[HTML][HTML] Probabilistic forecast of nonlinear dynamical systems with uncertainty quantification
Data-driven modeling is useful for reconstructing nonlinear dynamical systems when the
underlying process is unknown or too expensive to compute. Having reliable uncertainty …
underlying process is unknown or too expensive to compute. Having reliable uncertainty …
High-fidelity hurricane surge forecasting using emulation and sequential experiments
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 …
The Annals of Applied Statistics 2021, Vol. 15, No. 1, 460–480 https://doi.org/10.1214/20-AOAS1398 …
Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under conditions of high ice-shelf basal melt
Antarctica's Lambert Glacier drains about one-sixth of the ice from the East Antarctic Ice
Sheet and is considered stable due to the strong buttressing provided by the Amery Ice …
Sheet and is considered stable due to the strong buttressing provided by the Amery Ice …
Quantifying spatio-temporal boundary condition uncertainty for the North American deglaciation
Ice sheet models are used to study the deglaciation of North America at the end of the last
ice age (past 21,000 years), so that we might understand whether and how existing ice …
ice age (past 21,000 years), so that we might understand whether and how existing ice …
A Personalized Dose‐Finding Algorithm Based on Adaptive Gaussian Process Regression
Dose‐finding studies play a crucial role in drug development by identifying the optimal dose
(s) for later studies while considering tolerability. This not only saves time and effort in …
(s) for later studies while considering tolerability. This not only saves time and effort in …
RobustCalibration: Robust Calibration of Computer Models in R
M Gu - arXiv preprint arXiv:2201.01476, 2022 - arxiv.org
Two fundamental research tasks in science and engineering are forward predictions and
data inversion. This article introduces a recent R package RobustCalibration for Bayesian …
data inversion. This article introduces a recent R package RobustCalibration for Bayesian …
Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under high ice-shelf basal melt conditions
Antarctica's Lambert Glacier drains about one-sixth of the ice from the East Antarctica Ice
Sheet and is considered stable due to the strong buttressing provided by the Amery Ice …
Sheet and is considered stable due to the strong buttressing provided by the Amery Ice …
Bayesian calibration of a flood simulator using binary flood extent observations
M Balbi, DCB Lallemant - EGUsphere, 2022 - egusphere.copernicus.org
Computational simulators of complex physical processes, such as inundations, require a
robust characterization of the uncertainties involved to be useful for flood hazard and risk …
robust characterization of the uncertainties involved to be useful for flood hazard and risk …