Latent variable estimation with composite Hilbert space Gaussian processes
Fuente:
arXiv
Saved in:
| Main Authors: | Mukherjee, Soham, Aguilar, Javier Enrique, Zago, Marcello, Claassen, Manfred, Bürkner, Paul-Christian |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Hilbert space methods for approximating multi-output latent variable Gaussian processes
by: Mukherjee, Soham, et al.
Published: (2025)
by: Mukherjee, Soham, et al.
Published: (2025)
DGP-LVM: Derivative Gaussian process latent variable models
by: Mukherjee, Soham, et al.
Published: (2024)
by: Mukherjee, Soham, et al.
Published: (2024)
Generalized Decomposition Priors on R2
by: Aguilar, Javier Enrique, et al.
Published: (2024)
by: Aguilar, Javier Enrique, et al.
Published: (2024)
Intuitive Joint Priors for Bayesian Linear Multilevel Models: The R2D2M2 prior
by: Aguilar, Javier Enrique, et al.
Published: (2022)
by: Aguilar, Javier Enrique, et al.
Published: (2022)
Dependency-Aware Shrinkage Priors for High Dimensional Regression
by: Aguilar, Javier Enrique, et al.
Published: (2025)
by: Aguilar, Javier Enrique, et al.
Published: (2025)
Primed Priors for Simulation-Based Validation of Bayesian Models
by: Fazio, Luna, et al.
Published: (2024)
by: Fazio, Luna, et al.
Published: (2024)
Gaussian distributional structural equation models: A framework for modeling latent heteroscedasticity
by: Fazio, Luna, et al.
Published: (2024)
by: Fazio, Luna, et al.
Published: (2024)
R2 priors for Grouped Variance Decomposition in High-dimensional Regression
by: Aguilar, Javier Enrique, et al.
Published: (2025)
by: Aguilar, Javier Enrique, et al.
Published: (2025)
Prediction can be safely used as a proxy for explanation in causally consistent Bayesian generalized linear models
by: Scholz, Maximilian, et al.
Published: (2022)
by: Scholz, Maximilian, et al.
Published: (2022)
Posterior accuracy and calibration under misspecification in Bayesian generalized linear models
by: Scholz, Maximilian, et al.
Published: (2023)
by: Scholz, Maximilian, et al.
Published: (2023)
Simulation-based validation of Bayes factor computation
by: Modrák, Martin, et al.
Published: (2025)
by: Modrák, Martin, et al.
Published: (2025)
Some models are useful, but how do we know which ones? Towards a unified Bayesian model taxonomy
by: Bürkner, Paul-Christian, et al.
Published: (2022)
by: Bürkner, Paul-Christian, et al.
Published: (2022)
elicito: A Python Package for Expert Prior Elicitation
by: Bockting, Florence, et al.
Published: (2025)
by: Bockting, Florence, et al.
Published: (2025)
Expert-elicitation method for non-parametric joint priors using normalizing flows
by: Bockting, Florence, et al.
Published: (2024)
by: Bockting, Florence, et al.
Published: (2024)
Simulation-Based Prior Knowledge Elicitation for Parametric Bayesian Models
by: Bockting, Florence, et al.
Published: (2023)
by: Bockting, Florence, et al.
Published: (2023)
Efficient Uncertainty Propagation in Bayesian Two-Step Procedures
by: Jedhoff, Svenja, et al.
Published: (2025)
by: Jedhoff, Svenja, et al.
Published: (2025)
Detecting and diagnosing prior and likelihood sensitivity with power-scaling
by: Kallioinen, Noa, et al.
Published: (2021)
by: Kallioinen, Noa, et al.
Published: (2021)
Posterior SBC: Simulation-Based Calibration Checking Conditional on Data
by: Säilynoja, Teemu, et al.
Published: (2025)
by: Säilynoja, Teemu, et al.
Published: (2025)
Uncertainty-Aware Surrogate-based Amortized Bayesian Inference for Computationally Expensive Models
by: Scheurer, Stefania, et al.
Published: (2025)
by: Scheurer, Stefania, et al.
Published: (2025)
Sensitivity-Aware Amortized Bayesian Inference
by: Elsemüller, Lasse, et al.
Published: (2023)
by: Elsemüller, Lasse, et al.
Published: (2023)
Joint estimation of the predictive ability of experts using a multi-output Gaussian process
by: Oelrich, Oscar, et al.
Published: (2024)
by: Oelrich, Oscar, et al.
Published: (2024)
Does Unsupervised Domain Adaptation Improve the Robustness of Amortized Bayesian Inference? A Systematic Evaluation
by: Elsemüller, Lasse, et al.
Published: (2025)
by: Elsemüller, Lasse, et al.
Published: (2025)
Spatial Latent Gaussian Modelling with Change of Support
by: Chacón-Montalván, Erick A., et al.
Published: (2024)
by: Chacón-Montalván, Erick A., et al.
Published: (2024)
Locally weighted minimum contrast estimation for spatio-temporal log-Gaussian Cox processes
by: D'Angelo, Nicoletta, et al.
Published: (2022)
by: D'Angelo, Nicoletta, et al.
Published: (2022)
Latent process models for functional network data
by: MacDonald, Peter W., et al.
Published: (2022)
by: MacDonald, Peter W., et al.
Published: (2022)
Conformal uncertainty quantification using kernel depth measures in separable Hilbert spaces
by: Matabuena, Marcos, et al.
Published: (2024)
by: Matabuena, Marcos, et al.
Published: (2024)
Bayesian estimation of a multivariate TAR model when the noise process distribution belongs to the class of Gaussian variance mixtures
by: Vanegas, L. H., et al.
Published: (2025)
by: Vanegas, L. H., et al.
Published: (2025)
Model Uncertainty in Latent Gaussian Models with Univariate Link Function
by: Steel, Mark F. J., et al.
Published: (2024)
by: Steel, Mark F. J., et al.
Published: (2024)
Deep learning estimation of the spectral density of functional time series on large domains
by: Mohammadi, Neda, et al.
Published: (2026)
by: Mohammadi, Neda, et al.
Published: (2026)
Classification Trees with Valid Inference via the Exponential Mechanism
by: Bakshi, Soham, et al.
Published: (2025)
by: Bakshi, Soham, et al.
Published: (2025)
Improving instrumental variable estimators with post-stratification
by: Pashley, Nicole E., et al.
Published: (2023)
by: Pashley, Nicole E., et al.
Published: (2023)
Simulation-Based Calibration Checking for Bayesian Computation: The Choice of Test Quantities Shapes Sensitivity
by: Modrák, Martin, et al.
Published: (2022)
by: Modrák, Martin, et al.
Published: (2022)
Sensitivity of weighted least squares estimators to omitted variables
by: Wainstein, Leonard, et al.
Published: (2025)
by: Wainstein, Leonard, et al.
Published: (2025)
Assessing uncertainty in Gaussian mixtures-based entropy estimation
by: Scrucca, Luca
Published: (2024)
by: Scrucca, Luca
Published: (2024)
The Poisson-Gaussian Mixture Process: A Flexible and Robust Approach for Non-Gaussian Geostatistical Modeling
by: Gonçalves, F. B., et al.
Published: (2022)
by: Gonçalves, F. B., et al.
Published: (2022)
The Bayesian Gaussian Process Latent Variable Model for Spatio-Temporal Stream Networks
by: Basson, Marno, et al.
Published: (2026)
by: Basson, Marno, et al.
Published: (2026)
High-dimensional regression with outcomes of mixed-type using the multivariate spike-and-slab LASSO
by: Ghosh, Soham, et al.
Published: (2025)
by: Ghosh, Soham, et al.
Published: (2025)
Robust designs for Gaussian process emulation of computer experiments
by: Mak, Simon, et al.
Published: (2025)
by: Mak, Simon, et al.
Published: (2025)
Scalable generative modeling of non-Gaussian spatio-temporal fields via autoregressive Gaussian processes
by: Lei-Cramer, Carrie J., et al.
Published: (2026)
by: Lei-Cramer, Carrie J., et al.
Published: (2026)
Large covariance matrix estimation with factor-assisted variable clustering
by: Li, Dong, et al.
Published: (2025)
by: Li, Dong, et al.
Published: (2025)
Similar Items
-
Hilbert space methods for approximating multi-output latent variable Gaussian processes
by: Mukherjee, Soham, et al.
Published: (2025) -
DGP-LVM: Derivative Gaussian process latent variable models
by: Mukherjee, Soham, et al.
Published: (2024) -
Generalized Decomposition Priors on R2
by: Aguilar, Javier Enrique, et al.
Published: (2024) -
Intuitive Joint Priors for Bayesian Linear Multilevel Models: The R2D2M2 prior
by: Aguilar, Javier Enrique, et al.
Published: (2022) -
Dependency-Aware Shrinkage Priors for High Dimensional Regression
by: Aguilar, Javier Enrique, et al.
Published: (2025)