Results 31 to 40 of about 85,322 (257)
Complex model calibration through emulation, a worked example for a stochastic epidemic model
Epidemics, 2022 Uncertainty quantification is a formal paradigm of statistical estimation that aims to account for all uncertainties inherent in the modelling process of real-world complex systems. The methods are directly applicable to stochastic models in epidemiology,
Michael Dunne +12 more
doaj +1 more source
An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change [PDF]
Earth System DynamicsThis study investigated the computational benefits of using multi-fidelity statistical estimation (MFSE) algorithms to quantify uncertainty in the mass change of Humboldt Glacier, Greenland, between 2007 and 2100 using a single climate change scenario ...
J. D. Jakeman +6 more
doaj +1 more source
Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures
Entropy, 2021 Uncertainty quantification for complex deep learning models is increasingly important as these techniques see growing use in high-stakes, real-world settings.
Benjamin Kompa +2 more
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Automated 3D cytoplasm segmentation in soft X-ray tomography
iScienceSummary: Cells’ structure is key to understanding cellular function, diagnostics, and therapy development. Soft X-ray tomography (SXT) is a unique tool to image cellular structure without fixation or labeling at high spatial resolution and throughput ...
Ayse Erozan +3 more
doaj +1 more source
Uncertainty quantification in breakup reactions
Physical Review C, 2022 Breakup reactions are one of the favored probes to study loosely bound nuclei, particularly those in the limit of stability forming a halo. In order to interpret such breakup experiments, the continuum discretized coupled channel method is typically used. In this study, the first Bayesian analysis of a breakup reaction model is performed.
Ö. Sürer +3 more
openaire +4 more sources
Frontiers in Computational Neuroscience, 2017 Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs).
Pietro Quaglio +6 more
doaj +1 more source
STRUCTURING UNCERTAINTY MANAGEMENT FOR ENERGY SAVINGS CALCULATIONS
South African Journal of Industrial Engineering, 2019 South Africa has committed itself to reducing its greenhouse gas emissions. A key strategy to minimise the greenhouse gas intensity involves using incentivised energy efficiency initiatives.
Johnson, Kristin +2 more
doaj +1 more source
Automated Monte Carlo-based quantification and updating of geological uncertainty with borehole data (AutoBEL v1.0) [PDF]
Geoscientific Model Development, 2020 Geological uncertainty quantification is critical to subsurface modeling and prediction, such as groundwater, oil or gas, and geothermal resources, and needs to be continuously updated with new data.
Z. Yin, S. Strebelle, J. Caers
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction The use of herbal medical preparation (HMP) is rising among pediatric oncology patients, often to manage treatment‐related symptoms. Their effectiveness remains uncertain, and the risk of herb–drug interactions is underestimated.
Orianne Mahot +6 more
wiley +1 more source
Principal component density estimation for scenario generation using normalizing flows
Data-Centric Engineering, 2022 Neural networks-based learning of the distribution of non-dispatchable renewable electricity generation from sources, such as photovoltaics (PV) and wind as well as load demands, has recently gained attention.
Eike Cramer +3 more
doaj +1 more source