Results 11 to 20 of about 729,681 (329)
Pyramid-VAE-GAN: Transferring hierarchical latent variables for image inpainting
Computational Visual Media, 2023 Significant progress has been made in image inpainting methods in recent years. However, they are incapable of producing inpainting results with reasonable structures, rich detail, and sharpness at the same time. In this paper, we propose the Pyramid-VAE-
Huiyuan Tian +4 more
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Dynamic system multivariate calibration based on multirate sampling data [PDF]
Modeling, Identification and Control, 2001 The statistical principal component regression (PCR) and chemometric partial least squares regression (PLSR) algorithms based on latent variables (LV) modeling are effective tools for handling ill-conditioned regression data.
Rolf Ergon, Maths Halstensen
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A didactically motivated PLS prediction algorithm [PDF]
Modeling, Identification and Control, 2001 The intention of this paper is to develop an easily understood PLS prediction algorithm, especially for the control community. The algorithm is based on an explicit latent variables model, and is otherwise a combination of the previously published ...
Rolf Ergon, Kim H. Esbensen
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International Journal of Transportation Science and Technology, 2023 This paper aims to estimate segments of latent variables associated with mode choice. The estimates of latent segmentation is obtained through Structural Equation Modelling (SEM) approach.
Bharvi A. Shah, L.B. Zala, Nipa A. Desai
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Research on neural processes with multiple latent variables
IET Image Processing, 2023 Neural Process (NP) fully combines the advantages of neural network and Gaussian Process (GP) to provide an efficient method for solving regression problems. Nonetheless, limited by the dimensionality of the latent variable, NP has difficulty fitting the
Xiao‐Han Yu +4 more
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Restricted maximum-likelihood method for learning latent variance components in gene expression data with known and unknown confounders [PDF]
, 2021 Random effect models are popular statistical models for detecting and correcting spurious sample correlations due to hidden confounders in genome-wide gene expression data.
Malik, Muhammad Ammar, Michoel, Tom
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Method for estimating disease risk from microbiome data using structural equation modeling
Frontiers in Microbiology, 2023 The relationship between the human gut microbiota and disease is of increasing scientific interest. Previous investigations have focused on the differences in intestinal bacterial abundance between control and affected groups to identify disease ...
Hidetaka Tokuno +6 more
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Latent class instrumental variables and the monotonicity assumption
Emerging Themes in Epidemiology, 2020 A key aspect of the article by Lousdal on instrumental variables was a discussion of the monotonicity assumption. However, there was no mention of the history of the development of this assumption.
Stuart G. Baker
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Proper elimination of latent variables [PDF]
, 1997 We consider behaviors in which we distinguish two types of variables, manifest variables, the variables that are of interest to the user and latent variables, the variables that are introduced to obtain a first representation.
Polderman, Jan Willem
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Assessing the Relationship between Sea Turtle Strandings and Anthropogenic Impacts in Taiwan
Journal of Marine Science and Engineering, 2023 Data acquired from stranded sea turtles can provide awareness of human activities that adversely affect sea turtle populations. We assessed strandings of five sea turtle species between 2017 and 2021. This study utilizes principal component analysis (PCA)
Wei-Rung Chou, Po-Yu Wu, Tsung-Hsien Li
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