Uniform Manifold Approximation and Projection (UMAP)-Reference-Cited by-同舟云学术

Uniform Manifold Approximation and Projection (UMAP)

Published:2023 Issue: Volume: Page:479-497
ISSN:
Container-title:Elements of Dimensionality Reduction and Manifold Learning
language:
Short-container-title:

Author:

Ghojogh Benyamin^ORCID,Crowley Mark^ORCID,Karray Fakhri^ORCID,Ghodsi Ali^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-10602-6_17

Reference28 articles.

1. Etienne Becht et al. “Dimensionality reduction for visualizing single-cell data using UMAP”. In: Nature biotechnology 37.1 (2019), pp. 38–44.

2. Mikhail Belkin and Partha Niyogi. “Laplacian eigenmaps and spectral techniques for embedding and clustering”. In: Advances in neural information processing systems. Vol. 14. 14. 2001, pp. 585–591.

3. Jan Niklas Böhm, Philipp Berens, and Dmitry Kobak. “A unifying perspective on neighbor embeddings along the attraction-repulsion spectrum”. In: arXiv preprint arXiv:2007.08902 (2020).

4. Shan Carter et al. “Activation atlas”. In: Distill 4.3 (2019), e15.

5. Andy Coenen et al. “Visualizing and measuring the geometry of BERT”. In: arXiv preprint arXiv:1906.02715 (2019).

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