In geographic data analysis, one is often given point of different categories (such as facilities a university categorized by department). Drawing upon recent research on set visualization, we want to visualize category membership connecting points the same with visual links. Existing approaches that follow this path usually insist all members category, which may lead many crossings and clutter...

Identification of dynamic nonlinear panel data models is an important and delicate problem in econometrics. In this paper we provide insights that shed light on the identification of parameters of some commonly used models. Using this insight, we are able to show through simple calculations that point identification often fails in these models. On the other hand, these calculations also suggest...

Unlike on images, semantic learning on 3D point clouds using a deep network is challenging due to the naturally unordered data structure. Among existing works, PointNet has achieved promising results by directly learning on point sets. However, it does not take full advantage of a point’s local neighborhood that contains fine-grained structural information which turns out to be helpful towards ...