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In a recent paper, "Why does deep and cheap learning work so well?", Lin andTegmark claim to show that the mapping between deep belief networks and thevariational renormalization group derived in [arXiv:1410.3831] is invalid, andpresent a "counterexample" that claims to show that this mapping does not hold.In this comment, we show that these claims are incorrect and stem from amisunderstanding of the variational RG procedure proposed by Kadanoff. We alsoexplain why the "counterexample" of Lin and Tegmark is compatible with themapping proposed in [arXiv:1410.3831].

Comment on "Why does deep and cheap learning work so well?" [arXiv:1608.08225]