We analyze the convergence properties of Fermat distances, a family of
d...
In linear distance metric learning, we are given data in one Euclidean m...
Graph Neural Networks (GNNs) extend the success of neural networks to
gr...
Graph neural networks (GNNs) have attracted much attention due to their
...
This article discusses a generalization of the 1-dimensional multi-refer...
New geometric and computational analyses of power-weighted shortest-path...
We propose a nonlinear, wavelet based signal representation that is
tran...
Classical multidimensional scaling is an important tool for dimension
re...
We consider the problem of clustering with the longest leg path distance...