Probabilistic Graphical Model using Graph Neural Networks for Bayesian Inversion of Discrete Structural Component States
Fuente:
arXiv
Saved in:
| Main Authors: | Li, Teng, Wu, Stephen, Huang, Yong, Beck, James L., Li, Hui |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
MCMC with Adaptive Principal-Component Transformation: Rotation-Invariant Universal Samplers for Bayesian Structural System Identification
by: Meng, Xianghao, et al.
Published: (2026)
by: Meng, Xianghao, et al.
Published: (2026)
Adaptive Meta-Learning Stochastic Gradient Hamiltonian Monte Carlo Simulation for Bayesian Updating of Structural Dynamic Models
by: Meng, Xianghao, et al.
Published: (2026)
by: Meng, Xianghao, et al.
Published: (2026)
Probabilistic Multilabel Graphical Modelling of Motif Transformations in Symbolic Music
by: Taieb, Ron, et al.
Published: (2026)
by: Taieb, Ron, et al.
Published: (2026)
Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives
by: Behdin, Kayhan, et al.
Published: (2023)
by: Behdin, Kayhan, et al.
Published: (2023)
Scalable Bayesian Structure Learning for Gaussian Graphical Models Using Marginal Pseudo-likelihood
by: Mohammadi, Reza, et al.
Published: (2023)
by: Mohammadi, Reza, et al.
Published: (2023)
Covariate-dependent Graphical Model Estimation via Neural Networks with Statistical Guarantees
by: Lin, Jiahe, et al.
Published: (2025)
by: Lin, Jiahe, et al.
Published: (2025)
Hierarchical Probabilistic Principal Component Analysis of Longitudinal Data
by: Zhang, Xinyu, et al.
Published: (2026)
by: Zhang, Xinyu, et al.
Published: (2026)
Exact and Approximate MCMC for Doubly-intractable Probabilistic Graphical Models Leveraging the Underlying Independence Model
by: Chen, Yujie, et al.
Published: (2025)
by: Chen, Yujie, et al.
Published: (2025)
Bayesian Empirical Bayes: Simultaneous Inference from Probabilistic Symmetries
by: Wu, Bohan, et al.
Published: (2025)
by: Wu, Bohan, et al.
Published: (2025)
Graphical Principal Component Analysis of Multivariate Functional Time Series
by: Tan, Jianbin, et al.
Published: (2024)
by: Tan, Jianbin, et al.
Published: (2024)
Structure Maintained Representation Learning Neural Network for Causal Inference
by: Sun, Yang, et al.
Published: (2025)
by: Sun, Yang, et al.
Published: (2025)
Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks
by: Sainsbury-Dale, Matthew, et al.
Published: (2023)
by: Sainsbury-Dale, Matthew, et al.
Published: (2023)
Graphical Transformation Models
by: Herp, Matthias, et al.
Published: (2025)
by: Herp, Matthias, et al.
Published: (2025)
Amortized Inference for Correlated Discrete Choice Models via Equivariant Neural Networks
by: Huch, Easton, et al.
Published: (2026)
by: Huch, Easton, et al.
Published: (2026)
High-dimensional Functional Graphical Model Structure Learning via Neighborhood Selection Approach
by: Zhao, Boxin, et al.
Published: (2021)
by: Zhao, Boxin, et al.
Published: (2021)
Profile Graphical Models
by: Avalos-Pacheco, Alejandra, et al.
Published: (2026)
by: Avalos-Pacheco, Alejandra, et al.
Published: (2026)
A Copula Graphical Model for Multi-Attribute Data using Optimal Transport
by: Zhang, Qi, et al.
Published: (2024)
by: Zhang, Qi, et al.
Published: (2024)
Bayesian Functional Graphical Models with Change-Point Detection
by: Liu, Chunshan, et al.
Published: (2024)
by: Liu, Chunshan, et al.
Published: (2024)
Change-point Detection and Segmentation of Discrete Data using Bayesian Context Trees
by: Lungu, Valentinian, et al.
Published: (2022)
by: Lungu, Valentinian, et al.
Published: (2022)
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook
by: Jiang, Wenzhao, et al.
Published: (2023)
by: Jiang, Wenzhao, et al.
Published: (2023)
A Graphical Approach to State Variable Selection in Off-policy Learning
by: Andersen, Joakim Blach, et al.
Published: (2025)
by: Andersen, Joakim Blach, et al.
Published: (2025)
Introducing Diminutive Causal Structure into Graph Representation Learning
by: Gao, Hang, et al.
Published: (2024)
by: Gao, Hang, et al.
Published: (2024)
Graphical Modelling without Independence Assumptions for Uncentered Data
by: Andrew, Bailey, et al.
Published: (2024)
by: Andrew, Bailey, et al.
Published: (2024)
Enhancing the Power of Gaussian Graphical Model Inference by Modeling the Graph Structure
by: Kilian, Valentin, et al.
Published: (2024)
by: Kilian, Valentin, et al.
Published: (2024)
Weighting-Based Identification and Estimation in Graphical Models of Missing Data
by: Guo, Anna, et al.
Published: (2026)
by: Guo, Anna, et al.
Published: (2026)
Sequential Conditional Transport on Probabilistic Graphs for Interpretable Counterfactual Fairness
by: Machado, Agathe Fernandes, et al.
Published: (2024)
by: Machado, Agathe Fernandes, et al.
Published: (2024)
Bayesian Inference for PDE-based Inverse Problems using the Optimization of a Discrete Loss
by: Amoudruz, Lucas, et al.
Published: (2025)
by: Amoudruz, Lucas, et al.
Published: (2025)
Nonlinear Bayesian optimal experimental design using logarithmic Sobolev inequalities
by: Li, Fengyi, et al.
Published: (2024)
by: Li, Fengyi, et al.
Published: (2024)
Bayesian Inference for Single-factor Graphical Models
by: Marcano, David, et al.
Published: (2025)
by: Marcano, David, et al.
Published: (2025)
Symbolic Density Estimation for Discrete Distributions
by: Liu, Ziwen, et al.
Published: (2026)
by: Liu, Ziwen, et al.
Published: (2026)
Bayesian Multiplicity Correction in the Probabilistic Forward Stepwise Framework
by: Womack, Andrew, et al.
Published: (2026)
by: Womack, Andrew, et al.
Published: (2026)
Variational Bayesian Bow tie Neural Networks with Shrinkage
by: Sheinkman, Alisa, et al.
Published: (2024)
by: Sheinkman, Alisa, et al.
Published: (2024)
Bayesian Structure Learning in Undirected Gaussian Graphical Models: Literature Review with Empirical Comparison
by: Vogels, Lucas, et al.
Published: (2023)
by: Vogels, Lucas, et al.
Published: (2023)
High-Dimensional Covariate-Dependent Discrete Graphical Models and Dynamic Ising Models
by: Roach, Lyndsay, et al.
Published: (2025)
by: Roach, Lyndsay, et al.
Published: (2025)
Understanding the Trade-offs in Accuracy and Uncertainty Quantification: Architecture and Inference Choices in Bayesian Neural Networks
by: Sheinkman, Alisa, et al.
Published: (2025)
by: Sheinkman, Alisa, et al.
Published: (2025)
Integrating Causal Inference with Graph Neural Networks for Alzheimer's Disease Analysis
by: Peddi, Pranay Kumar, et al.
Published: (2025)
by: Peddi, Pranay Kumar, et al.
Published: (2025)
Bayesian Graphical High-Dimensional Time Series Models for Detecting Structural Changes
by: Ghosh, Shuvrarghya, et al.
Published: (2025)
by: Ghosh, Shuvrarghya, et al.
Published: (2025)
Mixture of Directed Graphical Models for Discrete Spatial Random Fields
by: Carter, J. Brandon, et al.
Published: (2024)
by: Carter, J. Brandon, et al.
Published: (2024)
Learning Gaussian Graphical Models under Total Positivity via Spectral Graph Sparsification
by: Rodríguez, Ignacio Echave-Sustaeta, et al.
Published: (2026)
by: Rodríguez, Ignacio Echave-Sustaeta, et al.
Published: (2026)
Near-Optimal Approximations for Bayesian Inference in Function Space
by: Wild, Veit, et al.
Published: (2025)
by: Wild, Veit, et al.
Published: (2025)
Similar Items
-
MCMC with Adaptive Principal-Component Transformation: Rotation-Invariant Universal Samplers for Bayesian Structural System Identification
by: Meng, Xianghao, et al.
Published: (2026) -
Adaptive Meta-Learning Stochastic Gradient Hamiltonian Monte Carlo Simulation for Bayesian Updating of Structural Dynamic Models
by: Meng, Xianghao, et al.
Published: (2026) -
Probabilistic Multilabel Graphical Modelling of Motif Transformations in Symbolic Music
by: Taieb, Ron, et al.
Published: (2026) -
Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives
by: Behdin, Kayhan, et al.
Published: (2023) -
Scalable Bayesian Structure Learning for Gaussian Graphical Models Using Marginal Pseudo-likelihood
by: Mohammadi, Reza, et al.
Published: (2023)