Bayesian Hyperbolic Multidimensional Scaling

1 code implementation • 26 Oct 2022 • Bolun Liu, Shane Lubold, Adrian E. Raftery, Tyler H. McCormick

We propose a Bayesian approach to multidimensional scaling when the low-dimensional manifold is hyperbolic.

Spectral goodness-of-fit tests for complete and partial network data

1 code implementation • 17 Jun 2021 • Shane Lubold, Bolun Liu, Tyler H. McCormick

In this work, we address the question of how to determine whether a parametric model, such as a stochastic block model or latent space model, fits a dataset well and will extrapolate to similar data.

Community Detection Stochastic Block Model