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Score Matching
Score Matching
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Question 1 of 6
120s
intermediate (6/10)
conceptual
Why does the partition function stop mattering when we train a data-space score field?
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A.
Because the score is a gradient with respect to the input variable, and the partition function does not depend on that variable
B.
Because score matching replaces the partition function with a sample average over the model distribution
C.
Because integration by parts cancels every normalization constant in every likelihood-based objective
D.
Because the partition function is always equal to one after taking logs
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