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Information-theoretic limits of Bayesian inference in Gaussian noise

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No logo availableBanff International Research Station (BIRS) for Mathematical Innovation and Discovery
 Miolane, Léo

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Information-theoretic limits of Bayesian inference in Gaussian noise
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54
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CC Attribution - NonCommercial - NoDerivatives 4.0 International:
You are free to use, copy, distribute and transmit the work or content in unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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We will discuss briefly the statistical estimation of a signal (vector, matrix, tensor...) corrupted by Gaussian noise. We will restrict ourselves to information-theoretic considerations and draw connections with statistical physics (random energy model, p-spin model).