4 papers · 1 filter
Learning manifold diffusion semigroups from graph transition matrices
Xiuyuan Cheng, Nan Wu
We consider graph diffusion processes constructed from finite i.i.d. samples drawn from an unknown manifold embedded in ambient Euclidean space, where the graph affinity is defined…
Improved convergence rate of kNN graph Laplacians: differentiable self-tuned affinity
Xiuyuan Cheng, Yixuan Tan, Nan Wu
In graph-based data analysis, -nearest neighbor (NN) graphs are widely used due to their adaptivity to local data densities. Allowing weighted edges in the graph, the kerneli…
Inferring manifolds using Gaussian processes
David B Dunson, Nan Wu
It is often of interest to infer lower-dimensional structure underlying complex data. As a flexible class of non-linear structures, it is common to focus on Riemannian manifolds. M…
Boundary Detection Algorithm Inspired by Locally Linear Embedding
Pei-Cheng Kuo, Nan Wu
In the study of high-dimensional data, it is often assumed that the data set possesses an underlying lower-dimensional structure. A practical model for this structure is an embedde…