Bayesian Scientific Computing
The once esoteric idea of embedding scientific computing into a probabilistic framework, mostly along the lines of the Bayesian paradigm, has recently enjoyed wide popularity and found its way into numerous applications. This book provides an insider’s view of how to combine two mature fields, scien...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Cham
Springer International Publishing
2023, 2023
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| Edition: | 1st ed. 2023 |
| Series: | Applied Mathematical Sciences
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Inverse problems and subjective computing
- Linear algebra
- Continuous and discrete multivariate distributions
- Introduction to sampling
- The praise of ignorance: randomness as lack of certainty
- Enter subject: Construction of priors
- Posterior densities, ill-conditioning, and classical regularization
- Conditional Gaussian densities
- Iterative linear solvers and priorconditioners
- Hierarchical models and Bayesian sparsity
- Sampling: the real thing
- Dynamic methods and learning from the past
- Bayesian filtering and Gaussian densities