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Coil sensitivity encoding for fast MRI. In:
 Proceedings of the ISMRM 6th Annual Meeting,
, 1998
"... New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementa ..."
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Cited by 193 (3 self)
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indicates the transposed complex conjugate, and ⌿ is the n C ϫ n C receiver noise matrix (see Appendix A), which describes the levels and correlation of noise in the receiver channels. Using the unfolding matrix, signal separation is performed by where the resulting vector v has length n P and lists
Conjugate bayesian analysis of the gaussian distribution
, 2007
"... The Gaussian or normal distribution is one of the most widely used in statistics. Estimating its parameters using ..."
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Cited by 23 (1 self)
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The Gaussian or normal distribution is one of the most widely used in statistics. Estimating its parameters using
Variational message passing
 JOURNAL OF MACHINE LEARNING RESEARCH
, 2005
"... This paper presents Variational Message Passing (VMP), a general purpose algorithm for applying variational inference to a Bayesian Network. Like belief propagation, Variational Message Passing proceeds by passing messages between nodes in the graph and updating posterior beliefs using local operati ..."
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Cited by 134 (10 self)
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, by introducing additional variational parameters, VMP can be applied to models containing nonconjugate distributions. The VMP framework also allows the lower bound to be evaluated, and this can be used both for model comparison and for detection of convergence. Variational Message Passing has been implemented
A CORRELATED TOPIC MODEL OF SCIENCE
, 2007
"... Topic models, such as latent Dirichlet allocation (LDA), can be useful tools for the statistical analysis of document collections and other discrete data. The LDA model assumes that the words of each document arise from a mixture of topics, each of which is a distribution over the vocabulary. A limi ..."
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Cited by 156 (10 self)
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Topic models, such as latent Dirichlet allocation (LDA), can be useful tools for the statistical analysis of document collections and other discrete data. The LDA model assumes that the words of each document arise from a mixture of topics, each of which is a distribution over the vocabulary. A
Conjugated Polymers
, 1997
"... Reproduction in while in part is permitted for any purpose of the United States Government This document has been approved for public release and sale; its distribution is unlimited. This statement should also appear in item ten (10) of the Document Control Data DD Form 1473. Copies of the form avai ..."
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Reproduction in while in part is permitted for any purpose of the United States Government This document has been approved for public release and sale; its distribution is unlimited. This statement should also appear in item ten (10) of the Document Control Data DD Form 1473. Copies of the form
Invariant Conjugate Analysis for Exponential Families
"... Abstract. There are several ways to parameterize a distribution belonging to an exponential family, each one leading to a different Bayesian analysis of the data under standard conjugate priors. To overcome this problem, we propose a new class of conjugate priors which is invariant with respect to s ..."
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Cited by 2 (1 self)
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Abstract. There are several ways to parameterize a distribution belonging to an exponential family, each one leading to a different Bayesian analysis of the data under standard conjugate priors. To overcome this problem, we propose a new class of conjugate priors which is invariant with respect
SUPERLINEAR CONVERGENCE OF CONJUGATE GRADIENTS
, 2001
"... We give a theoretical explanation for superlinear convergence behavior observed while solving large symmetric systems of equations using the conjugate gradient method or other Krylov subspace methods. We present a new bound on the relative error after n iterations. This bound is valid in an asympto ..."
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Cited by 24 (6 self)
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We give a theoretical explanation for superlinear convergence behavior observed while solving large symmetric systems of equations using the conjugate gradient method or other Krylov subspace methods. We present a new bound on the relative error after n iterations. This bound is valid
A Compendium of Conjugate Priors
, 1997
"... This report reviews conjugate priors and priors closed under sampling for a variety of data generating processes where the prior distributions are univariate, bivariate, and multivariate. The effects of transformations on conjugate prior relationships are considered and cases where conjugate prior r ..."
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Cited by 17 (0 self)
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This report reviews conjugate priors and priors closed under sampling for a variety of data generating processes where the prior distributions are univariate, bivariate, and multivariate. The effects of transformations on conjugate prior relationships are considered and cases where conjugate prior
The Multigrid Preconditioned Conjugate Gradient Method
, 1993
"... This paper considers an efficient preconditioner and proposes a multigrid preconditioned conjugate gradient method (MGCG method) which is the conjugate gradient method with the multigrid method as a preconditioner. The combination of the multigrid method and the conjugate gradient method was already ..."
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Cited by 31 (2 self)
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' distribution of the preconditioned matrix. In Sections 2 and 3, the preconditioned conjugate gradient method and the multigrid method which are the basis of this paper are briefly explained. Section 4 discusses the requirements of the valid twogrid preconditioner for the conjugate gradient method
the Conjugate Gradient method 3
, 1994
"... The use of a tree topology on a distributed memory system for the implementation of ..."
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The use of a tree topology on a distributed memory system for the implementation of
Results 11  20
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