Review for NeurIPS paper: General Control Functions for Causal Effect Estimation from IVs

The reviewers and myself are in agreement that the paper proposes an interesting methodological approach for the instrumental variable regression problem without the additive separability assumption, that is widespread in the literature. The approach also combines interesting ideas from both the econometrics/statistics literature (control functions) and the machine learning literature (autoencoders). The reviewers continue to have concerns on the relation of the identification results to prior literature. The authors tried to address this in the rebuttal and point to a relevant discussion in the paper. However, the short discussion in the paper and in the rebuttal is not sufficient.