  In a recent paper, "Why does deep and cheap learning work so well?", Lin and
Tegmark claim to show that the mapping between deep belief networks and the
variational renormalization group derived in [arXiv:1410.3831] is invalid, and
present 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 a
misunderstanding of the variational RG procedure proposed by Kadanoff. We also
explain why the "counterexample" of Lin and Tegmark is compatible with the
mapping proposed in [arXiv:1410.3831].
