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I am trying to find out a paper that mentioned that in a conditional setting, generative adversarial networks overlook the sampled noise. Please let me know if this is not the right place or way to ask this question.

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I came across this paper "Image-to-Image Translation with Conditional Adversarial Networks", but the way how the noise is added is not described in the paper.

Past conditional GANs have acknowledged this and provided Gaussian noise z as an input to the generator, in addition to x (e.g., [54]). In initial experiments, we did not find this strategy effective – the generator simply learned to ignore the noise – which is consistent with Mathieu et al. [39].

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