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It seems to conflict with Algorithm 2 in the Neurips paper (https://arxiv.org/pdf/1910.13148.pdf), as in that algorithm, the log_probs are only calculated at the end, whereas in the code, it is updated at every iteration in the for loop.
The text was updated successfully, but these errors were encountered:
Hi. Could you please explain how the
log_prob
function for the tensor ring induced prior works - mainly this line: https://github.com/insilicomedicine/TRIP/blob/master/core/learnable_priors/trip.py#L164It seems to conflict with
Algorithm 2
in the Neurips paper (https://arxiv.org/pdf/1910.13148.pdf), as in that algorithm, the log_probs are only calculated at the end, whereas in the code, it is updated at every iteration in the for loop.The text was updated successfully, but these errors were encountered: