Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualisation similarly to t-SNE, but also for general non-linear dimension reduction. UMAP has a rigorous mathematical foundation, but is simple to use, with a scikit-learn compatible API. UMAP is among the fastest manifold learning implementations available -significantly faster than most t-SNE implementations.
No takes yet. Share an insight, caveat, or question.
McInnes et al. (2018) studied this question.
Synapse has enriched 5 related papers. Consider them for comparative context: