Efficient Bayesian Inference for Discretely Observed Continuous Time Markov Chains
Fuente:
arXiv
Saved in:
| Main Authors: | Tang, Tao, Astfalck, Lachlan, Dunson, David |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Scalable Bayesian inference for time series via divide-and-conquer
by: Ou, Rihui, et al.
Published: (2021)
by: Ou, Rihui, et al.
Published: (2021)
Posterior Projection for Inference in Constrained Spaces
by: Astfalck, Lachlan, et al.
Published: (2018)
by: Astfalck, Lachlan, et al.
Published: (2018)
Universal Modelling of Autocovariance Functions via Spline Kernels
by: Astfalck, Lachlan
Published: (2025)
by: Astfalck, Lachlan
Published: (2025)
Generalised Bayes Linear Inference
by: Astfalck, Lachlan, et al.
Published: (2024)
by: Astfalck, Lachlan, et al.
Published: (2024)
Spatial meshing for general Bayesian multivariate models
by: Peruzzi, Michele, et al.
Published: (2022)
by: Peruzzi, Michele, et al.
Published: (2022)
Factor pre-training in Bayesian multivariate logistic models
by: Mauri, Lorenzo, et al.
Published: (2024)
by: Mauri, Lorenzo, et al.
Published: (2024)
Nonparametric Modeling of Continuous-Time Markov Chains
by: Monti, Filippo, et al.
Published: (2025)
by: Monti, Filippo, et al.
Published: (2025)
Bias correction of quadratic spectral estimators
by: Astfalck, Lachlan, et al.
Published: (2024)
by: Astfalck, Lachlan, et al.
Published: (2024)
Bayesian Inference for Non-Synchronously Observed Diffusions
by: Jasra, Ajay, et al.
Published: (2025)
by: Jasra, Ajay, et al.
Published: (2025)
Inference on covariance structure in high-dimensional multi-view data
by: Mauri, Lorenzo, et al.
Published: (2025)
by: Mauri, Lorenzo, et al.
Published: (2025)
Accelerated Inference for Partially Observed Markov Processes using Automatic Differentiation
by: Tan, Kevin, et al.
Published: (2024)
by: Tan, Kevin, et al.
Published: (2024)
Efficient Amortized Bayesian Inference for Markov Random Fields via Gradient-Informed Grid Selection
by: Bazahica, Laura, et al.
Published: (2026)
by: Bazahica, Laura, et al.
Published: (2026)
Efficient posterior sampling for high-dimensional imbalanced logistic regression
by: Sen, Deborshee, et al.
Published: (2019)
by: Sen, Deborshee, et al.
Published: (2019)
Bayesian Clustering via Fusing of Localized Densities
by: Dombowsky, Alexander, et al.
Published: (2023)
by: Dombowsky, Alexander, et al.
Published: (2023)
Bayesian Inference for Discrete Markov Random Fields Through Coordinate Rescaling
by: Arena, Giuseppe, et al.
Published: (2026)
by: Arena, Giuseppe, et al.
Published: (2026)
Product Centered Dirichlet Processes for Bayesian Multiview Clustering
by: Dombowsky, Alexander, et al.
Published: (2023)
by: Dombowsky, Alexander, et al.
Published: (2023)
Debiasing Welch's Method for Spectral Density Estimation
by: Astfalck, Lachlan C., et al.
Published: (2023)
by: Astfalck, Lachlan C., et al.
Published: (2023)
Learning discrete Bayesian networks with hierarchical Dirichlet shrinkage
by: Dombowsky, Alexander, et al.
Published: (2025)
by: Dombowsky, Alexander, et al.
Published: (2025)
Bayesian Latent Class Regression with Interpretable Binary Profiles
by: Zhou, Yuren, et al.
Published: (2025)
by: Zhou, Yuren, et al.
Published: (2025)
Bayesian Deep Generative Models for Multiplex Networks with Multiscale Overlapping Clusters
by: Zhou, Yuren, et al.
Published: (2024)
by: Zhou, Yuren, et al.
Published: (2024)
Blessing of dimension in Bayesian inference on covariance matrices
by: Chattopadhyay, Shounak, et al.
Published: (2024)
by: Chattopadhyay, Shounak, et al.
Published: (2024)
Bayesian modeling of nearly mutually orthogonal processes
by: Matuk, James, et al.
Published: (2022)
by: Matuk, James, et al.
Published: (2022)
Bayesian Level Set Clustering
by: Buch, David, et al.
Published: (2024)
by: Buch, David, et al.
Published: (2024)
panelPomp: Analysis of Panel Data via Partially Observed Markov Processes in R
by: Bretó, Carles, et al.
Published: (2024)
by: Bretó, Carles, et al.
Published: (2024)
A Bayesian theory for estimation of biodiversity
by: Rigon, Tommaso, et al.
Published: (2025)
by: Rigon, Tommaso, et al.
Published: (2025)
Efficient Bayesian Inference for Spatial Point Patterns Using the Palm Likelihood
by: Collins, Kevin M., et al.
Published: (2025)
by: Collins, Kevin M., et al.
Published: (2025)
Uncertainty Quantification in Bayesian Clustering
by: Page, Garritt L., et al.
Published: (2025)
by: Page, Garritt L., et al.
Published: (2025)
Spectral decomposition-assisted multi-study factor analysis
by: Mauri, Lorenzo, et al.
Published: (2025)
by: Mauri, Lorenzo, et al.
Published: (2025)
Nearest Neighbor Dirichlet Mixtures
by: Chattopadhyay, Shounak, et al.
Published: (2020)
by: Chattopadhyay, Shounak, et al.
Published: (2020)
Bayesian Joint Additive Factor Models for Multiview Learning
by: Anceschi, Niccolo, et al.
Published: (2024)
by: Anceschi, Niccolo, et al.
Published: (2024)
Bayesian nonparametric modeling of latent partitions via Stirling-gamma priors
by: Zito, Alessandro, et al.
Published: (2023)
by: Zito, Alessandro, et al.
Published: (2023)
Bayesian Markov-Switching Partial Reduced-Rank Regression
by: Pintado, Maria F., et al.
Published: (2025)
by: Pintado, Maria F., et al.
Published: (2025)
Bayesian penalized empirical likelihood and Markov Chain Monte Carlo sampling
by: Chang, Jinyuan, et al.
Published: (2024)
by: Chang, Jinyuan, et al.
Published: (2024)
Stereographic Markov Chain Monte Carlo
by: Yang, Jun, et al.
Published: (2022)
by: Yang, Jun, et al.
Published: (2022)
Bayesian cross-validation by parallel Markov Chain Monte Carlo
by: Cooper, Alex, et al.
Published: (2023)
by: Cooper, Alex, et al.
Published: (2023)
Inferring Covariance Structure from Multiple Data Sources via Subspace Factor Analysis
by: Chandra, Noirrit Kiran, et al.
Published: (2023)
by: Chandra, Noirrit Kiran, et al.
Published: (2023)
Efficient Inference in First Passage Time Models
by: Liu, Sicheng, et al.
Published: (2025)
by: Liu, Sicheng, et al.
Published: (2025)
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)
Gridding and Parameter Expansion for Scalable Latent Gaussian Models of Spatial Multivariate Data
by: Peruzzi, Michele, et al.
Published: (2021)
by: Peruzzi, Michele, et al.
Published: (2021)
Generalized Bayesian Likelihood-Free Inference
by: Pacchiardi, Lorenzo, et al.
Published: (2021)
by: Pacchiardi, Lorenzo, et al.
Published: (2021)
Similar Items
-
Scalable Bayesian inference for time series via divide-and-conquer
by: Ou, Rihui, et al.
Published: (2021) -
Posterior Projection for Inference in Constrained Spaces
by: Astfalck, Lachlan, et al.
Published: (2018) -
Universal Modelling of Autocovariance Functions via Spline Kernels
by: Astfalck, Lachlan
Published: (2025) -
Generalised Bayes Linear Inference
by: Astfalck, Lachlan, et al.
Published: (2024) -
Spatial meshing for general Bayesian multivariate models
by: Peruzzi, Michele, et al.
Published: (2022)