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UMAP: Uniform Manifold Approximation and Projection

Leland McInnes, John Healy, Nathaniel Saul, Lukas Großberger
<span title="2018-09-02">2018</span> <i title="The Open Journal"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3gk7mr6lhvdwnkgcicv7r2lrry" style="color: black;">Journal of Open Source Software</a> </i> &nbsp;
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 is among the fastest manifold learning implementations available -significantly faster than most t-SNE implementations.  ...  UMAP: Uniform Manifold Approximation and Projection. Journal of Open Source Software, 3(29), 861. https://doi.org/10.21105/joss.00861  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.21105/joss.00861">doi:10.21105/joss.00861</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7wbja53lm5bntjkex2mqzo4hlm">fatcat:7wbja53lm5bntjkex2mqzo4hlm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190224210928/http://pdfs.semanticscholar.org/5df8/b7279e0d80b6f418f7d5cb79b27cdba9ed16.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/5d/f8/5df8b7279e0d80b6f418f7d5cb79b27cdba9ed16.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.21105/joss.00861"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction [article]

Leland McInnes, John Healy, James Melville
<span title="2020-09-18">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
UMAP (Uniform Manifold Approximation and Projection) is a novel manifold learning technique for dimension reduction.  ...  The UMAP algorithm is competitive with t-SNE for visualization quality, and arguably preserves more of the global structure with superior run time performance.  ...  Acknowledgements e authors would like to thank Colin Weir, Rick Jardine, Brendan Fong, David Spivak and Dmitry Kobak for discussion and useful commentary on various dra s of this paper.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1802.03426v3">arXiv:1802.03426v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/m47pbjy7vzcqbg56ncpq5aiyte">fatcat:m47pbjy7vzcqbg56ncpq5aiyte</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200922001735/https://arxiv.org/pdf/1802.03426v3.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1802.03426v3" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Uniform Manifold Approximation and Projection (UMAP) and its Variants: Tutorial and Survey [article]

Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley
<span title="2021-08-25">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Uniform Manifold Approximation and Projection (UMAP) is one of the state-of-the-art methods for dimensionality reduction and data visualization.  ...  This is a tutorial and survey paper on UMAP and its variants.  ...  Uniform Manifold Approximation and Projection (UMAP) (McInnes et al., 2018) .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2109.02508v1">arXiv:2109.02508v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/hjffgntw2vbhzpio6ydhboqv3m">fatcat:hjffgntw2vbhzpio6ydhboqv3m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210909070556/https://arxiv.org/pdf/2109.02508v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/de/0d/de0d4779c3e0678828aad8e79df22ec38d0324da.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2109.02508v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Progressive Uniform Manifold Approximation and Projection

Hyung-Kwon Ko, Jaemin Jo, Jinwook Seo
<span title="">2020</span> <i title="The Eurographics Association"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/fvnub6swsjfnhdwblr4kp44pry" style="color: black;">Eurographics Conference on Visualization</a> </i> &nbsp;
We present a progressive algorithm for the Uniform Manifold Approximation and Projection (UMAP), called the Progressive UMAP.  ...  In our experiment with the Fashion MNIST dataset, we found that Progressive UMAP could generate the first approximate projection within a few seconds while also sufficiently capturing the important structures  ...  Conclusion and Future Work We present a progressive algorithm for the Uniform Manifold Approximation and Projection (Progressive UMAP).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2312/evs.20201061">doi:10.2312/evs.20201061</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/vissym/KoJS20.html">dblp:conf/vissym/KoJS20</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wauenhizm5flzjfuuvwmek7ycu">fatcat:wauenhizm5flzjfuuvwmek7ycu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200603032842/https://diglib.eg.org/xmlui/bitstream/handle/10.2312/evs20201061/133-137.pdf;jsessionid=A698488CC31BD1B0E6B097AAB5899A3C?sequence=2" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3b/9d/3b9d887496ef3c538d68d862fd9c380cef68f69d.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2312/evs.20201061"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

HUMAP: Hierarchical Uniform Manifold Approximation and Projection [article]

Wilson E. Marcílio-Jr and Danilo M. Eler and Fernando V. Paulovich and Rafael M. Martins
<span title="2021-11-08">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
However, current hierarchical DR techniques are not fully capable of addressing literature problems because they do not preserve the projection mental map across hierarchical levels or are not suitable  ...  These techniques, often represented by scatter plots, are employed in diverse science domains and facilitate similarity analysis among clusters and data samples.  ...  ACKNOWLEDGMENTS This work was supported by Fundac ¸ão de Amparo à Pesquisa (FAPESP) [grant number #2018/17881-3] and the Coordenac ¸ão de Aperfeic ¸oamento de Pessoal de Nível Superior (CAPES) [grant number  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2106.07718v2">arXiv:2106.07718v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/za5wg2bym5b2rkjq2bh3muugfa">fatcat:za5wg2bym5b2rkjq2bh3muugfa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211113045014/https://arxiv.org/pdf/2106.07718v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/69/cf/69cffbf273fa42c0ea97d645ecc61006f7e02486.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2106.07718v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Modeling disciplinary structure with uniform manifold approximation and projection

Maximilian Noichl
<span title="2020-02-20">2020</span> <i title="Zenodo"> Zenodo </i> &nbsp;
To supplement such detailed accounts, this project proposes the use of Uniform Manifold Approximation and Projection (McInnes et al. 2018) for the mapping and clustering of disciplines.  ...  This data was in turn transformed with uniform manifold approximation and projection (UMAP) into a two dimensional map, which will not only be presented as a poster, but is made available in interactive  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.4621966">doi:10.5281/zenodo.4621966</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/576dwetk7nhgpphsdtyhvuon34">fatcat:576dwetk7nhgpphsdtyhvuon34</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210330081148/https://zenodo.org/record/4621966/files/272_final-NOICHL_Maximilian_Modeling_disciplinary_structure_with_unifo.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/4e/32/4e325d1d4cd3ea53cc2616caee67ca601cbddb96.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.4621966"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> zenodo.org </button> </a>

Uniform Manifold Approximation and Projection Analysis of Soccer Players

António M. Lopes, José A. Tenreiro Machado
<span title="2021-06-23">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4d3elkqvznfzho6ki7a35bt47u" style="color: black;">Entropy</a> </i> &nbsp;
Experts can recognize similarities between players and their styles, but the procedures adopted are often subjective and prone to misclassification.  ...  Players are characterized by different skills and their relevance depends on the position that they occupy on the pitch.  ...  manifold approximation and projection (UMAP) [57] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e23070793">doi:10.3390/e23070793</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/iklnxz6xyjfthc372t5g4nrvbe">fatcat:iklnxz6xyjfthc372t5g4nrvbe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210624133608/https://res.mdpi.com/d_attachment/entropy/entropy-23-00793/article_deploy/entropy-23-00793.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d2/b7/d2b7726171a1180859cbbcbb4edfbde2a6c41e70.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e23070793"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

EVALUATING UNIFORM MANIFOLD APPROXIMATION AND PROJECTION FOR DIMENSION REDUCTION AND VISUALIZATION OF POLINSAR FEATURES

S. Schmitz, U. Weidner, H. Hammer, A. Thiele
<span title="2021-06-17">2021</span> <i title="Copernicus GmbH"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/yhzu63ehjfe2dbswnsdfm5vlba" style="color: black;">ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences</a> </i> &nbsp;
In this paper, the nonlinear dimension reduction algorithm Uniform Manifold Approximation and Projection (UMAP) is investigated to visualize information contained in high dimensional feature representations  ...  The results show that UMAP exceeds the capability of PCA and LE in these regards and is competitive with t-SNE.  ...  Manifold Approximation and Projection UMAP is applied to embed the high dimensional feature representation into a low dimensional euclidian space.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5194/isprs-annals-v-1-2021-39-2021">doi:10.5194/isprs-annals-v-1-2021-39-2021</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/44xjdpwpzfc45edfw4c5anrvqi">fatcat:44xjdpwpzfc45edfw4c5anrvqi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210716144907/https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-1-2021/39/2021/isprs-annals-V-1-2021-39-2021.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/7a/f4/7af43ebd2806d2cd4187102c8207620c3749189f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5194/isprs-annals-v-1-2021-39-2021"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Uniform Manifold Approximation and Projection for Clustering Taxa through Vocalizations in a Neotropical Passerine (Rough-Legged Tyrannulet, Phyllomyias burmeisteri)

Ronald M. Parra-Hernández, Jorge I. Posada-Quintero, Orlando Acevedo-Charry, Hugo F. Posada-Quintero
<span title="2020-08-12">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hpefvtxa65c3ligdlwjcphei34" style="color: black;">Animals</a> </i> &nbsp;
In this study, we have evaluated the sensitivity of the Uniform Manifold Approximation and Projection (UMAP) technique for grouping the vocalizations of individuals of the Rough-legged Tyrannulet Phyllomyias  ...  UMAP exhibited a clearer separation of groups than previously used dimensionality-reduction techniques (i.e., principal component analysis), as it was able to effectively identify the two taxa groups.  ...  We would like to thank all recordists that shared their sounds through Macaulay Library and xeno-canto. We thank Adrian Eisen for allowing us to share his recording from Brazil.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/ani10081406">doi:10.3390/ani10081406</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32806680">pmid:32806680</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC7460062/">pmcid:PMC7460062</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5ksb2h5kyvcp5l5d6efobyjv54">fatcat:5ksb2h5kyvcp5l5d6efobyjv54</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200817184203/https://res.mdpi.com/d_attachment/animals/animals-10-01406/article_deploy/animals-10-01406-v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/7e/54/7e549b8eaf8c5c80890f15adf17d5037c4eb6c73.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/ani10081406"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7460062" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

A review of UMAP in population genetics

Alex Diaz-Papkovich, Luke Anderson-Trocmé, Simon Gravel
<span title="2020-10-14">2020</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/avi4tsqgffasfptxvmvxpsww34" style="color: black;">Journal of Human Genetics</a> </i> &nbsp;
Uniform manifold approximation and projection (UMAP) has been rapidly adopted by the population genetics community to study population structure.  ...  Here we give an overview of applications of UMAP in population genetics, provide recommendations for best practices, and offer insights on optimal uses for the technique.  ...  Here we focus on uniform manifold approximation and projection (UMAP) [4] , a method developed in 2018 that has seen widespread use across fields (e.g., single-cell genomics [5] ).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/s10038-020-00851-4">doi:10.1038/s10038-020-00851-4</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33057159">pmid:33057159</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ecsojmiqhnfjpmxj7uo2cuml5y">fatcat:ecsojmiqhnfjpmxj7uo2cuml5y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210429050450/https://www.nature.com/articles/s10038-020-00851-4.pdf?error=cookies_not_supported&amp;code=2ec25d2b-abe1-49bc-9b79-b288ac8e7edd" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/66/de/66dee91027d09ae6f45cc9dc5688cc2092bc2e86.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/s10038-020-00851-4"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Computer-assisted corpus exploration with UMAP and agglomerative clustering

James Bradbury
<span title="2020-10-19">2020</span> <i title="Zenodo"> Zenodo </i> &nbsp;
The paper will discuss the technical implementation and rationale for decisions made in the development process as well as touching on some compositional applications.  ...  Using the algorithm "Uniform Manifold Approximation and Projection" (UMAP) (McInnes, Healy, & Melville, 2018), the MFCC dimensions was reduced from 273 to 2 to support visualisation.  ...  Clustering The reduced data was then clustered to understand how corpus items were projected onto the manifold.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.4285398">doi:10.5281/zenodo.4285398</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/h64exhfvofhe5antiflfqkzfqq">fatcat:h64exhfvofhe5antiflfqkzfqq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201126223141/https://zenodo.org/record/4285398/files/CSMC__MuMe_2020_paper_6.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/82/99/8299dfe0a75be9a429ec186dfb195a10029a224a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.4285398"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> zenodo.org </button> </a>

Comparing Deep Neural Nets with UMAP Tour [article]

Mingwei Li, Carlos Scheidegger
<span title="2021-10-18">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this work, a tool, UMAP Tour, is built to visually inspect and compare internal behavior of real-world neural network models using well-aligned, instance-level representations.  ...  Using the visual tool and the similarity measure, we find concepts learned in state-of-the-art models and dissimilarities between them, such as GoogLeNet and ResNet.  ...  In particular, Uniform Manifold Approximation and Projection (UMAP) McInnes et al. (2018) can reliably preserve the global structure of high dimensional data in the low dimensional embedding.UMAP works  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2110.09431v1">arXiv:2110.09431v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/65s66gubpned3fucewkow22aji">fatcat:65s66gubpned3fucewkow22aji</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211020174049/https://arxiv.org/pdf/2110.09431v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/7d/a6/7da62b04b9dba86b54456345eba332f23ba6ff2b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2110.09431v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Improved Time-Series Clustering with UMAP dimension reduction method

Clement Pealat, Guillaume Bouleux, Vincent Cheutet
<span title="2021-01-10">2021</span> <i title="IEEE"> 2020 25th International Conference on Pattern Recognition (ICPR) </i> &nbsp;
For completeness, three different clustering algorithms and two different geometric representation for the time series (Classic Euclidean geometry, and Riemannian geometry on the Stiefel Manifold) are  ...  In this paper, a benchmark of time series clustering is created, comparing the results with and without UMAP as a pre-processing step. UMAP is used to enhance clustering results.  ...  Then, in section V, the results on the Euclidean geometry and the Stiefel manifold are presented. II. UMAP: UNIFORM MANIFOLD APPROXIMATION AND PROJECTION A.  ... 
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Sketch and Scale: Geo-distributed tSNE and UMAP [article]

Viska Wei, Nikita Ivkin, Vladimir Braverman, Alexander Szalay
<span title="2020-11-11">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Visualizing high dimensional data using tools such as t-distributed Stochastic Neighbor Embedding (tSNE) and Uniform Manifold Approximation and Projection (UMAP) became common practice for data scientists  ...  It leverages a Count Sketch data structure to compress the data on the edge nodes, aggregates the reduced size sketches on the master node, and runs vanilla tSNE or UMAP on the summary, representing the  ...  UMAP [15] is using manifold learning and topological data analysis to reduce dimensionality. It uses cross-entropy to optimize the lower dimensional representation.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2011.06103v1">arXiv:2011.06103v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4lpf7f7kvvgjxi2ok3l47rwaiq">fatcat:4lpf7f7kvvgjxi2ok3l47rwaiq</a> </span>
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Clustering with UMAP: Why and How Connectivity Matters [article]

Ayush Dalmia, Suzanna Sia
<span title="2021-12-16">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Topology based dimensionality reduction methods such as t-SNE and UMAP have seen increasing success and popularity in high-dimensional data.  ...  In this paper which focuses on UMAP, we study the effects of node connectivity (k-Nearest Neighbors vs mutual k-Nearest Neighbors) and relative neighborhood (Adjacent via Path Neighbors) on dimensionality  ...  ACKNOWLEDGEMENTS We would like to thank Desh Raj and Jinyi Yang for their feedback about the paper, and Kelly Marchisio for early discussions.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2108.05525v2">arXiv:2108.05525v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/iop7cigrqrc3xgzxbmcieguqxu">fatcat:iop7cigrqrc3xgzxbmcieguqxu</a> </span>
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