Cover Image

Data-Efficient Generative Modeling of Non-Gaussian Global Climate Fields via Scalable Composite Transformations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Brachem, Johannes, Wiemann, Paul F. V., Katzfuss, Matthias
Format:	Preprint
Published:	2026
Subjects:	Methodology Applications
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Bayesian Penalized Transformation Models: Structured Additive Location-Scale Regression for Arbitrary Conditional Distributions
by: Brachem, Johannes, et al.
Published: (2024)

Generative multi-scale modeling and downscaling via spatial autoregressive transport maps
by: Calle-Saldarriaga, Alejandro, et al.
Published: (2025)

Bayesian structured additive quantile regression for inflated bounded data
by: Queiroz, Francisco F., et al.
Published: (2026)

Gridding and Parameter Expansion for Scalable Latent Gaussian Models of Spatial Multivariate Data
by: Peruzzi, Michele, et al.
Published: (2021)

Combined Quantile Forecasting for High-Dimensional Non-Gaussian Data
by: Park, Seeun, et al.
Published: (2024)

Soil Texture Prediction with Bayesian Generalized Additive Models for Spatial Compositional Data
by: Martínez-Minaya, Joaquín, et al.
Published: (2025)

Composite Dyadic Models for Spatio-Temporal Data
by: Schwob, Michael R, et al.
Published: (2023)

Spatiotemporal Autoregressive Models for Areal Compositional Data
by: Eckardt, Matthias, et al.
Published: (2025)

Assessing Climate-Driven Mortality Risk: A Stochastic Approach with Distributed Lag Non-Linear Models
by: Min, Jiacheng, 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)

Scalable Fitting Methods for Multivariate Gaussian Additive Models with Covariate-dependent Covariance Matrices
by: Gioia, Vincenzo, et al.
Published: (2025)

Scalable Scalar-on-Image Cortical Surface Regression with a Relaxed-Thresholded Gaussian Process Prior
by: Menacher, Anna, et al.
Published: (2024)

Spatial Hyperspheric Models for Compositional Data
by: Schwob, Michael R., et al.
Published: (2024)

Graphical Transformation Models
by: Herp, Matthias, et al.
Published: (2025)

Learning non-Gaussian spatial distributions via Bayesian transport maps with parametric shrinkage
by: Chakraborty, Anirban, et al.
Published: (2024)

Integrating Complex Covariate Transformations in Generalized Additive Models
by: Collarin, Claudia, et al.
Published: (2025)

Capturing Aleatoric Uncertainty in Climate Models
by: Gruber, Cornelia, et al.
Published: (2026)

Bayesian Bootstrap based Gaussian Copula Model for Mixed Data with High Missing Rates
by: Kim, Seongmin, et al.
Published: (2025)

Modeling Zero-Inflated Correlated Dental Data through Gaussian Copulas and Approximate Bayesian Computation
by: Mukherjee, Anish, et al.
Published: (2024)

Rethinking Climate Econometrics: Data Cleaning, Flexible Trend Controls, and Predictive Validation
by: Schötz, Christof, et al.
Published: (2025)

What Influences the Field Goal Attempts of Professional Players? Analysis of Basketball Shot Charts via Log Gaussian Cox Processes with Spatially Varying Coefficients
by: Cao, Jiahao, et al.
Published: (2025)

Spatially Regularized Gaussian Mixtures for Clustering Spatial Transcriptomic Data
by: Sottosanti, Andrea, et al.
Published: (2025)

Generative Bayesian Computation as a Scalable Alternative to Gaussian Process Surrogates
by: Polson, Nick, et al.
Published: (2026)

cardinalR: Generating Interesting High-Dimensional Data Structures
by: Gamage, Jayani P., et al.
Published: (2025)

Multi-state Models For Disease Histories Based On Longitudinal Data
by: Wiegrebe, Simon, et al.
Published: (2025)

Temporal Models for Demographic and Global Health Outcomes in Multiple Populations: Introducing the Normal-with-Optional-Shrinkage Data Model Class
by: Alkema, Leontine, et al.
Published: (2024)

Scalable Causal Structure Learning via Amortized Conditional Independence Testing
by: Leiner, James, et al.
Published: (2023)

Spatial-temporal prediction of forest attributes using latent Gaussian models and inventory data
by: May, Paul B., et al.
Published: (2025)

Scalable Bayesian Semiparametric Additive Regression Models For Microbiome Studies
by: Chen, Tinghua, et al.
Published: (2024)

An Interpretable Single-Index Mixed-Effects Model for Non-Gaussian National Survey Data
by: Liu, Qingyang, et al.
Published: (2025)

Large Wave Direction Data Modeling Using Wrapped Spatial Gaussian Markov Random Fields
by: Hazra, Arnab
Published: (2026)

Heterogeneous Clinical Trial Outcomes via Multi-Output Gaussian Processes
by: Thomas, Owen, et al.
Published: (2024)

An Efficient Two-Dimensional Functional Mixed-Effect Model Framework for Repeatedly Measured Functional Data
by: Cao, Cheng, et al.
Published: (2024)

VT-MRF-SPF: Variable Target Markov Random Field Scalable Particle Filter
by: Ning, Ning
Published: (2024)

Efficient Generative Modeling via Penalized Optimal Transport Network
by: Lu, Wenhui Sophia, et al.
Published: (2024)

Multiscale Topological Inference for Marked Point Processes via Euler Characteristic Envelopes
by: Eckardt, Matthias, et al.
Published: (2026)

Effective Degrees of Freedom for Balanced Repeated Replication and Paired Jackknife Variance Estimates: A Unified Approach via Stratum Contrasts
by: von Davier, Matthias
Published: (2026)

Generalized Heterogeneous Functional Model with Applications to Large-scale Mobile Health Data
by: Sun, Xiaojing, et al.
Published: (2025)

Bayesian Image-on-Image Regression via Deep Kernel Learning based Gaussian Processes
by: Ma, Guoxuan, et al.
Published: (2023)

A Gaussian Process Model for Ordinal Data with Applications to Chemoinformatics
by: Gosnell, Arron, et al.
Published: (2024)