Year: 2022
Type: preprint
Abstract: In this paper, we introduce a neighbor embedding framework for manifold alignment. We demonstrate the efficacy of the framework using a manifold-aligned version of the uniform manifold approximation and projection algorithm. We show that our algorithm can learn an aligned manifold that is visually competitive to embedding of the whole dataset.
Source: arXiv (Cornell University)
Authors: Islam, Mohammad Tariqul, Fleischer, Jason W.
Institution: Princeton University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: G1523888516, G4746683970, G6067253068
OpenAlex ID: W4281482914