UMAP: Uniform Manifold Approximation and Projection

Leland McInnes; John Healy; Nathaniel Saul; Lukas Großberger · The Journal of Open Source Software · 2018

Resource page

Quick overview. Review the resource’s basic details, then access the content using the main button. This page shows only the information needed to identify, cite, and open the work.

Author / responsible party

Leland McInnes; John Healy; Nathaniel Saul; Lukas Großberger

Publisher

The Journal of Open Source Software

Year

2018

Language

English

Resource access

Open the content from the main option or choose another available source.

OpenAlex OpenAlex Works

Entrar por OpenAlex

Main access

Resource page

Resource reference page. Full text availability has not been automatically confirmed.

Open resource

Summary

Descripción general del contenido del recurso.

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.

How to cite

Elegí el formato que necesitás y copiá la referencia al portapapeles.

APA 7

McInnes, L, Healy, J, Saul, N, & Großberger, L. (2018). UMAP: Uniform Manifold Approximation and Projection. https://doi.org/10.21105/joss.00861

MLA

McInnes, Leland, et al. "UMAP: Uniform Manifold Approximation and Projection." 2018. https://doi.org/10.21105/joss.00861.

Chicago

McInnes, Leland, John Healy, Nathaniel Saul, and Lukas Großberger. 2018. "UMAP: Uniform Manifold Approximation and Projection.". https://doi.org/10.21105/joss.00861.

Harvard

McInnes, L. et al. 2018, UMAP: Uniform Manifold Approximation and Projection, The Journal of Open Source Software, available at: https://doi.org/10.21105/joss.00861 [Accessed 8 Aug. 2026].

Share and print

Save the record, copy its permanent link, or print it as a PDF.

Export reference

You can export the record in common formats for use in a reference manager.

RIS BibTeX

Resource details

Bibliographic information to help confirm that this is the correct material.

Title: UMAP: Uniform Manifold Approximation and Projection

Author / contributors: Leland McInnes; John Healy; Nathaniel Saul; Lukas Großberger

Publisher: The Journal of Open Source Software

Publication year: 2018

Language: English

Subjects

Explore related resources through these subjects.

Projection (relational algebra); Manifold (fluid mechanics); Mathematics; Computer science; Geometry; Algorithm; Engineering; Mechanical engineering