Let’s think about a likelihood which is non-trivial y=(x+\mu+\sigma\epsilon)^2,\ \text{with}\ \epsilon\sim\mathcal{N}(0,1) I know this can be transformed into ChiSquared dist analytically. But we still will encounter more complicated and non-linear function (maybe deep nerual network!!) involving…

How to model very complicated likelihood automatically？

ricardoV94 Split this topic September 6, 2025, 1:16pm 3

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