Bayesian Inference: Optimal Estimation

In course

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Description

This lecture covers the concept of optimal Bayesian inference, focusing on denoising and scalar estimation. It delves into the posterior probability, Gaussian and Gauss-Bernoulli distributions, and the Bayes theorem. The lecture also explores the phase transition in the Curie-Weiss model and the spectrum of random matrices.

Instructors (2)

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Official source

https://mediaspace.epfl.ch/media/0_cv7dazi7

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Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics, Statistical hypothesis testing

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