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Found 3 papers, 2 papers with code
Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport
We tackle this challenging Bayesian inference problem using a likelihood-free approach based on measure transport together with the construction of summary statistics for the image data.
A stochastic Stein Variational Newton method
Meanwhile, Stein variational Newton (SVN), a Newton-like extension of SVGD, dramatically accelerates the convergence of SVGD by incorporating Hessian information into the dynamics, but also produces biased samples.
Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High Dimensions
We propose a projected Stein variational Newton (pSVN) method for high-dimensional Bayesian inference.
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