Factor analysis, probabilistic principal component analysis, variational inference, and variational autoencoder: Tutorial and survey
This is a tutorial and survey paper on factor analysis, probabilistic Principal Component
Analysis (PCA), variational inference, and Variational Autoencoder (VAE). These methods …
Analysis (PCA), variational inference, and Variational Autoencoder (VAE). These methods …
[图书][B] The EM algorithm and extensions
GJ McLachlan, T Krishnan - 2008 - books.google.com
The only single-source——now completely updated and revised——to offer a unified
treatment of the theory, methodology, and applications of the EM algorithm Complete with …
treatment of the theory, methodology, and applications of the EM algorithm Complete with …
Characterization of volatile compounds in different edible parts of steamed Chinese mitten crab (Eriocheir sinensis)
S Gu, X Wang, N Tao, N Wu - Food Research International, 2013 - Elsevier
Chinese mitten crab (Eriocheir sinensis) from Yangcheng Lake in Jiangshu province is one
of the favorite aquatic foods to Chinese consumers and possesses high economic value due …
of the favorite aquatic foods to Chinese consumers and possesses high economic value due …
Prediction of total viable counts on chilled pork using an electronic nose combined with support vector machine
D Wang, X Wang, T Liu, Y Liu - Meat science, 2012 - Elsevier
The aim of this study was to predict the total viable counts (TVC) in chilled pork using an
electronic nose (EN) together with support vector machine (SVM). EN and bacteriological …
electronic nose (EN) together with support vector machine (SVM). EN and bacteriological …
Extension of the mixture of factor analyzers model to incorporate the multivariate t-distribution
GJ McLachlan, RW Bean, LBT Jones - Computational Statistics & Data …, 2007 - Elsevier
Mixtures of factor analyzers enable model-based density estimation to be undertaken for
high-dimensional data, where the number of observations n is small relative to their …
high-dimensional data, where the number of observations n is small relative to their …
Extending mixtures of multivariate t-factor analyzers
JL Andrews, PD McNicholas - Statistics and Computing, 2011 - Springer
Abstract Model-based clustering typically involves the development of a family of mixture
models and the imposition of these models upon data. The best member of the family is then …
models and the imposition of these models upon data. The best member of the family is then …
[HTML][HTML] Sensory and chemical assessment of silver pomfret (Pampus argenteus) treated with Ginkgo biloba leaf extract treatment during storage in ice
W Lan, X Che, Q Xu, T Wang, R Du, J Xie, M Hou… - Aquaculture and …, 2018 - Elsevier
This study investigated the physical (L*, a*, b*, texture profile analyses, pH), chemical (TVB-
N, K value and TBA), microbiological, amino acid content, and flavor effects that Gingko …
N, K value and TBA), microbiological, amino acid content, and flavor effects that Gingko …
Learning graphical factor models with riemannian optimization
Graphical models and factor analysis are well-established tools in multivariate statistics.
While these models can be both linked to structures exhibited by covariance and precision …
While these models can be both linked to structures exhibited by covariance and precision …
Bayesian robust PCA of incomplete data
We present a probabilistic model for robust factor analysis and principal component analysis
in which the observation noise is modeled by Student-t distributions in order to reduce the …
in which the observation noise is modeled by Student-t distributions in order to reduce the …
Signal Modeling and Classification Using a Robust Latent Space Model Based on Distributions
SP Chatzis, DI Kosmopoulos… - IEEE Transactions on …, 2008 - ieeexplore.ieee.org
Factor analysis is a statistical covariance modeling technique based on the assumption of
normally distributed data. A mixture of factor analyzers can be hence viewed as a special …
normally distributed data. A mixture of factor analyzers can be hence viewed as a special …