Variational method (quantum mechanics)

In quantum mechanics, the variational method is one way of finding approximations to the lowest energy eigenstate or ground state, and some excited… (More)
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Highly Cited
2014
Highly Cited
2014
Variational inference has become a widely used method to approximate posteriors in complex latent variables models. However… (More)
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Highly Cited
2009
Highly Cited
2009
Sparse Gaussian process methods that use inducing variables require the selection of the inducing inputs and the kernel… (More)
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Highly Cited
2007
Highly Cited
2007
A long-term global atmospheric reanalysis, named ‘‘Japanese 25-year Reanalysis (JRA-25)’’ was completed using the Japan… (More)
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Highly Cited
2005
Highly Cited
2005
Bayesian inference is now widely established as one of the pr inci al foundations for machine learning. In practice, exact… (More)
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Highly Cited
2004
Highly Cited
2004
Sparse Bayesian learning (SBL) and specifically relevance vector machines have received much attention in the machine learning… (More)
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Highly Cited
2003
Highly Cited
2003
We present a class of generalized mean field (GMF) algorithms for approximate inference in exponential family graphical models… (More)
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Highly Cited
2000
Highly Cited
2000
Using a variational method, we exhibit a surprisingly simple periodic orbit for the newtonian problem of three equal masses in… (More)
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Highly Cited
1997
Highly Cited
1997
This paper is concerned with a classical denoising and deblurring problem in image recovery. Our approach is based on a… (More)
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Highly Cited
1994
Highly Cited
1994
The variational method has been introduced by Kass et al. (1987) in the field of object contour modeling, as an alternative to… (More)
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Highly Cited
1992
Highly Cited
1992
A novel discrete variable representation (DVR) is introduced for use as the L 2 basis of the Smatrix version of the Kohn… (More)
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