135 citations · 886 across the 57 of their papers we have counts for
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stat.ML2016
Likelihood-free inference by ratio estimation
Owen Thomas, Ritabrata Dutta, Jukka Corander +2
We consider the problem of parametric statistical inference when likelihood computations are prohibitively expensive but sampling from the model is possible. Several so-called like…
stat.ML2016★ 20 cited
Learning Gaussian Graphical Models With Fractional Marginal Pseudo-likelihood
Janne Leppä-aho, Johan Pensar, Teemu Roos +1
We propose a Bayesian approximate inference method for learning the dependence structure of a Gaussian graphical model. Using pseudo-likelihood, we derive an analytical expression…