2 papers
math.NA2021
Multilevel Stein variational gradient descent with applications to Bayesian inverse problems
Terrence Alsup, Luca Venturi, Benjamin Peherstorfer
This work presents a multilevel variant of Stein variational gradient descent to more efficiently sample from target distributions. The key ingredient is a sequence of distribution…
math.NA2020
Context-aware surrogate modeling for balancing approximation and sampling costs in multi-fidelity importance sampling and Bayesian inverse problems
Terrence Alsup, Benjamin Peherstorfer
Multi-fidelity methods leverage low-cost surrogate models to speed up computations and make occasional recourse to expensive high-fidelity models to establish accuracy guarantees.…