Reviews: Mining GOLD Samples for Conditional GANs

Clarity - The paper is very well written and very clearly structured - Experimental setup is clear and results are well explained Originality While there are several related methods that use the discriminator for estimating likelihood ratios (e.g., [1], [2], and [3]), the proposed method is specific for the conditional case, and is applied in a new way for modifying training and active learning. The paper clearly states that for rejection sampling is an extension of a similar approach for the unconditional case. In terms of novelty, I think the paper passes the required bar. Quality - The method used is sound. I think the paper does a good job in addressing the main issues that can arise in the proposed method, such as using sufficiently trained discriminators (line 132-133).