4 papers
Bayesian Multi-scale Modeling of Factor Matrix without using Partition Tree
Maoran Xu, Leo L. Duan
The multi-scale factor models are particularly appealing for analyzing matrix- or tensor-valued data, due to their adaptiveness to local geometry and intuitive interpretation. Howe…
Spiked Laplacian Graphs: Bayesian Community Detection in Heterogeneous Networks
Leo L Duan, George Michailidis, Mingzhou Ding
In network data analysis, it is becoming common to work with a collection of graphs that exhibit \emph{heterogeneity}. For example, neuroimaging data from patient cohorts are incre…
Tuning-Free Disentanglement via Projection
Yue Bai, Leo L. Duan
In representation learning and non-linear dimension reduction, there is a huge interest to learn the 'disentangled' latent variables, where each sub-coordinate almost uniquely cont…
Latent Simplex Position Model: High Dimensional Multi-view Clustering with Uncertainty Quantification
Leo L Duan
High dimensional data often contain multiple facets, and several clustering patterns can co-exist under different variable subspaces, also known as the views. While multi-view clus…