Keyword

manifold learning

Description: Manifold learning is a family of machine-learning methods that represents high-dimensional data through lower-dimensional structures while preserving nonlinear relationships.

Primary topic: Face and Expression Recognition (27%)

Wikidata ID: wiki/Q7049464

OpenAlex ID: keywords/manifold-learning

Visualizing Data using t-SNE

2008 · Laurens van der Maaten, Geoffrey E. Hinton · Journal of Machine Learning Research · 33,046

Nonlinear Dimensionality Reduction by Locally Linear Embedding

2000 · Sam T. Roweis, Lawrence K. Saul · Science · 14,885

Representation Learning: A Review and New Perspectives

2013 · Y. Bengio, A. Courville, et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence · 12,970

UMAP: Uniform Manifold Approximation and Projection

2018 · Leland McInnes, John Healy, et al. · The Journal of Open Source Software · 9,751

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Inference and analysis of cell-cell communication using CellChat

2021 · Suoqin Jin, Christian F. Guerrero-Juarez, et al. · Nature Communications · 8,292

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Laplacian Eigenmaps for Dimensionality Reduction and Data Representation

2003 · Mikhail Belkin, Partha Niyogi · Neural Computation · 7,631

Extracting and composing robust features with denoising autoencoders

2008 · Pascal Vincent, Hugo Larochelle, et al. · International Conference on Machine Learning · 7,421

UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

2018 · McInnes, Leland, Healy, John, et al. · arXiv (Cornell University) · 7,083

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Dimensionality Reduction by Learning an Invariant Mapping

2006 · R. Hadsell, S. Chopra, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 5,335

Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering

2002 · Mikhail Belkin, Partha Niyogi · The MIT Press eBooks · 4,518

Geometric Deep Learning: Going beyond Euclidean data

2017 · Michael M. Bronstein, Joan Bruna, et al. · IEEE Signal Processing Magazine · 3,588

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Spectral Hashing

2008 · Yair Weiss, Antonio Torralba, et al. · neural information processing systems · 2,391

Dimensionality Reduction: A Comparative Review

2009 · Laurens van der Maaten, Eric Postma, et al. · 2,066

Super-resolution through neighbor embedding

2004 · Hong Chang, Dit-Yan Yeung, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 1,994

Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs

2017 · Federico Monti, Davide Boscaini, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 1,819

Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps

2005 · R. R. Coifman, S. Lafon, et al. · Proceedings of the National Academy of Sciences · 1,663

Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data

2003 · David L. Donoho, Carrie Grimes · Proceedings of the National Academy of Sciences · 1,662

Stochastic Neighbor Embedding

2002 · Geoffrey E. Hinton, Sam T. Roweis · 1,635

Neighborhood preserving embedding

2005 · Xiaofei He, Deng Cai, et al. · 1,610

Semi-supervised Learning by Entropy Minimization

2004 · Yves Grandvalet, Yoshua Bengio · 1,567

Nonlinear Dimensionality Reduction

2007 · John A. Lee, Michel Verleysen · Springer eBooks · 1,523

Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment

2004 · Zhenyue Zhang, Hongyuan Zha · SIAM Journal on Scientific Computing · 1,480

Contractive Auto-Encoders: Explicit Invariance During Feature Extraction

2011 · Salah Rifai, Pascal Vincent, et al. · 1,189

Unsupervised feature selection for multi-cluster data

2010 · Deng Cai, Chiyuan Zhang, et al. · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · 1,180

Diffusion maps, spectral clustering and reaction coordinates of dynamical systems

2006 · Boaz Nadler, Stéphane Lafon, et al. · Applied and Computational Harmonic Analysis · 989

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Works count: 10,130

Citation count: 277,300