Latent Variable Models and Big Data in the Process Industries

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Clustering Mixed Data via Latent Variable Models

A model based clustering procedure for data of mixed type, termed clustMD, is developed using a latent variable model. It is proposed that a latent variable, following a mixture of Gaussian distributions, generates the observed data of mixed type. The observed data may be any combination of continuous, binary, ordinal or nominal variables. The model employs a parsimonious covariance structure f...

متن کامل

Latent Variable Models for Neural Data

iv v Acknowledgements Many thanks are due to my advisors, Richard Andersen and John Hoppeld. Richard has been tremendously supportive throughout, providing valuable advice and encouragement, even when my work has taken me outside the domains typically trodden by members of his group. Furthermore he has assembled an exceptional group of people in whose company I have worked for the last ve years...

متن کامل

Preserving Local Structure in Gaussian Process Latent Variable Models

The Gaussian Process Latent Variable Model (GPLVM) is a non-linear variant of probabilistic Principal Components Analysis (PCA). The main advantage of the GPLVM over probabilistic PCA is that it can model non-linear transformations from the latent space to the data space. An important disadvantage of the GPLVM is its focus on preserving global data structure in the latent space, whereas preserv...

متن کامل

Spike and Slab Gaussian Process Latent Variable Models

The Gaussian process latent variable model (GPLVM) is a popular approach to non-linear probabilistic dimensionality reduction. One design choice for the model is the number of latent variables. We present a spike and slab prior for the GP-LVM and propose an efficient variational inference procedure that gives a lower bound of the log marginal likelihood. The new model provides a more principled...

متن کامل

Bayesian Gaussian Process Latent Variable Models for pseudotime inference in single-cell RNA-seq data

Single-cell genomics has revolutionised modern biology while requiring the development of advanced computational and statistical methods. Advances have been made in uncovering gene expression heterogeneity, discovering new cell types and novel identification of genes and transcription factors involved in cellular processes. One such approach to the analysis is to construct pseudotime orderings ...

متن کامل

ذخیره 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: IFAC-PapersOnLine

سال: 2015

ISSN: 2405-8963

DOI: 10.1016/j.ifacol.2015.09.020