Going With the Flow: Normalizing Flows for Gaussian Process Regression under Hierarchical Shrinkage Priors
Fuente:
arXiv
Saved in:
| Main Author: | Knaus, Peter |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
The Dynamic Triple Gamma Prior as a Shrinkage Process Prior for Time-Varying Parameter Models
by: Knaus, Peter, et al.
Published: (2023)
by: Knaus, Peter, et al.
Published: (2023)
GRASP: Grouped Regression with Adaptive Shrinkage Priors
by: Tew, Shu Yu, et al.
Published: (2025)
by: Tew, Shu Yu, et al.
Published: (2025)
Locally Adaptive Bayesian Isotonic Regression using Half Shrinkage Priors
by: Okano, Ryo, et al.
Published: (2022)
by: Okano, Ryo, 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)
Clustering Computer Mouse Tracking Data with Informed Hierarchical Shrinkage Partition Priors
by: Song, Ziyi, et al.
Published: (2024)
by: Song, Ziyi, et al.
Published: (2024)
Bayesian Region Selection and Prediction in Poisson Regression with Spatially Dependent Global-Local Shrinkage Prior
by: Zhu, Zihan, et al.
Published: (2026)
by: Zhu, Zihan, et al.
Published: (2026)
Relaxation of Projected Prior with Continuous Gap Shrinkage
by: Duan, Leo L, et al.
Published: (2026)
by: Duan, Leo L, et al.
Published: (2026)
Shrinkage Estimators for Beta Regression Models
by: Firinguetti, Luis, et al.
Published: (2024)
by: Firinguetti, Luis, et al.
Published: (2024)
Discrete Autoregressive Switching Processes with Cumulative Shrinkage Priors for Graphical Modeling of Time Series Data
by: Hadj-Amar, Beniamino, et al.
Published: (2024)
by: Hadj-Amar, Beniamino, et al.
Published: (2024)
Non-null Shrinkage Regression and Subset Selection via the Fractional Ridge Regression
by: Park, Sihyung, et al.
Published: (2025)
by: Park, Sihyung, et al.
Published: (2025)
Modeling Dynamic Correlation Matrices with Shrinkage Priors
by: Coulson, Daniel Andrew, et al.
Published: (2026)
by: Coulson, Daniel Andrew, et al.
Published: (2026)
The Choice of Normalization Influences Shrinkage in Regularized Regression
by: Larsson, Johan, et al.
Published: (2025)
by: Larsson, Johan, et al.
Published: (2025)
Linear Shrinkage Convexification of Penalized Linear Regression With Missing Data
by: Park, Seongoh, et al.
Published: (2024)
by: Park, Seongoh, et al.
Published: (2024)
Scalable Scalar-on-Image Cortical Surface Regression with a Relaxed-Thresholded Gaussian Process Prior
by: Menacher, Anna, et al.
Published: (2024)
by: Menacher, Anna, et al.
Published: (2024)
Flexibly Modeling Shocks to Demographic and Health Indicators with Bayesian Shrinkage Priors
by: Susmann, Herbert, et al.
Published: (2024)
by: Susmann, Herbert, et al.
Published: (2024)
Hybrid Bernstein Normalizing Flows for Flexible Multivariate Density Regression with Interpretable Marginals
by: Arpogaus, Marcel, et al.
Published: (2025)
by: Arpogaus, Marcel, et al.
Published: (2025)
Bayesian Bridge Gaussian Process Regression
by: Xu, Minshen, et al.
Published: (2025)
by: Xu, Minshen, et al.
Published: (2025)
Shrinkage-Based Regressions with Many Related Treatments
by: Dilber, Enes, et al.
Published: (2025)
by: Dilber, Enes, et al.
Published: (2025)
Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows
by: Cabezas, Alberto, et al.
Published: (2024)
by: Cabezas, Alberto, et al.
Published: (2024)
Bayesian Multi-Group Functional Factor Models with Parameter-Expanded Cumulative Shrinkage Priors
by: Dai, Xuanye, et al.
Published: (2026)
by: Dai, Xuanye, et al.
Published: (2026)
FlowSDR: Sufficient Dimension Reduction via Conditional Normalizing Flows
by: Dong, Yuexiao, et al.
Published: (2026)
by: Dong, Yuexiao, et al.
Published: (2026)
The Group R2D2 Shrinkage Prior for Sparse Linear Models with Grouped Covariates
by: Yanchenko, Eric, et al.
Published: (2024)
by: Yanchenko, Eric, et al.
Published: (2024)
Energetic Variational Gaussian Process Regression for Computer Experiments
by: Kang, Lulu, et al.
Published: (2023)
by: Kang, Lulu, et al.
Published: (2023)
Correlated Bayesian Additive Regression Trees with Gaussian Process for Regression Analysis of Dependent Data
by: a, Xuetao Lu, et al.
Published: (2023)
by: a, Xuetao Lu, et al.
Published: (2023)
Estimating Complex Densities using Two-Stage Normalizing Flows
by: Darvishi, Roxana, et al.
Published: (2026)
by: Darvishi, Roxana, et al.
Published: (2026)
Bayesian Variable Selection on Small Sample Trial Data via Adaptive Posterior-Informed Shrinkage Prior
by: Kong, Lingxuan, et al.
Published: (2025)
by: Kong, Lingxuan, et al.
Published: (2025)
Order-based Structure Learning with Normalizing Flows
by: Kamkari, Hamidreza, et al.
Published: (2023)
by: Kamkari, Hamidreza, et al.
Published: (2023)
Laplace Approximations for Mixed-Effects and Gaussian Process Quantile Regression
by: Nava, Andrea, et al.
Published: (2026)
by: Nava, Andrea, et al.
Published: (2026)
Enhancing Forecasts Using Real-Time Data Flow and Hierarchical Forecast Reconciliation, with Applications to the Energy Sector
by: Neubauer, Lukas, et al.
Published: (2024)
by: Neubauer, Lukas, et al.
Published: (2024)
Bayesian Transfer Learning for High-Dimensional Linear Regression via Adaptive Shrinkage
by: Jamshidian, Parsa, et al.
Published: (2025)
by: Jamshidian, Parsa, et al.
Published: (2025)
Optimal Priors for the Discounting Parameter of the Normalized Power Prior
by: Shen, Yueqi, et al.
Published: (2023)
by: Shen, Yueqi, et al.
Published: (2023)
Repulsive g-Priors for Regression Mixtures
by: Hayashida, Yuta, et al.
Published: (2025)
by: Hayashida, Yuta, et al.
Published: (2025)
Shrinkage through multiple identifiability
by: Meixide, Carlos García, et al.
Published: (2026)
by: Meixide, Carlos García, et al.
Published: (2026)
Review of Recent Advances in Gaussian Process Regression Methods
by: Lyu, Chenyi, et al.
Published: (2024)
by: Lyu, Chenyi, et al.
Published: (2024)
Wrapped Gaussian Process Functional Regression Model for Batch Data on Riemannian Manifolds
by: Liu, Jinzhao, et al.
Published: (2024)
by: Liu, Jinzhao, et al.
Published: (2024)
Sensitivity Analysis to Unobserved Confounding with Copula-based Normalizing Flows
by: Balgi, Sourabh, et al.
Published: (2025)
by: Balgi, Sourabh, et al.
Published: (2025)
The Curious Problem of the Normal Inverse Mean: Robustness and Shrinkage
by: Ghosh, Soham, et al.
Published: (2024)
by: Ghosh, Soham, et al.
Published: (2024)
Probabilistically Plausible Counterfactual Explanations with Normalizing Flows
by: Wielopolski, Patryk, et al.
Published: (2024)
by: Wielopolski, Patryk, et al.
Published: (2024)
Block-Additive Gaussian Processes under Monotonicity Constraints
by: Deronzier, M., et al.
Published: (2024)
by: Deronzier, M., et al.
Published: (2024)
Wasserstein-type Gaussian Process Regressions for Input Measurement Uncertainty
by: Luo, Hengrui, et al.
Published: (2026)
by: Luo, Hengrui, et al.
Published: (2026)
Similar Items
-
The Dynamic Triple Gamma Prior as a Shrinkage Process Prior for Time-Varying Parameter Models
by: Knaus, Peter, et al.
Published: (2023) -
GRASP: Grouped Regression with Adaptive Shrinkage Priors
by: Tew, Shu Yu, et al.
Published: (2025) -
Locally Adaptive Bayesian Isotonic Regression using Half Shrinkage Priors
by: Okano, Ryo, et al.
Published: (2022) -
Dependency-Aware Shrinkage Priors for High Dimensional Regression
by: Aguilar, Javier Enrique, et al.
Published: (2025) -
Clustering Computer Mouse Tracking Data with Informed Hierarchical Shrinkage Partition Priors
by: Song, Ziyi, et al.
Published: (2024)