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Variational message passing
Known as:
Message passing (disambiguation)
, Passing
Variational message passing (VMP) is an approximate inference technique for continuous- or discrete-valued Bayesian networks, with conjugate…
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Related topics
Related topics
3 relations
Latent Dirichlet allocation
Markov blanket
One-shot learning
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2016
2016
HEVA: cooperative localization using a combined non-parametric belief propagation and variational message passing approach
Panagiotis Agis Oikonomou Filandras
,
Kai-Kit Wong
Journal of Communications and Networks
2016
Corpus ID: 18000755
This paper proposes a novel cooperative localization method for distributed wireless networks in 3-dimensional (3D) global…
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2016
2016
Receiver Architectures for MIMO-OFDM Based on a Combined VMP-SP Algorithm
Carles Navarro
2016
Corpus ID: 61528533
Iterative information processing, either based on heurist ics or analytical frameworks, has been shown to be a very powerful tool…
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2015
2015
Variational Bayesian inference in Python Year : 2015 Version :
Jaakko Luttinen
2015
Corpus ID: 265039208
BayesPy is an open-source Python software package for performing variational Bayesian inference. It is based on the variational…
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2014
2014
Consensus Message Passing for Layered Graphical Models
V. Jampani
,
S. Eslami
,
Daniel Tarlow
,
Pushmeet Kohli
,
J. Winn
International Conference on Artificial…
2014
Corpus ID: 14860127
Generative models provide a powerful framework for probabilistic reasoning. However, in many domains their use has been hampered…
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2014
2014
Distributed Inference : Combining Variational Inference With Distributed Computing
Chris Calabrese
2014
Corpus ID: 17476267
The study of inference techniques and their use for solving complicated models has taken off in recent years, but as the models…
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2013
2013
Variational message-passing: extension to continuous variables and applications in multi-target tracking
A. Ihler
,
Padhraic Smyth
,
A. Frank
2013
Corpus ID: 61207968
This dissertation focuses on both the application and development of variational inference algorithms for probabilistic graphical…
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2008
2008
Variational Transform Invariant Mixture of Probabilistic PCA
Jilin Tu
,
Yun Fu
,
Alexandar Ivanovic
,
Thomas S. Huang
,
Li Fei-Fei
IEEE Workshop on Applications of Computer Vision
2008
Corpus ID: 16580441
In many video-based object recognition applications, the object appearances are acquired by visual tracking or detection and are…
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2006
2006
Distributed Bayes Blocks for Variational Bayesian Learning
Antti Honkela
2006
Corpus ID: 12956507
In this work preliminary results on a distributed version of Bayes Blocks software library [1, 4] are presented. Bayes Blocks is…
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2006
2006
Variational Shift Invariant Probabilistic PCA for Face Recognition
Jilin Tu
,
Aleksandar Ivanovic
,
Xun Xu
,
Li Fei-Fei
,
Thomas S. Huang
International Conference on Pattern Recognition
2006
Corpus ID: 2809427
While PCA learns a subspace that captures the variations of the data, it assumes the collected data is well pre-processed (i.e…
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2005
2005
Explorer Variational Message Passing
J. Winn
2005
Corpus ID: 85555823
Bayesian inference is now widely established as one of the pr inci al foundations for machine learning. In practice, exact…
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