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What is an intuitive interpretation of the concept of maximum entropy? I want to understand this concept better but what I'm finding is too "advanced" right now. Can anyone simplify it ... imagine I'm 10 years old:) For starters i'm confused about what it's measuring, how it does that (roughly), and where one would apply it. Why do we talk of max entropy related to a Gaussian distribution vs, say, related to a uniform distribution. Are there different uses for this term (physics vs statistics?)

Thank you

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Typically, we have some constraints on a distribution (for example, the marginal distributions), and we seek a max-entropy distribution satisfying these constraints. This basically means that, apart from the known constraints, we know as little as possible about the distribution. We do not want to specify anything about the distribution that is not already implied by the known constraints.

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