Generative ai for bayesian computation

NG Polson, V Sokolov - arXiv preprint arXiv:2305.14972, 2023 - arxiv.org
Bayesian Generative AI (BayesGen-AI) methods are developed and applied to Bayesian
computation. BayesGen-AI reconstructs the posterior distribution by directly modeling the …

Calibrating an ice sheet model using high-dimensional binary spatial data

W Chang, M Haran, P Applegate… - Journal of the American …, 2016 - Taylor & Francis
Rapid retreat of ice in the Amundsen Sea sector of West Antarctica may cause drastic sea
level rise, posing significant risks to populations in low-lying coastal regions. Calibration of …

Saving storage in climate ensembles: a model-based stochastic approach

H Huang, S Castruccio, AH Baker… - Journal of Agricultural …, 2023 - Springer
While climate models are an invaluable tool for increasing our understanding and therefore,
the predictability of the Earth's system for decades, their increase in complexity and …

High-fidelity hurricane surge forecasting using emulation and sequential experiments

M Plumlee, TG Asher, W Chang, MV Bilskie - 2021 - projecteuclid.org
High-fidelity hurricane surge forecasting using emulation and sequential experiments Page 1
The Annals of Applied Statistics 2021, Vol. 15, No. 1, 460–480 https://doi.org/10.1214/20-AOAS1398 …

[HTML][HTML] Reproducing internal variability with few ensemble runs

S Castruccio, Z Hu, B Sanderson… - Journal of …, 2019 - journals.ametsoc.org
Reproducing Internal Variability with Few Ensemble Runs in: Journal of Climate Volume 32 Issue
24 (2019) Jump to Content Jump to Main Navigation Logo Logo Logo Logo Logo Logo …

A fast particle-based approach for calibrating a 3-D model of the Antarctic ice sheet

BS Lee, M Haran, RW Fuller, D Pollard… - The Annals of Applied …, 2020 - JSTOR
We consider the scientifically challenging and policy-relevant task of understanding the past
and projecting the future dynamics of the Antarctic ice sheet. The Antarctic ice sheet has …

[HTML][HTML] Monthly rainfall-runoff modeling at watershed scale: A comparative study of data-driven and theory-driven approaches

W Chang, X Chen - Water, 2018 - mdpi.com
Data-driven machine learning approaches have been rapidly developed in the past 10 to 20
years and applied to various problems in the field of hydrology. To investigate the capability …

Constructing a simulation surrogate with partially observed output

MYH Chan, M Plumlee, SM Wild - Technometrics, 2024 - Taylor & Francis
Gaussian process surrogates are a popular alternative to directly using computationally
expensive simulation models. When the simulation output consists of many responses …

[HTML][HTML] Spatial probabilistic calibration of a high-resolution Amundsen Sea Embayment ice sheet model with satellite altimeter data

A Wernecke, TL Edwards, IJ Nias, PB Holden… - The …, 2020 - tc.copernicus.org
Probabilistic predictions of the sea level contribution from Antarctica often have large
uncertainty intervals. Calibration of model simulations with observations can reduce …

[HTML][HTML] Exploration of diverse solutions for the calibration of imperfect climate models

S Peatier, BM Sanderson, L Terray - Earth System Dynamics, 2024 - esd.copernicus.org
The calibration of Earth system model parameters is subject to data, time, and computational
constraints. The high dimensionality of this calibration problem, combined with errors arising …