Latest Research in Bayesian Latent Modeling

Top Research Topics in Bayesian Latent Modeling

• Methodology — 71 papers
• Machine Learning — 37 papers
• Machine Learning — 32 papers
• Statistics Theory — 19 papers
• Statistical Methods and Inference — 17 papers
• Econometrics — 9 papers
• Advanced Statistical Methods and Models — 6 papers
• Advanced Causal Inference Techniques — 5 papers
• Bayesian Methods and Mixture Models — 5 papers
• Computation — 4 papers

Highest-Cited Papers

1. CliPS: How to identify cluster distributions in Bayesian mixture models
2. Recommendations for visual predictive checks in Bayesian workflow (1 citations)
3. Doubly robust estimation of causal survival effects via inverse probability of treatment and censoring weighting and semi-parametric AFT models with variable selection
4. 7 Reasons Bayes' Theorem Is the Most Consequential Equation You Were Never Taught
5. Deep Permutation Networks: Layerwise Invariant Manifolds, Closed-Form Attractor Splicing, and Zero-Backpropagation Topological Learning
6. Scalable multicollinearity recovery via mixed-integer optimization
7. Scalable Fitting Methods for Multivariate Gaussian Additive Models with Covariate-dependent Covariance Matrices
8. Hierarchical Evidence Calculus (HEC): A Meta-Statistical Framework Unifying Frequentist and Bayesian Paradigms
9. Efficient estimation in a semiparametric longitudinal data model with unknown time-varying AR error structure
10. Approximate Factor Models for Functional Time Series
11. Deep Permutation Networks: Layerwise Invariant Manifolds, Closed-Form Attractor Splicing, and Zero-Backpropagation Topological Learning
12. Robust empirical likelihood inference of longitudinal partially linear models with missing response
13. Modeling multivariate lattice data with Dirichlet process mixture spatial random effects
14. Integrative Analysis of Heterogeneous Multisource Partly Interval‐Censored Data
15. Nonparametric Feature Screening for Non-Euclidean Data
16. Next-token functional estimation
17. Compressed Active Subspaces for Scalable Bayesian Inference
18. Online Adaptive Kernel Mixing for Gaussian Process Decision Making
19. Multi-Absorbing Phase-Type Distributions for Right-Censored Competing Risks Data
20. A Bayesian Bi-Directional Splitting Framework for Variable Selection in Large Datasets

Sub-Regions

• Machine Learning — 47 papers
• Econometrics — 40 papers
• Statistics Theory — 27 papers
• Methodology — 22 papers
• Statistical Methods and Inference — 21 papers
• Computation — 20 papers