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We propose a framework for solving high-dimensional Bayesian inference problems using \emph{structure-exploiting} low-dimensional transport maps or flows.
Remarks on a multivariate transformation
M. Rosenblatt · 1952
Earlier work this paper cites.
Contributions to the theory of convex bodies
H. Knothe et al · 1957
Earlier work this paper cites.
Quadrature and interpolation formulas for tensor products of certain classes of functions
S. Smolyak · 1963
Earlier work this paper cites.
Calculation of Gauss quadrature rules
G. H. Golub and J. H. Welsch · 1969
Earlier work this paper cites.
The Convergence of a Class of Double Rank Minimization Algorithms. Part {II}
C. G. Broyden · 1970
Earlier work this paper cites.
Projection pursuit
P. J. Huber · 1985
Earlier work this paper cites.
Log Gaussian Cox Processes
J. Møller, A. R. Syversveen, and R. Waagepetersen · 1998
Earlier work this paper cites.
Monte Carlo errors with less errors
U. Wolff · 2004
Earlier work this paper cites.
Triangular transformations of measures
V. I. Bogachev, A. V. Kolesnikov, and K. V. Medvedev · 2005
Earlier work this paper cites.
Scaling limits for the transient phase of local Metropolis-Hastings algorithms
O. F. Christensen, G. O. Roberts, and J. S. Rosenthal · 2005
Earlier work this paper cites.
A tutorial on adaptive MCMC
C. Andrieu and J. Thoms · 2008
Earlier work this paper cites.
Greedy approximation
V. N. Temlyakov · 2008
Earlier work this paper cites.
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C. Villani · 2008
Earlier work this paper cites.
Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations
H. Rue, S. Martino, and N. Chopin · 2009
Earlier work this paper cites.
From Knothe’s transport to Brenier’s map and a continuation method for optimal transport
G. Carlier, A. Galichon, and F. Santambrogio · 2010
Earlier work this paper cites.
Dolfin: Automated finite element computing
A. Logg and G. N. Wells · 2010
Earlier work this paper cites.
Inverse problems: a Bayesian perspective
A. M. Stuart · 2010
Earlier work this paper cites.
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M. Girolami and B. Calderhead · 2011
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MCMC using Hamiltonian dynamics
R. M. Neal et al · 2011
Earlier work this paper cites.
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T. Moselhy and Y. Marzouk · 2012
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Masked autoregressive flow for density estimation
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Cubature, approximation, and isotropy in the hypercube
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Later among the works it cites.
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R. T. Q. Chen, Y. Rubanova, J. Bettencourt, and D. Duvenaud · 2018
Later among the works it cites.
A Stein variational Newton method
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M. Parno and Y. M. Marzouk · 2018
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