[Todos CMAT] Seminario de Probabilidad y Estadística - Mario González (DMEL-Cenur Litoral Norte)

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Mie Oct 5 08:30:29 -03 2022


Seminario de Probabilidad y Estadística
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Título: "Solving Inverse Problems in Imaging by Posterior Sampling with Auto-Encoding Prior"

Expositor: Mario González (DMEL-Cenur Litoral Norte)

Resumen:
 
 In Bayesian statistics, prior knowledge about the unobserved signal of interest
is expressed as a prior distribution which, combined with observational data in
the form of a likelihood function allows to determine the posterior
distribution. This posterior can be used to derive point estimates such as the
MAP or MMSE estimators, but also to estimate uncertainty in these predictions,
e.g. in the form of confidence intervals. Most of the work using generative
models such as Generative Adversarial Networks (GAN) or Variational AutoEncoders
(VAE) as image priors focus on computing point estimates. On the other hand,
MCMC methods for sampling from the posterior distribution permit the exploration
of the solution space and computing point estimates as well as other statistics
about the solutions such as uncertainty estimates. However, the performance of
widely used methods like Metropolis-Hastings depends on having precise proposal
distributions which can be challenging to define in high-dimensional spaces. In
this talk, we present a Gibbs-like posterior sampling algorithm that exploits
the bidirectional nature of VAE networks. Thanks to the GPU's parallelization
capability, we efficiently run multiple chains which explore more rapidly the
posterior distribution and also give more accurate convergence tests. To
accelerate the burn-in period we explore the adaptation of the annealed
importance sampling with resampling method.
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Viernes 7/10 a las 10:30, zoom

Contacto: Alejandro Cholaquidis - acholaquidis en hotmail.com
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Datos para la reunión     virtual  :

https://salavirtual-udelar. zoom
.us/j/81121640094?pwd=SWVsZ1V2TTI5aDZob0NTdXVRVzhVZz09

Página del   seminario  :  https://pye.cmat.edu.uy/  seminario     Página del
grupo:  https://pye.cmat.edu.uy/home

Canal de youtube:  https://www.youtube.com/channel/UCOPZEOrLSAYPz2qCAL-KqMg/abo
ut
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