I'm having trouble deriving the KL divergence formula assuming two multivariate normal distributions. I've done the univariate case fairly easily. However, it's been quite a while since I took math stats, so I'm having some trouble extending it to the multivariate case. I'm sure I'm just missing something simple. Here's what I have...

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As all the other losses in PyTorch, this function expects the first argument, input, to be the output of the model (e.g. the neural network) and the second, target, to be the observations in the dataset. This differs from the standard mathematical notation KL (P\ ||\ Q) K L(P ∣∣ Q) where P P denotes the distribution of the observations and ...
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