Results 21 to 30 of about 6,143,323 (339)
A geoadditive Bayesian latent variable model for Poisson indicators [PDF]
, 2006 We introduce a new latent variable model with count variable indicators, where usual linear parametric effects of covariates, nonparametric effects of continuous covariates and spatial effects on the continuous latent variables are modelled through a ...
Fahrmeir, Ludwig, Steinert, Sven
core +3 more sources
Frontiers in Psychology, 2019 The Inventory of Callous-Unemotional Traits (ICU) was designed to evaluate multiple facets of Callous-Unemotional (CU) traits in youths. However, no study has examined the factor structure and psychometrical properties of the ICU in Chinese detained ...
Xintong Zhang +11 more
doaj +1 more source
Latent-Variable Non-Autoregressive Neural Machine Translation with Deterministic Inference using a Delta Posterior [PDF]
AAAI Conference on Artificial Intelligence, 2019 Although neural machine translation models reached high translation quality, the autoregressive nature makes inference difficult to parallelize and leads to high translation latency.
Raphael Shu +3 more
semanticscholar +1 more source
Frontiers in Psychology, 2019 The Youth Psychopathic Traits Inventory (YPI) was designed to assess psychopathic traits in adolescents. However, there exists limited evidence for the factor structure and psychometric properties of the YPI when used with Chinese detained juveniles. The
Wendeng Yang +10 more
doaj +1 more source
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.
Wenjuan Han, Ge Wang, Kewei Tu
doaj +1 more source
The Use of Loglinear Models for Assessing Differential Item Functioning Across Manifest and Latent Examinee Groups [PDF]
, 1990 Loglinear latent class models are used to detect differential item functioning (DIF). These models are formulated in such a manner that the attribute to be assessed may be continuous, as in a Rasch model, or categorical, as in Latent Class Mastery models.
Kelderman, Henk, Macready, George B.
core +4 more sources
Evaluation of Variance Inflation Factors in Regression Models Using Latent Variable Modeling Methods
Educational and Psychological Measurement, 2019 A procedure that can be used to evaluate the variance inflation factors and tolerance indices in linear regression models is discussed. The method permits both point and interval estimation of these factors and indices associated with explanatory ...
Katerina M. Marcoulides, T. Raykov
semanticscholar +1 more source
Latent Variable Model for Multi-modal Translation [PDF]
, 2019 In this work, we propose to model the interaction between visual and textual features for multi-modal neural machine translation (MMT) through a latent variable model. This latent variable can be seen as a multi-modal stochastic embedding of an image and
Aziz, Wilker +2 more
core +2 more sources
Econometrics, 2019 It is customary to assume that an indicator of a latent variable is driven by the latent variable and some random noise. In contrast, a background indicator is also systematically influenced by variables outside the structural model of interest ...
Burkhard Raunig
doaj +1 more source
Implicit Deep Latent Variable Models for Text Generation [PDF]
Conference on Empirical Methods in Natural Language Processing, 2019 Deep latent variable models (LVM) such as variational auto-encoder (VAE) have recently played an important role in text generation. One key factor is the exploitation of smooth latent structures to guide the generation.
Le Fang +4 more
semanticscholar +1 more source