I asked this question on /r/MLQuestions aswell.
Although similar questions have been asked a few times here on reddit and elsewhere, I'm still unclear on how one would calculate the log-likelihood of, say, the CIFAR10 test set, under VAE/VQVAE models, as presented in
and related papers. A "black-box" method using tensorflow's tf.distributions (although for binarized MINST) can be found here
, but I would love to understand how this value is calculated "manually".
Would anyone care to elaborate on exactly how to estimate this reported value for CIFAR10? I mention this dataset specifically since it's used as benchmark in many recent papers, and since CIFAR10 isn't binary like binarized MNIST.
I'm very thankful for any help! :)
PS: I am aware of a previous explanation on how to convert the log-likelihood value to bits/dim here:
but following this method requires that some loglikelihood (5371 in this case) has already been calculated (in the NICE code, this is done for the particular case)