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02/22/2022
A gradient-free subspace-adjusting ensemble sampler for infinite-dimensional Bayesian inverse problems
Sampling of sharp posteriors in high dimensions is a challenging problem...
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04/07/2020
Stability of Gibbs Posteriors from the Wasserstein Loss for Bayesian Full Waveform Inversion
Recently, the Wasserstein loss function has been proven to be effective ...
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10/31/2019
Multiplicative noise in Bayesian inverse problems: Well-posedness and consistency of MAP estimators
Multiplicative noise arises in inverse problems when, for example, uncer...
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05/10/2019
Hyperparameter Estimation in Bayesian MAP Estimation: Parameterizations and Consistency
The Bayesian formulation of inverse problems is attractive for three pri...
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05/23/2018
Large Data and Zero Noise Limits of Graph-Based Semi-Supervised Learning Algorithms
Scalings in which the graph Laplacian approaches a differential operator...
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03/09/2018
Robust MCMC Sampling with Non-Gaussian and Hierarchical Priors in High Dimensions
A key problem in inference for high dimensional unknowns is the design o...
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11/30/2017