Approximate Methods for Bayesian Computation
RV Craiu, E Levi - Annual Review of Statistics and Its Application, 2023 - annualreviews.org
Rich data generating mechanisms are ubiquitous in this age of information and require
complex statistical models to draw meaningful inference. While Bayesian analysis has seen …
complex statistical models to draw meaningful inference. While Bayesian analysis has seen …
Surge-NF: Neural Fields inspired peak storm surge surrogate modeling with multi-task learning and positional encoding
Storm surges pose a significant threat to coastal communities, necessitating rapid and
precise storm surge prediction methods for long-time risk assessment and emergency …
precise storm surge prediction methods for long-time risk assessment and emergency …
[HTML][HTML] A novel hybrid machine learning model for rapid assessment of wave and storm surge responses over an extended coastal region
Storm surge and waves are responsible for a substantial portion of tropical and extratropical
cyclones-related damages. While high-fidelity numerical models have significantly …
cyclones-related damages. While high-fidelity numerical models have significantly …
Spatio-temporal storm surge emulation using Gaussian Process techniques
AP Kyprioti, C Irwin, AA Taflanidis… - Coastal …, 2023 - Elsevier
Surrogate models (also referenced as metamodels) are recognized as powerful, data-
driven, predictive tools for the approximation (emulation) of storm surge. For this application …
driven, predictive tools for the approximation (emulation) of storm surge. For this application …
Improvements in storm surge surrogate modeling for synthetic storm parameterization, node condition classification and implementation to small size databases
Surrogate models are becoming increasingly popular for storm surge predictions. Using
existing databases of storm simulations, developed typically during regional flood studies …
existing databases of storm simulations, developed typically during regional flood studies …
Adaptive multi-fidelity Monte Carlo for real-time probabilistic storm surge predictions
Real-time, probabilistic predictions of the expected storm surge represent an important
information source for guiding emergency response decisions during landfalling tropical …
information source for guiding emergency response decisions during landfalling tropical …
Real-time simulated storm surge predictions during Hurricane Michael (2018)
MV Bilskie, TG Asher, PW Miller… - Weather and …, 2022 - journals.ametsoc.org
Storm surge caused by tropical cyclones can cause overland flooding and lead to loss of life
while damaging homes, businesses, and critical infrastructure. In 2018, Hurricane Michael …
while damaging homes, businesses, and critical infrastructure. In 2018, Hurricane Michael …
The zero problem: Gaussian process emulators for range-constrained computer models
ET Spiller, RL Wolpert, P Tierz, TG Asher - SIAM/ASA Journal on Uncertainty …, 2023 - SIAM
We introduce a zero-censored Gaussian process as a systematic, model-based approach to
building Gaussian process emulators for range-constrained simulator output. This approach …
building Gaussian process emulators for range-constrained simulator output. This approach …
Constructing a simulation surrogate with partially observed output
Gaussian process surrogates are a popular alternative to directly using computationally
expensive simulation models. When the simulation output consists of many responses …
expensive simulation models. When the simulation output consists of many responses …
Advancing Spatio-temporal Storm Surge Prediction with Hierarchical Deep Neural Networks
Coastal regions in North America face major threats from storm surges caused by hurricanes
and nor'easters. Traditional numerical models, while accurate, are computationally …
and nor'easters. Traditional numerical models, while accurate, are computationally …