Here are the most tweeted papers that were uploaded onto arXiv during November 2020. Results are powered by Arxiv Sanity Preserver. Abstract: Efficient gradient computation of the Jacobian determinant term is a core problem of the normalizing flow framework. Thus, most proposed flow models either restrict to a function class with easy evaluation of the Jacobian determinant, or an efficient estimator thereof. However, these restrictions limit the performance of such density models, frequently requiring significant depth to reach desired performance levels.