2bcab9d935d219641434683dd9d18a03-Reviews.html

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. This study investigates two algorithms for fast inference in generative models of olfaction. Their goal is to compute the most likely, linear mixture of odors comprising an olfactory stimulus. One of the algorithms employs variational inference, while the other is based on a sampling scheme. Simulations demonstrate that both algorithms perform suitably well, and the authors claim that inference is performed rapidly within the first 100 ms, while eliminating false positives (detection of odors not present in a particular stimulus) takes much longer and is difficult when more than two odors are present.