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Clustering high-dimensional data, such as images or biological measurements, is a long-standingproblem and has been studied extensively.
Computer programs for hierarchical polythetic classification ("similarity analysis")
Lance Godfrey N. and Williams William T · 1966
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Neural Networks for Pattern Recognition,
Christopher M. Bishop · 1995
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Lipoprotein lipase (LpL) on the surface of cardiomyocytes increases lipid uptake and produces a cardiomyopathy
Hiroaki Yagyu, Guangping Chen, Masayoshi Yokoyama, Kumiko Hirata, Ayanna Augustus, Yuko Kako, Toru Seo, Yunying Hu, E. Peer Lutz, Martin Merkel, André Bensadoun, Shunichi Homma, Ira J. Goldberg · 2003
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Learning a similarity metric discriminatively, with application to face verification
S. Chopra, R. Hadsell, Y. LeCun · 2005
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Pattern Recognition and Machine Learning
Christopher M. Bishop · 2006
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A Kernel Method for the Two-Sample Problem
Arthur Gretton, Karsten Borgwardt, Malte J. Rasch, Bernhard Scholkopf, Alexander J. Smola · 2008
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Visualizing Data using t-SNE
Laurens van der Maaten, Geoffrey Hinton · 2008
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Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE
Peng Qiu, Erin F. Simonds, Sean C. Bendall, Kenneth D. Gibbs Jr., Robert V. Bruggner, Michael D. Linderman, Karen Sachs, Garry P. Nolan, Sylvia K. Plevritis · 2011
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Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators
Bernd Bodenmiller, Eli R. Zunder, Rachel Finck, Tiffany J. Chen, Erica S. Savig, Robert V. Bruggner, Erin F. Simonds, Sean C. Bendall, Karen Sachs, Peter O. Krutzik, Garry P. Nolan · 2012
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Critical assessment of automated flow cytometry data analysis techniques
N. Aghaeepour, G. Finak, FlowCAP Consortium, DREAM Consortium, H. Hoos, TR. Mosmann, R. Brinkman, R. Gottardo, Rh. Scheuermann · 2013
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Application of Mass Cytometry (CyTOF) for Functional and Phenotypic Analysis of Natural Killer Cells
Alexander W. Kay, Dara M. Strauss-Albee, Catherine A. Blish · 2013
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Auto-Encoding Variational Bayes
D. P. Kingma, M. Welling · 2014
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Lipoprotein lipase activity is required for cardiac lipid droplet production
Chad M. Trent, Shuiqing Yu, Yunying Hu, Nathan Skoller, Lesley A. Huggins, Shunichi Homma, Ira J. Goldberg · 2014
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A comparative encyclopedia of DNA elements in the mouse genome
Feng Yue et al · 2014
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FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data
Sofie Van Gassen, Britt Callebaut, Mary J. Van Helden, Bart N. Lambrecht, Piet Demeester, Tom Dhaene, Yvan Saeys · 2015
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Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis
Jacob H. Levine, Erin F. Simonds, Sean C. Bendall, Kara L. Davis, El-ad D. Amir, Michelle D. Tadmor, Oren Litvin, Harris G. Fienberg, Astraea Jager, Eli R. Zunder, Rachel Finck, Amanda L. Gedman, Ina Radtke, James R. Downing, Dana Pe’er, Garry P. Nolan · 2015
Cited alongside, same era.
Comparison of clustering methods for high-dimensional single-cell flow and mass cytometry data
Lukas M. Weber, Mark D. Robinson · 2016
Cited alongside, same era.
Automated Mapping of Phenotype Space with Single-Cell Data
Nikolay Samusik, Zinaida Good, Matthew H. Spitzer, Kara L. Davis, Garry P. Nolan · 2016
Cited alongside, same era.
Clustering Techniques and the Similarity Measures used in Clustering: A Survey
Jasmine Irani, Nitin Pise, Madhura Phatak · 2016
Cited alongside, same era.
Unsupervised deep embedding for clustering analysis
J. Xie, R. Girshick, A. Farhadi · 2016
Cited alongside, same era.
Neural clustering: Concatenating layers for better projections
S. Saito, R. T. Tan · 2017
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Unsupervised multi-manifold clustering by learning deep representation
D. Chen, J. Lv, Z. Yi · 2017
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Learning discrete representations via information maximizing self augmented training
W. Hu, T. Miyato, S. Tokui, E. Matsumoto, M. Sugiyama · 2017
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A Comprehensive Mouse Transcriptomic BodyMap across 17 Tissues by RNA-seq
Li, B., Qing, T., Zhu, J. et al · 2017
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hdbscan: Hierarchical density based clustering In: Journal of Open Source Software
L. McInnes, J. Healy, S. Astels · 2017
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Clustering with Deep Learning: Taxonomy and New Methods
Elie Aljalbout, Vladimir Golkov, Yawar Siddiqui, Maximilian Strobel, Daniel Cremers · 2018
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Learning a task-specific deep architecture for clustering
Z. Wang, S. Chang, J. Zhou, M. Wang, T. S. Huang · 2016
Cited alongside, same era.
Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering
Zhuxi Jiang, Yin Zheng, Huachun Tan, Bangsheng Tang, Hanning Zhou · 2017
Cited alongside, same era.
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layers
Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le1, Geoffrey Hinton, Jeff Dean · 2017
Cited alongside, same era.
Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization
Kamran Ghasedi Dizaji, Amirhossein Herandi, Cheng Deng, Weidong Cai, Heng Huang · 2017
Cited alongside, same era.
Sensitive detection of rare disease-associated cell subsets via representation learning
Eirini Arvaniti, Manfred Claassen · 2017
Cited alongside, same era.
Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering
Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos, Mingyi Hong · 2017
Cited alongside, same era.
Deep Unsupervised Clustering Using Mixture of Autoencoders
Dejiao Zhang, Yifan Sun, Brian Eriksson, Laura Balzano · 2017
Cited alongside, same era.
Later among the works it cites.
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
Leland McInnes, John Healy, James Melville · 2018
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A Survey of Clustering With Deep Learning: From the Perspective of Network Architecture
Erxue Min, Xifeng Guo, Qiang Liu, Gen Zhang, Jianjing Cui, Jun Long · 2018
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SpectralNet: Spectral Clustering using Deep Neural Networks
Uri Shaham, Kelly Stanton, Henry Li, Boaz Nadler, Ronen Basri, Yuval Kluger · 2018
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Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris
The Tabula Muris Consortium., Overall coordination., Schaum, N. et al · 2018
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Generative models and model criticism via optimized maximum mean discrepancy
Dougal J. Sutherland, Hsiao-Yu Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alex Smola, Arthur Gretton · 2019
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SOM-VAE: Interpretable Discrete Representation Learning on Time Series
Vincent Fortuin, Matthias Hüser, Francesco Locatello, Heiko Strathmann, Gunnar Rätsch · 2019
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fuzzy-c-means: An implementation of Fuzzy C C -means clustering algorithm
Madson Luiz Dantas Dias · 2019
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Dimension Reduction and Clustering Models for Single-Cell RNA Sequencing Data: A Comparative Study
Chao Feng, Shufen Liu, Hao Zhang, Renchu Guan, Dan Li, Fengfeng Zhou, Yanchun Liang, Xiaoyue Feng · 2020
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