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stat.CO2026
Sampling through iterated approximation: Gradient-free and multi-fidelity Bayesian inference via transport
Daniel Sharp, Bart van Bloemen Waanders, Youssef Marzouk
We develop an iterative framework for Bayesian inference problems where the posterior distribution may involve computationally intensive models, intractable gradients, significant…
math.OC2026
Path-OED for infinite-dimensional Bayesian linear inverse problems governed by PDEs
J. Nicholas Neuberger, Alen Alexanderian, Bart van Bloemen Waanders +1
We consider infinite-dimensional Bayesian linear inverse problems governed by time-dependent partial differential equations (PDEs) and develop a mathematical and computational fram…