. Teckentrup
We consider the use of randomised forward models and log-likelihoods within the Bayesian approach to inverse problems. Such random approximations to the exact forward model or log-…
math.ST2017★ 4 cited
How Deep Are Deep Gaussian Processes?
Matthew M. Dunlop, Mark A. Girolami, Andrew M. Stuart +1
Recent research has shown the potential utility of Deep Gaussian Processes. These deep structures are probability distributions, designed through hierarchical construction, which a…