Results 101 to 110 of about 3,213,103 (353)

A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges [PDF]

Information Fusion, 2020
Moloud Abdar, Farhad Pourpanah, Sadiq Hussain, Dana Rezazadegan, Li Liu, M. Ghavamzadeh, P. Fieguth, Xiaochun Cao, A. Khosravi, U. R. Acharya, V. Makarenkov, S. Nahavandi   +11 more
semanticscholar   +1 more source

Efficient Calculation of Uncertainty Quantification [PDF]

, 2014
We consider Uncertainty Quantification (UQ) by expanding the solution in so-called generalized Polynomial Chaos expansions. In these expansions the solution is decomposed into a series with orthogonal polynomials in which the parameter dependency becomes an argument of the orthogonal polynomial basis functions.
Maten, ter, E.J.W., Pulch, R., Schilders, W.H.A., Janssen, H.H.J.M.   +3 more
openaire   +2 more sources

Plasma Proteomic Signatures for Alzheimer's Disease: Comparable Accuracy to ATN Biomarkers and Cross‐Platform Validation

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background There is growing recognition of the potential of plasma proteomics for Alzheimer's Disease (AD) risk assessment and disease characterization. However, differences between proteomics platforms introduce uncertainties regarding cross‐platform applicability.
Manyue Hu, Oliver Robinson, Christina M. Lill, Anna Matton, Raquel Puerta, Pilar Sanz, Merce Boada, Agustín Ruiz, Lefkos Middleton, for the Alzheimer's Disease Neuroimaging Initiative   +9 more
wiley   +1 more source

Uncertainty Quantification in Mineral Resource Estimation

Natural Resources Research
Mineral resources are estimated to establish potential orebody with acceptable quality (grade) and quantity (tonnage) to validate investment. Estimating mineral resources is associated with uncertainty from sampling, geological heterogeneity, shortage of
O. Lindi, A. Aladejare, Toochukwu Ozoji, J. Ranta   +3 more
semanticscholar   +1 more source

Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification

, 2018
A massively parallel method to build large transition rate matrices from temperature accelerated molecular dynamics trajectories is presented. Bayesian Markov model analysis is used to estimate the expected residence time in the known state space ...
Perez, Danny, Swinburne, Thomas D
core   +3 more sources

Frailty Exacerbates Disability in Progressive Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background To evaluate frailty in severe progressive multiple sclerosis (PMS) and to investigate the underlying mechanisms. Methods This prospective, cross‐sectional, multicenter study enrolled a late severe PMS group requiring skilled nursing (n = 53) and an age, sex, and disease duration‐matched control PMS group (n = 53).
Taylor R. Wicks, Anna Wolska, Diala Ghazal, Dejan Jakimovski, Bianca Weinstock‐Guttman, Alexander Burnham, Niels Bergsland, Michael G. Dwyer, Alan T. Remaley, Robert Zivadinov, Murali Ramanathan   +10 more
wiley   +1 more source

Dakota A Multilevel Parallel Object-Oriented Framework for Design Optimization Parameter Estimation Uncertainty Quantification and Sensitivity Analysis: Version 6.14 User's Manual.

, 2020
The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling ...
B. Adams, W. Bohnhoff, K. Dalbey, Mohamed S. Ebeida, John P. Eddy, M. Eldred, Russell Hooper, P. Hough, Kenneth T. Hu, J. Jakeman, Mohammad Khalil, Kathryn Maupin, Jason Monschke, Elliott Ridgway, A. Rushdi, Daniel Seidl, John Stephens, J. Winokur   +17 more
semanticscholar   +1 more source

Exploratory Analysis of ELP1 Expression in Whole Blood From Patients With Familial Dysautonomia

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Familial dysautonomia (FD) is a hereditary neurodevelopmental disorder caused by aberrant splicing of the ELP1 gene, leading to a tissue‐specific reduction in ELP1 protein expression. Preclinical models indicate that increasing ELP1 levels can mitigate disease manifestations.
Alejandra González‐Duarte, Lucy Norcliffe‐Kaufmann, Maria Luisa Cotrina, Zenith Khan, Kaia Dalamo, Patricio Millar Vernetti, Matthew Lawless, Elisabetta Morini, Monica Salani, Marla Weetall, Jana Narasimhan, Agostino G. Rocha, Susan A. Slaugenhaupt, Horacio Kaufmann   +13 more
wiley   +1 more source

Uncertainty quantification by large language models

Machine Learning with Applications
As reasoning capabilities of large language models (LLMs) continue to advance, they are being integrated into increasingly complex scientific workflows, with the goal of developing agents capable of generating evidence-based explanations and testing ...
Dorianis M. Perez, Bryan E. Kaiser, Ismael Boureima   +2 more
doaj   +1 more source

Learning to quantify uncertainty in off-target activity for CRISPR guide RNAs [PDF]

, 2023
Furkan Özden, Péter Mináry
openalex   +1 more source