Results 41 to 50 of about 110,431 (303)

UNCERTAINTY QUANTIFICATION IN THE CLOUD WITH UQCLOUD [PDF]

Proceedings of the 4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2019), 2021
General-purpose uncertainty quantification software has become a well established requirement in modern engineering workflows. Different communities (e.g. applied maths, engineering, economics, etc.), however, generally employ diverse arrays of technologies and workflows, from computing infrastructure to programming languages. To overcome the intrinsic
Lataniotis, Christos, Marelli, Stefano, Sudret, Bruno   +2 more
openaire   +1 more source

Uncertainty quantification in DenseNet model using myocardial infarction ECG signals

, 2023
Background and objective: Myocardial infarction (MI) is a life-threatening condition diagnosed acutely on the electrocardiogram (ECG). Several errors, such as noise, can impair the prediction of automated ECG diagnosis.
Oh, Shu Lih, Ng, Eddie Yin Kwee, Jahmunah, V, Acharya, U. Rajendra, Ng, E.Y.K., Jahmunah, V., Tan, Ru-San   +6 more
core   +1 more source

Uncertainty quantification for multiphase flow [PDF]

, 2021
The purview of this thesis is insight into, and development of, methods for uncertainty quantification in multiphase flow. The work is directed towards commercial simulators for transport of gas and liquid in pipelines and the primary quantities of ...
Strand, Andreas
core   +1 more source

An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change [PDF]

Earth System Dynamics
This 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, M. Perego, D. T. Seidl, T. A. Hartland, T. R. Hillebrand, M. J. Hoffman, S. F. Price   +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, Jasper Snoek, Andrew L. Beam   +2 more
doaj   +1 more source

Application of uncertainty quantification to artificial intelligence in healthcare: A review of last decade (2013–2023) [PDF]

, 2023
: Uncertainty estimation in healthcare involves quantifying and understanding the inherent uncertainty or variability associated with medical predictions, diagnoses, and treatment outcomes.
Barua, Prabal Datta, Vicnesh Jahmunah, Filippo Molinari, Silvia Seoni, Salvi, Massimo, U. Rajendra Acharya, Molinari, Filippo, Seoni, Silvia, Jahmunah, Vicnesh, Prabal Datta Barua, Acharya, U Rajendra, Acharya, U. Rajendra, Massimo Salvi   +12 more
core   +1 more source

Automated 3D cytoplasm segmentation in soft X-ray tomography

iScience
Summary: 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, Philipp D. Lösel, Vincent Heuveline, Venera Weinhardt   +3 more
doaj   +1 more source

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE

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, Alper Yegenoglu, Emiliano Torre, Emiliano Torre, Dominik M. Endres, Sonja Grün, Sonja Grün   +6 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, F. M. Nunes, M. Plumlee, S. M. Wild   +3 more
openaire   +4 more sources

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 , Hamer, Waldt , Vosloo, Jan   +2 more
doaj   +1 more source