Crystallized and fluid intelligence are predicted by microstructure of specific white‐matter tracts
Sign Up to like & getrecommendations! Published in 2020 at "Human Brain Mapping"
DOI: 10.1002/hbm.24848
Abstract: Studies of the neural basis of intelligence have focused on comparing brain imaging variables with global scales instead of the cognitive domains integrating these scales or quotients. Here, the relation between mean tract‐based fractional anisotropy… read more here.
Keywords: intelligence; mtbfa; fluid intelligence; latent variables ... See more keywords
The probabilistic discriminative time-series model with latent variables and its application to industrial chemical process modeling
Sign Up to like & getrecommendations! Published in 2021 at "Chemical Engineering Journal"
DOI: 10.1016/j.cej.2021.130298
Abstract: Abstract Probabilistic models with latent variables have caught extensive attention in industrial modeling since they can predict the distribution of variables of interest. However, the traditional probabilistic model is a generative model in which some… read more here.
Keywords: process; model; chemical process; latent variables ... See more keywords
Examination of the Association Between Latent Variables for Social Determinants of Health and Blood Pressure Control in Immigrants using Structural Equation Modeling.
Sign Up to like & getrecommendations! Published in 2020 at "Journal of the National Medical Association"
DOI: 10.1016/j.jnma.2020.02.004
Abstract: BACKGROUND Hypertension is responsible for about 12.8% of deaths around the world. Immigrants' risk of developing hypertension increases with length of residency. There is limited work on the role of social determinants of health and… read more here.
Keywords: determinants health; blood pressure; blood; latent variables ... See more keywords
Graphical Model Selection for Gaussian Conditional Random Fields in the Presence of Latent Variables
Sign Up to like & getrecommendations! Published in 2019 at "Journal of the American Statistical Association"
DOI: 10.1080/01621459.2018.1434531
Abstract: ABSTRACT We consider the problem of learning a conditional Gaussian graphical model in the presence of latent variables. Building on recent advances in this field, we suggest a method that decomposes the parameters of a… read more here.
Keywords: presence latent; model; graphical model; model selection ... See more keywords
Latent variables underlying the memory beliefs of Chartered Clinical Psychologists, Hypnotherapists and undergraduate students
Sign Up to like & getrecommendations! Published in 2017 at "Memory"
DOI: 10.1080/09658211.2015.1125927
Abstract: ABSTRACT In courts in the United Kingdom, understanding of memory phenomena is often assumed to be a matter of common sense. To test this assumption 337 UK respondents, consisting of 125 Chartered Clinical Psychologists, 88… read more here.
Keywords: variables underlying; chartered clinical; clinical psychologists; underlying memory ... See more keywords
Data-driven discovery of partial differential equation models with latent variables
Sign Up to like & getrecommendations! Published in 2019 at "Physical review. E"
DOI: 10.1103/physreve.100.022219
Abstract: In spatially extended systems, it is common to find latent variables that are hard, or even impossible, to measure with acceptable precision but are crucially important for the proper description of the dynamics. This substantially… read more here.
Keywords: discovery partial; partial differential; driven discovery; equation ... See more keywords
ALGAN: Anomaly Detection by Generating Pseudo Anomalous Data via Latent Variables
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3169594
Abstract: In many anomaly detection tasks, where anomalous data rarely appear and are difficult to collect, training using only normal data is important. Although it is possible to manually create anomalous data using prior knowledge, they… read more here.
Keywords: latent variables; pseudo anomalous; anomalous data; anomaly detection ... See more keywords
iVAE-GAN: Identifiable VAE-GAN Models for Latent Representation Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3172333
Abstract: Remarkable progress has been made within nonlinear Independent Component Analysis (ICA) and identifiable deep latent variable models. Formally, the latest nonlinear ICA theory enables us to recover the true latent variables up to a linear… read more here.
Keywords: ivae gan; vae; representation learning; gan ... See more keywords
Joint Learning of Multiple Differential Networks With Latent Variables
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Cybernetics"
DOI: 10.1109/tcyb.2018.2845838
Abstract: Graphical models have been widely used to learn the conditional dependence structures among random variables. In many controlled experiments, such as the studies of disease or drug effectiveness, learning the structural changes of graphical models… read more here.
Keywords: differential networks; graphical models; multiple differential; networks latent ... See more keywords
Community Detection With Known, Unknown, or Partially Known Auxiliary Latent Variables
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Network Science and Engineering"
DOI: 10.1109/tnse.2022.3207413
Abstract: Empirical observations suggest that in practice, community membership does not completely explain the dependency between the edges of an observation graph. The residual dependence of the graph edges are modeled in this paper, to first… read more here.
Keywords: auxiliary latent; latent; exact recovery; latent variables ... See more keywords
Tools for assessing the psychometric adequacy of latent variables in conservation research
Sign Up to like & getrecommendations! Published in 2020 at "Conservation Biology"
DOI: 10.1111/cobi.13625
Abstract: Conservation psychology has a history of measuring variables that cannot be seen (e.g., values, attitudes, norms). Such latent variables are critical drivers of human action and are often measured using responses to survey questions. Tools… read more here.
Keywords: adequacy; psychometric adequacy; conservation; assessing psychometric ... See more keywords