Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 154 for “"Latent variables"”.
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Learning Generative Models Using Structured Latent Variables
… knowledge is used to specify meaningful latent representation with structure, which forces the model to generalize better under certain scenarios. For example, a generative model with latent gating variables that will ``switch off" noisy pixels should perform better when encountering …
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Anomaly Detection via Latent Variables Learned by Variational Autoencoders
… of the art modeling techniques that incorporate latent variables, hidden variables that are not directly observed but instead inferred from observed variables. Approaches to anomaly detection via variational autoencoders either adopt reconstruction error as a sole anomaly detection metric, …
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Towards smooth particle filters for likelihood estimation with multivariate latent variables
… when the parameters change. When the state variables are univariate, a method exists that gives an estimator of the log-likelihood that is continuous in the parameters. We present a non-trivial generalization of this method using tree-based o(N²) (and as low as O(N log N)) resampling schemes …
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Least squares estimation for latent variables with dichotomous item response data
A new method for estimating the ability parameters in the statistical models based on item response theory (IRT) was presented in this study. A brief review of existing parameter estimation methods suggested the utility of a parameter estimation method which requires no specific assumption. By …
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Extended discrete choice models : integrated framework, flexible error structures, and latent variables
… of the parameter estimates. - Incorporating latent variables in order to provide a richer explanation of behavior by explicitly representing the formation and effects of latent constructs such as attitudes and perceptions. - Stipulating latent classes in order to capture latent segmentation, …
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Repeated Measures ANOVA with Latent Variables: A New Approach Based on Structural Equation Modeling
This doctoral dissertation develops latent repeated measures analysis of variance (L-RM-ANOVA) as an alternative approach to traditional repeated measures ANOVA (RM-ANOVA). Traditional RM-ANOVA are commonplace for investigating phenomena in the social and behavioral sciences, and researchers often …
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Some Recent Advances in Non- and Semiparametric Bayesian Modeling with Copulas, Mixtures, and Latent Variables
… the interpretability of factor loadings and the latent variables. I adopt an approximate likelihood for posterior inference and prove that, if the Gaussian copula model is true, the approximate posterior distribution of the copula correlation matrix asymptotically converges to the correct …
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Understanding blood pressure dynamics in the South African population: a latent variables approach to the analysis and comparison of data from multiple surveys
… of such variations with socioeconomic variables.However, evidence on these mechanisms and reliable information on the temporal trends of blood pressure themselves are scant outside high‐income countries. Given the large gain in health that would result in low‐ and middle‐income …
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Probabilistic latent variable models for knowledge discovery and optimization
I conduct a systematic study of probabilistic latent variable models (PLVMs) with applications to knowledge discovery and optimization. Probabilistic modeling is a principled means to gain insight of data. By assuming that the observed data are generated from a distribution, we can estimate its …
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Latent Clustered Causal Models
… directed graphical models in the presence of latent variables. We define latent clustered causal models as a particular restriction on directed graphical models with latent variables and corresponding clusters of observed nodes, characterized by edges between only observed and latent …
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Capsule Networks: Framework and Application to Disentanglement for Generative Models
… of variational autoencoders is centered around latent variables and their objective function directly governs the generative factors, they are the perfect choice for creating a more disentangled representation. However, these architectures generate samples that are blurry and of lower quality …
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Essays in Corporate Saving, Financial Development, and *Growth
… and Saving Channels of Economic Growth as Latent Variables: An Application of Confirmatory Factor Analysis"". It is well-known that the rate of economic growth per capita can be decomposed into two sources: total factor productivity and capital per worker. Our claim is that the measurement …
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Identificação do efeito causal no modelo de mediação com variáveis latentes
… methods are described in terms of continuous variables, especially linear models, and are used in situations where the variables are measured without error. In certain scenarios, however, the mediator and/or outcome may not be directly observed but can be potentially defined through latent …
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Probabilistic Graphical Models for Crowdsourcing and Turbulence
… for the crowdsourced annotations involving as latent variables the worker reliability, the structure of the labels, and the ground truth labels. Furthermore, we design an effective inference algorithm to infer the latent variables. In turbulence, we consider the problem of modeling the mixing …
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Automatic Bayesian Inference of Reaction Networks via Guiding
… modeling. However, performing inference on the latent variables and parameters of such models is challenging, particularly when the observations of the system state are noisy and incomplete. This thesis presents CatalystFitting, a system for inferring the latent variables and parameters of …
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Testing a Theoretical Model of Critical Thinking and Cognitive Development
… nursing education. Multivariate analysis with latent variables was used to test a theoretical model of critical thinking and cognitive development. A two-step approach for testing the hypothesized model was used in this study. The first step involved testing the measurement model by …
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Generalized Linear Mixed Proficiency Models for Cognitive Diagnosis
Models for cognitive diagnosis combine discrete latent trait models with constrained latent class analysis, allowing the user to diagnosis the set of abilities an examinee may possess. Following a review of relevant cognitive diagnosis models and commonly used methods of estimation, implementation …
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Trees and beyond : exploiting and improving tree-structured graphical models
Probabilistic models commonly assume that variables are independent of each other conditioned on a subset of other variables. Graphical models provide a powerful framework for encoding such conditional independence structure of a large collection of random variables. A special class of graphical …
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Latent variable interaction in structural equation models
… investigated moderated regression analysis using latent variables. Interactive psychological theories, the stress-buffering hypothesis, and interaction in regression and structural equation models, were reviewed. Moderated regression was recast using latent variables to accommodate measurement …
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A COMPARATIVE STUDY OF THE GLOBAL-MINDEDNESS OF FRESHMEN AND SENIOR STUDENTS AT NORTHERN MICHIGAN UNIVERSITY
… difference in the mean score on one of the five latent variables of globalcentrism between freshmen and senior pre-service teachers. Globalcentrism is defined by Hett (1993) as a tradition of thinking and behaving globally rather than locally and a sense of full global consideration when making …
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