Reviews: Augmented Neural ODEs

This paper connects a well-known result about the limits of diffeomorphisms, and applies it to the recent neural ODE model. The authors do experiments to show how adding extra channels reduces the computational cost of these models as well. R1 makes the valid point that the theoretical result was shown in 1955, and that the engineering trick of making layers wider is resnets existed previously. However, I'd say that the main contribution of this paper is in connecting these ideas to neural ODEs, and giving a possible explanation of why wider layers help in resnets. This paper also pushes forward our practical understanding of training neural ODEs. However, the paper and rebuttal avoided reporting absolute (probably poor) classification results.