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  1. No Access

    Article

    Variational Bayes with synthetic likelihood

    Synthetic likelihood is an attractive approach to likelihood-free inference when an approximately Gaussian summary statistic for the data, informative for inference about the parameters, is available. The synt...

    Victor M. H. Ong, David J. Nott, Minh-Ngoc Tran… in Statistics and Computing (2018)

  2. No Access

    Article

    Variational inference for sparse spectrum Gaussian process regression

    We develop a fast variational approximation scheme for Gaussian process (GP) regression, where the spectrum of the covariance function is subjected to a sparse approximation. Our approach enables uncertainty i...

    Linda S. L. Tan, Victor M. H. Ong, David J. Nott, Ajay Jasra in Statistics and Computing (2016)