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UMAP (Uniform Manifold Approximation and Projection) is a novel manifold learning technique for dimension reduction.
Analysis of a complex of statistical variables into principal components
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Fuzzy set theory and topos theory
Michael Barr · 1986
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Simplicial objects in algebraic topology
J Peter May · 1992
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Columbia object image library (coil-20
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object image library (coil-100
Sameer A. Nene, Shree K. Nayar, and Hiroshi Murase · 1996
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Pen-based recognition of handwritten digits data set. university of california, irvine
E Alpaydin and Fevzi Alimoglu · 1998
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Mapping a manifold of perceptual observations
Joshua B. Tenenbaum · 1998
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A global geometric framework for nonlinear dimensionality reduction
Joshua B Tenenbaum, Vin De Silva, and John C Langford · 2000
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Laplacian eigenmaps and spectral techniques for embedding and clustering
Mikhail Belkin and Partha Niyogi · 2002
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Laplacian eigenmaps for dimensionality reduction and data representation
Mikhail Belkin and Partha Niyogi · 2003
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Diffusion maps
Ronald R Coifman and Stéphane Lafon · 2006
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Distance metric learning: A comprehensive survey
Liu Yang and Rong Jin · 2006
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Graph laplacians and their convergence on random neighborhood graphs
Matthias Hein, Jean-Yves Audibert, and Ulrike von Luxburg · 2007
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Visualizing data using t-sne
Laurens van der Maaten and Geoffrey Hinton · 2008
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Visualizing data using t-SNE
Laurens van der Maaten and Geoffrey Hinton · 2008
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Simplicial homotopy theory
Paul G Goerss and John F Jardine · 2009
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Efficient k-nearest neighbor graph construction for generic similarity measures
Wei Dong, Charikar Moses, and Kai Li · 2011
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Shift-invariant similarities circumvent distance concentration in stochastic neighbor embedding and variants
John A Lee and Michel Verleysen · 2011
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A leisurely introduction to simplicial sets
Emily Riehl · 2011
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Survey article: an elementary illustrated introduction to simplicial sets
Greg Friedman et al · 2012
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Flowrepository: A resource of annotated flow cytometry datasets associated with peer-reviewed publications
Josef Spidlen, Karin Breuer, Chad Rosenberg, Nikesh Kotecha, and Ryan R Brinkman · 2012
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Metric realization of fuzzy simplicial sets
David I Spivak · 2012
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A survey on metric learning for feature vectors and structured data
Aurélien Bellet, Amaury Habrard, and Marc Sebban · 2013
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Omip-018: Chemokine receptor expression on human t helper cells
Evaluation of umap as an alternative to t-sne for single-cell data
Etienne Becht, Charles-Antoine Dutertre, Immanuel W.H. Kwok, Lai Guan Ng, Florent Ginhoux, and Evan W Newell · 2018
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Comprehensive analysis of retinal development at single cell resolution identifies nfi factors as essential for mitotic exit and specification of late-born cells
Brian Clark, Genevieve Stein-O’Brien, Fion Shiau, Gabrielle Cannon, Emily Davis, Thomas Sherman, Fatemeh Rajaii, Rebecca James-Esposito, Richard Gronostajski, Elana Fertig, et al · 2018
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Revealing multi-scale population structure in large cohorts
Alex Diaz-Papkovich, Luke Anderson-Trocme, and Simon Gravel · 2018
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(self-attentive) autoencoder-based universal language representation for machine translation
Carlos Escolano, Marta R Costa-jussà, and José AR Fonollosa · 2018
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Data-driven design: Exploring new structural forms using machine learning and graphic statics
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Tess Brodie, Elena Brenna, and Federica Sallusto · 2013
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API design for machine learning software: experiences from the scikit-learn project
Lars Buitinck, Gilles Louppe, Mathieu Blondel, Fabian Pedregosa, Andreas Mueller, Olivier Grisel, Vlad Niculae, Peter Prettenhofer, Alexandre Gramfort, Jaques Grobler, Robert Layton, Jake VanderPlas, Arnaud Joly, Brian Holt, and Gaël Varoquaux · 2013
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Classifying clustering schemes
Gunnar Carlsson and Facundo Mémoli · 2013
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UCI machine learning repository, 2013
M. Lichman · 2013
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Categories for the working mathematician
Saunders Mac Lane · 2013
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013
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Accelerating t-sne using tree-based algorithms
Laurens van der Maaten · 2014
Cited alongside, same era.
Lukas Fuhrimann, Vahid Moosavi, Patrick Ole Ohlbrock, and Pierluigi Dacunto · 2018
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Gaussian mixture models with wasserstein distance
Benoit Gaujac, Ilya Feige, and David Barber · 2018
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Human bone marrow assessment by single cell rna sequencing, mass cytometry and flow cytometry
Karolyn A Oetjen, Katherine E Lindblad, Meghali Goswami, Gege Gui, Pradeep K Dagur, Catherine Lai, Laura W Dillon, J Philip McCoy, and Christopher S Hourigan · 2018
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Fast batch alignment of single cell transcriptomes unifies multiple mouse cell atlases into an integrated landscape
Jong-Eun Park, Krzysztof Polanski, Kerstin Meyer, and Sarah A Teichmann · 2018
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Simplicial autoencoders
Jose Daniel Gallego Posada · 2018
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What do numbers look like?
John Williamson · 2018
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Dimensionality reduction for visualizing single-cell data using umap
Etienne Becht, Leland McInnes, John Healy, Charles-Antoine Dutertre, Immanuel WH Kwok, Lai Guan Ng, Florent Ginhoux, and Evan W Newell · 2019
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The single-cell transcriptional landscape of mammalian organogenesis
Junyue Cao, Malte Spielmann, Xiaojie Qiu, Xingfan Huang, Daniel M Ibrahim, Andrew J Hill, Fan Zhang, Stefan Mundlos, Lena Christiansen, Frank J Steemers, et al · 2019
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Activation atlas
Shan Carter, Zan Armstrong, Ludwig Schubert, Ian Johnson, and Chris Olah · 2019
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Deep learning multidimensional projections
Mateus Espadoto, Nina ST Hirata, and Alexandru C Telea · 2019
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The art of using t-sne for single-cell transcriptomics
Dmitry Kobak and Philipp Berens · 2019
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Umap does not preserve global structure any better than t-sne when using the same initialization
Dmitry Kobak and George C Linderman · 2019
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Manifold learning of four-dimensional scanning transmission electron microscopy
Xin Li, Ondrej E Dyck, Mark P Oxley, Andrew R Lupini, Leland McInnes, John Healy, Stephen Jesse, and Sergei V Kalinin · 2019
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Clustering with t-sne, provably
George C Linderman and Stefan Steinerberger · 2019
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Visualizing structure and transitions in high-dimensional biological data
Kevin R Moon, David van Dijk, Zheng Wang, Scott Gigante, Daniel B Burkhardt, William S Chen, Kristina Yim, Antonia van den Elzen, Matthew J Hirn, Ronald R Coifman, et al · 2019
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Comparison between umap and t-sne for multiplex-immunofluorescence derived single-cell data from tissue sections
Duoduo Wu, Joe Yeong, Grace Tan, Marion Chevrier, Josh Loh, Tony Lim, and Jinmiao Chen · 2019
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