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Bayesian Reimaging of Sparsity in Inverse Problems - SIAM-IS Virtual Seminar
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- 1 Intro
- 2 Linear Sparse Inverse Problems
- 3 Sparsity as a Belief
- 4 Sparsity in a Bayesian Way
- 5 Sparsity promoting priors
- 6 Hierarchical prior model for sparsity
- 7 The Bayesian solution is the posterior
- 8 Iterated Alternating Sequential (IAS) algorithm
- 9 IAS algorithm for Generalized Gamma hyperpriors
- 10 Approximate IAS and reduced model: the x update
- 11 The Gamma hyperprior (r = 1)
- 12 From Gamma to Generalized Gamma hyperprior
- 13 Convexity region
- 14 Special Generalized Gamma hyperpriors
- 15 Global Hybrid IAS
- 16 Support of the signal the meaning of
- 17 Computed example: 1D test
- 18 Computed examples: starry night
- 19 Dictionary Learning
- 20 MNIST Data: Handwritten digits
- 21 MNIST Dataset example: mismatch noise 0.01
- 22 MNIST Dataset: mismatch noise 0.05
