Variational Bayes and the Principal Component Analysis Coupled With Bayesian Regulation Backpropagation Network to Retrieve Total Precipitable Water (TPW) From GCOM-W1/AMSR2
نویسندگان
چکیده
منابع مشابه
A Variational Bayes Approach to Robust Principal Component Analysis
We solve the Robust Principal Component Analysis problem: decomposing an observed matrix into a low-rank matrix plus a sparse matrix. Unlike alternative methods that approximate this l0 objective with an l1 objective and solve a convex optimization problem, we develop a corresponding generative model and solve a statistical inference problem. The main advantages of this approach is its ability ...
متن کاملLearning Bayesian Network Structure Using Genetic Algorithm with Consideration of the Node Ordering via Principal Component Analysis
‎The most challenging task in dealing with Bayesian networks is learning their structure‎. ‎Two classical approaches are often used for learning Bayesian network structure;‎ ‎Constraint-Based method and Score-and-Search-Based one‎. ‎But neither the first nor the second one are completely satisfactory‎. ‎Therefore the heuristic search such as Genetic Alg...
متن کاملBayesian Principal Component Analysis
Principal component analysis (PCA) is a dimensionality reduction modeling technique that transforms a set of process variables by rotating their axes of representation. Maximum Likelihood PCA (MLPCA) is an extension that accounts for different noise contributions in each variable. Neither PCA nor its extensions utilize external information about the model or data such as the range or distributi...
متن کاملOn Bayesian principal component analysis
A complete Bayesian framework for Principal Component Analysis (PCA) is proposed in this paper. Previous model-based approaches to PCA were usually based on a factor analysis model with isotropic Gaussian noise. This model does not impose orthogonality constraints, contrary to PCA. In this paper, we propose a new model with orthogonality restrictions, and develop its approximate Bayesian soluti...
متن کاملVariational Bayesian Independent Component Analysis
Blind separation of signals through the info-max algorithm may be viewed as maximum likelihood learning in a latent variable model. In this paper we present an alternative approach to maximum likelihood learning in these models, namely Bayesian inference. It has already been shown how Bayesian inference can be applied to determine latent dimensionality in principal component analysis models (Bi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
سال: 2015
ISSN: 1939-1404,2151-1535
DOI: 10.1109/jstars.2015.2447532