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By mixing the target posterior distribution with a surrogate distribution, of which the normalizing constant is tractable, we propose a method for estimating the marginal likelihood using the Wang-Landau algorithm. We show that a faster convergence of the proposed method can be achieved via the momentum acceleration. Two implementation strategies are detailed: (i) facilitating global jumps between the posterior and surrogate distributions via the Multiple-try Metropolis; (ii) constructing thedoi:10.6084/m9.figshare.12851205.v1 fatcat:wkwqvbgepvcqnlxaizxxjgpefe