Reviews: Learning from brains how to regularize machines

CNNs, like visual cortex, build a representation of the visual world that is useful to the "viewer". We have known for a while that CNNs trained on object recognition tasks capture some (but not all) aspects of the representation computed by primate visual cortex. Here the authors propose to bridge the gap by explicitly encouraging a CNN to build a representation that is "similar" to the one computed by the visual cortex of mice. This is a neat idea and certainly a novel one. The paper is clearly written, which I appreciated.