Reviews: Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs

The paper proposed a quite interesting idea of representing data by weighted graphs (shortest path between nodes). Reviewers have raised concerns on edge dependency and the given similarity metric. However, I'm less worried about making the independence assumption because after all, it's a model, and it seems to work well in experiments. Likewise, it is also common in variational inference to use independent distribution to approximate a graphical model, based on which learning is carried out. What interests me more is the general methodology of optimization.