Manifold-aligned Neighbor Embedding

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.

Accepted at the ICLR 2022 Workshop on Geometrical and Topological Representation Learning