Reviews: Augmented Neural ODEs

Originality: The method is original in the deep learning literature. Though limitations of ODEs cannot cross paths is quite well-known, this paper views this deficiency from a modeling perspective and removes it while keeping within the ODE framework. Quality & Clarity: The motivations for ANODE are well-explained and the experiments are well-chosen. The prose is very well written, and with many simple visualizations that support their claims. Significance: Given the interest in ODE-based modeling, this work has enough impact for a NeurIPS paper.