Results 11 to 20 of about 186,339 (256)
Latent Variable Autoencoder [PDF]
IEEE Access, 2019 Learning to discover hidden variables from unlabeled data is an important task. Traditional generative methods model the generation process of the observed variables as well as the hidden variables. However, tractable inference and learning on these models requires strong conditional independence assumptions being made among observed and hidden ...
Wenjuan Han, Ge Wang 0005, Kewei Tu
openaire +2 more sources
A review of dynamic network models with latent variables [PDF]
Statistics Surveys, 2018 Lingzhou Xue, Xiaoyue Niu, Bomin Kim
exaly +2 more sources
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
doaj +1 more source
Multimodal latent variable analysis [PDF]
Signal Processing, 2018 Consider a set of multiple, multimodal sensors capturing a complex system or a physical phenomenon of interest. Our primary goal is to distinguish the underlying sources of variability manifested in the measured data. The first step in our analysis is to find the common source of variability present in all sensor measurements.
Vardan Papyan, Ronen Talmon
openaire +2 more sources
A constrained latent variable model [PDF]
2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012 Latent variable models provide valuable compact representations for learning and inference in many computer vision tasks. However, most existing models cannot directly encode prior knowledge about the specific problem at hand. In this paper, we introduce a constrained latent variable model whose generated output inherently accounts for such knowledge ...
Varol, Aydin +3 more
openaire +3 more sources
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
doaj +1 more source
Latent variable modeling for the microbiome [PDF]
Biostatistics, 2018 SummaryThe human microbiome is a complex ecological system, and describing its structure and function under different environmental conditions is important from both basic scientific and medical perspectives. Viewed through a biostatistical lens, many microbiome analysis goals can be formulated as latent variable modeling problems.
Sankaran, Kris, Holmes, Susan P.
openaire +3 more sources
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
doaj +1 more source
Factorisation-Based Image Labelling
Frontiers in Neuroscience, 2022 Segmentation of brain magnetic resonance images (MRI) into anatomical regions is a useful task in neuroimaging. Manual annotation is time consuming and expensive, so having a fully automated and general purpose brain segmentation algorithm is highly ...
Yu Yan +6 more
doaj +1 more source
VARIABEL LATEN SEBAGAI MODERATOR DAN MEDIATOR DALAM HUBUNGAN KAUSAL
E-Jurnal Matematika, 2013 Latent variables are variables that can not be measured directly. In analysis of causal relationship involving three latent variables, one latent variable can be a moderator or mediator variables. Goodness of Fit moderation and mediation model of latent
I KOMANG GEDE ANTARA +2 more
doaj +1 more source