Discussion of "Exponential-family Embedding with Application to Cell Developmental Trajectories for Single-cell RNA-seq Data".

Exponential-family singular value decomposition (eSVD) is a new approach for embedding multivariate data into a lower-dimensional space. It provides an elegant dimension reduction framework with flexibility to handle one-parameter exponential family distributions and proven consistency. This approach adds a valuable new tool to the toolbox of data analysts. Here we discuss a number of open problems and challenges that remain to be addressed in the future in order to unleash the full potential of eSVD and other similar approaches.