论文信息 - Quantified Maximum Entropy

Quantified Maximum Entropy

This tutorial paper discusses the theoretical basis of quantified maximum entropy, as a technique for obtaining probabilistic estimates of images and other positive additive distributions from noisy and incomplete data. The analysis is fully Bayesian, with estimates always being obtained as probability distributions from which appropriate error bars can be found. This supersedes earlier techniques, even those using maximum entropy, which aimed to produce a single optimal distribution.

J. Skilling

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