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Diffusion map

Known as: Diffusion maps 
Diffusion maps is a dimensionality reduction or feature extraction algorithm introduced by R. R. Coifman and S. Lafon. It computes a family of… 
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Related topics

Related topics

5 relations
Dimensionality reductionFeature extractionMarkov chainNonlinear dimensionality reduction

Papers overview

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2019
2019
Design optimization of a scramjet under uncertainty using probabilistic learning on manifolds
Highly Cited
2018
Highly Cited
2018
Diffusion Scattering Transforms on Graphs
Stability is a key aspect of data analysis. In many applications, the natural notion of stability is geometric, as illustrated… 
2017
2017
Probabilistic nonconvex constrained optimization with fixed number of function evaluations
A methodology is proposed for the efficient solution of probabilistic nonconvex constrained optimization problems with uncertain… 
2016
2016
Manifold learning for the emulation of spatial fields from computational models
Highly Cited
2015
Highly Cited
2015
Online anomaly detection using dimensionality reduction techniques for HTTP log analysis
Highly Cited
2015
Highly Cited
2015
Parsimonious Representation of Nonlinear Dynamical Systems Through Manifold Learning: A Chemotaxis Case Study
Highly Cited
2015
Highly Cited
2015
Classification of healthcare data using genetic fuzzy logic system and wavelets
2015
2015
Forecasting turbulent modes with nonparametric diffusion models: Learning from noisy data
2010
2010
A diffusion framework for detection of moving vehicles
Highly Cited
2010
Highly Cited
2010
Adaptive local dissimilarity measures for discriminative dimension reduction of labeled data
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