Appendix A Inference in the Generative Model

A.1 Generative model We choose the deconvolutional generative model (DGM) [25] as the generative feedback in CNN-F. The graphical model of the DGM is shown in Figure 2 (middle). In this section, we provide proofs for Theorem 2.1. Without loss of generality, we consider a DGM that has the following architecture. Lemma A.1 shows that logits output from the corresponding CNN of the DGM is proportional to the inner product of generated image and input image plus Lemma A.1 to show that CNN performs Bayesian inference in the DGM.