Certified coordinate selection for high-dimensional Bayesian inversion with Laplace prior
Sign Up to like & getrecommendations! Published in 2024 at "Statistics and Computing"
DOI: 10.1007/s11222-024-10445-1
Abstract: We consider high-dimensional Bayesian inverse problems with arbitrary likelihood and product-form Laplace prior for which we provide a certified approximation of the posterior in the Hellinger distance. The approximate posterior differs from the prior only… read more here.
Keywords: coordinate selection; certified coordinate; dimensional bayesian; high dimensional ... See more keywords
High-dimensional Bayesian optimization with projections using quantile Gaussian processes
Sign Up to like & getrecommendations! Published in 2020 at "Optimization Letters"
DOI: 10.1007/s11590-019-01433-w
Abstract: Key challenges of Bayesian optimization in high dimensions are both learning the response surface and optimizing an acquisition function. The acquisition function selects a new point to evaluate the black-box function. Both challenges can be… read more here.
Keywords: dimensional bayesian; optimization; optimization projections; high dimensional ... See more keywords
Trans-dimensional Bayesian inversion of airborne electromagnetic data for 2D conductivity profiles
Sign Up to like & getrecommendations! Published in 2017 at "Exploration Geophysics"
DOI: 10.1071/eg16139
Abstract: This paper presents the application of a novel trans-dimensional sampling approach to a time domain airborne electromagnetic (AEM) inverse problem to solve for plausible conductivities of the subsurface. Geophysical inverse field problems, such as time… read more here.
Keywords: trans dimensional; airborne electromagnetic; dimensional bayesian; conductivity ... See more keywords
Automated Filter Pruning Based on High-Dimensional Bayesian Optimization
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3153025
Abstract: Filter pruning is necessary to efficiently deploy convolutional neural networks on edge devices that have limited computational resources and power budgets. With conventional filter pruning techniques, the same pruning rate is manually specified for different… read more here.
Keywords: filter pruning; bayesian optimization; dimensional bayesian; pruning rate ... See more keywords
Reconstruction of Multiple Target Bodies Using Trans-Dimensional Bayesian Inversion With Different Constraints
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2024.3382106
Abstract: Geophysical geometry inversion aims to reconstruct the geometrical characteristics of subsurface target bodies, which is different from conventional inversion techniques that focus on subsurface physical properties (e.g., density and velocity). The published works on geometry… read more here.
Keywords: trans dimensional; dimensional bayesian; geometry; target bodies ... See more keywords
ANOVA-GP Modeling for High-Dimensional Bayesian Inverse Problems
Sign Up to like & getrecommendations! Published in 2024 at "Mathematics"
DOI: 10.3390/math12020301
Abstract: Markov chain Monte Carlo (MCMC) stands out as an effective method for tackling Bayesian inverse problems. However, when dealing with computationally expensive forward models and high-dimensional parameter spaces, the challenge of repeated sampling becomes pronounced.… read more here.
Keywords: inverse problems; gaussian process; dimensional bayesian; high dimensional ... See more keywords