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Variational Approximations for Categorical Causal Modeling With Latent Variables
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Latent Structure Analysis
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Structural Equations with Latent Variables
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Introduction to Bayesian Networks
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Tractable Undirected Approximations for Graphical Models
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Introduction to Inference for Bayesian Networks
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A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants
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Efficient Estimation and Local Identification in Latent Class Analysis
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The computational complexity of probabilistic inference using bayesian belief networks
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The EM algorithm for graphical association models with missing data
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The theory of planned behavior
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Information geometry of the EM and em algorithms for neural networks
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Longitudinal Factor Analysis
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Patterns of Change within Latent Variable Structural Equation Models
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Advances in neural information processing systems 7
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Advances in neural information processing systems 7
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Probability functions on complex pedigrees
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Factorial Hidden Markov Models
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An Introduction to Variational Methods for Graphical Models
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Improving the Mean-Field Approximation in Belief Networks Using Bahadur's Reparameterisation of the Multivariate Binary Distribution
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Graphical Models in Applied Multivariate Statistics
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Exploratory Latent Structure Analysis Using Both Identifiable and Unidentifiable Models
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Analysis of Latent Structure Models with Multidimensional Latent Variables
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The application of the Gibbs-Bogoliubov-Feynman inequality in mean field calculations for Markov random fields
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An introduction to hidden Markov models
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The Estimation of Gross Flows in the Presence of Measurement Error using Auxiliary Variables
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On the Adequacy of Variational Lower Bound Functions for Likelihood-based Inference in Markovian Models with Missing Values
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Application of the Theory of Planned Behavior to Adolescents’ Condom Use: A Panel Study1
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Asymptotically distribution‐free methods for the analysis of covariance structures
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Maximum Likelihood from Incomplete Data Via the EM Algorithm
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Local Computations with Probabilities on Graphical Structures and Their Application to Expert Systems
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Probabilistic Independence Networks for Hidden Markov Probability Models
inferredcites →https://doi.org/10.1177/0049124198026004002openalex-snapshot
Categorical Causal Modeling
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Graphs, Causality, and Structural Equation Models
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A Longitudinal Factor Model For Studying Change In Ability Structure
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A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains
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Mean Field Theory for Sigmoid Belief Networks
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Hidden Markov and Other Models for Discrete-Valued Time Series
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Structural Equations with Latent Variables.
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Loglinear Models with Latent Variables.
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Latent Variables Analysis: Applications for Developmental Research.
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Studies in Item Analysis and Prediction.
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Applications of Latent Trait and Latent Class Models in the Social Sciences
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Hidden Markov and Other Models for Discrete-Valued Time Series
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An Introduction to Bayesian Networks.
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Structural Equation Modeling: Concepts, Issues, and Applications.
inferredcites →https://doi.org/10.4135/9781412984850openalex-snapshot
Loglinear models with Latent Variables
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The nature of mathematical modeling
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Advanced Mean Field Methods
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/s10479-012-1181-7openalex-snapshot
Fitting an item response theory model with random item effects across groups by a variational approximation method
inferred← citeshttps://doi.org/10.1007/s10985-014-9316-6openalex-snapshot
Joint modeling of recurrent event processes and intermittently observed time-varying binary covariate processes
inferred← citeshttps://doi.org/10.1007/s11336-007-9001-8openalex-snapshot
Latent Class Models for Diary Method Data: Parameter Estimation by Local Computations
inferred← citeshttps://doi.org/10.1007/s11336-011-9203-yopenalex-snapshot
Item Screening in Graphical Loglinear Rasch Models
inferred← citeshttps://doi.org/10.1007/s11336-012-9295-zopenalex-snapshot
Global Convergence of the EM Algorithm for Unconstrained Latent Variable Models with Categorical Indicators
inferred← citeshttps://doi.org/10.1007/s11336-017-9555-zopenalex-snapshot
A Variational Maximization–Maximization Algorithm for Generalized Linear Mixed Models with Crossed Random Effects
inferred← citeshttps://doi.org/10.1007/s11336-022-09884-4openalex-snapshot
Scalable Bayesian Approach for the Dina Q-Matrix Estimation Combining Stochastic Optimization and Variational Inference
inferred← citeshttps://doi.org/10.1007/s40547-018-0088-0openalex-snapshot
A Factorial Hidden Markov Model for the Analysis of Temporal Change in Choice Models
inferred← citeshttps://doi.org/10.1017/cbo9780511642401.023openalex-snapshot
Maximum likelihood estimation in latent class models for contingency table data
inferred← citeshttps://doi.org/10.1080/10705511.2024.2339396openalex-snapshot
A Causal Framework for the Comparability of Latent Variables
inferred← citeshttps://doi.org/10.1111/1467-9868.00350openalex-snapshot
On the Adequacy of Variational Lower Bound Functions for Likelihood-based Inference in Markovian Models with Missing Values
inferred← citeshttps://doi.org/10.1111/bmsp.12308openalex-snapshot
Variational Bayes inference for hidden Markov diagnostic classification models
inferred← citeshttps://doi.org/10.1214/15-aos1414openalex-snapshot
Tensor decompositions and sparse log-linear models
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Variational Bayes Inference for the DINA Model
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Recent developments in maximum likelihood estimation of MTMM models for categorical data
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