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First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. Summary: This paper proposes a deep learning based spatial attention mechanism based on a probabilistic generative model. The approach enables identifying novel objects in large images, and hence might allow for better exploitation of unlabeled, uncropped data. Main Comments: This paper takes a solid step towards being able to apply deep learning methods to large uncropped, unlabeled images. The experimental section contains a number of interesting experiments verifying that the approximate inference method is working, and that HMC is still worthwhile beyond this.