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… (More)
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Highly Cited
2015
Highly Cited
2015
MOTIVATION Single-cell technologies have recently gained popularity in cellular differentiation studies regarding their ability… (More)
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2013
2013
It has long been known that the method of time-delay embedding can be used to reconstruct nonlinear dynamics from time series… (More)
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2013
2013
We propose a multiscale approach to anomaly detection in images, combining spectral dimensionality reduction and a nearest… (More)
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2012
2012
Graph Laplacians and related nonlinear mappings into low dimensional spaces have been shown to be powerful tools for organizing… (More)
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2012
2012
Diffusion maps are among the most powerful Machine Learning tools to analyze and work with complex high-dimensional datasets… (More)
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Highly Cited
2007
Highly Cited
2007
We introduce intrinsic, nonlinearly invariant, parameterizations of empirical data, generated by a nonlinear transformation of… (More)
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Highly Cited
2007
Highly Cited
2007
Data fusion and multi-cue data matching are fundamental tasks of high-dimensional data analysis. In this paper, we apply the… (More)
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Highly Cited
2006
Highly Cited
2006
In this paper, we provide a framework based upon diffusion processes for finding meaningful geometric descriptions of data sets… (More)
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Highly Cited
2005
Highly Cited
2005
A central problem in data analysis is the low dimensional representation of high dimensional data, and the concise description of… (More)
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Highly Cited
2002
Highly Cited
2002
This paper presents a new procedure to estimate the diffusion tensor from a sequence of diffusion-weighted images. The first step… (More)
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