Quantifying the survival uncertainty of Wolbachia-infected mosquitoes in a spatial model by Martin Strugarek, Nicolas Vauchelet, Jorge P. Zubelli

Subjects: Get full text

Cloudy with a chance of uncertainty: autoconversion rates forecasting via evidential regression from satellite data – CORRIGENDUM by Maria Carolina Novitasari, Johannes Quaas, Miguel R. D. Rodrigues

Subjects: Get full text

Bayesian Inference and Global Sensitivity Analysis for Ambient Solar Wind Prediction by Opal Issan, Pete Riley, Enrico Camporeale, Boris Kramer

Subjects: Get full text

Ensemble Modeling of Radiation Belt Electron Flux Decay Following a Geomagnetic Storm: Dependence on Key Input Parameters by Man Hua, Jacob Bortnik, Adam C. Kellerman, Enrico Camporeale, Qianli Ma

Subjects: Get full text

Multi‐Hour‐Ahead Dst Index Prediction Using Multi‐Fidelity Boosted Neural Networks by A. Hu, E. Camporeale, B. Swiger

Subjects: Get full text

A Surrogate Model for Studying Solar Energetic Particle Transport and the Seed Population by Atilim Guneş Baydin, Bala Poduval, Nathan A. Schwadron

Subjects: Get full text

On the Measurement of Laser Lines in 3D Space with Uncertainty Estimation by Ivan De Boi, Nasser Ghaderi, Steve Vanlanduit, Rudi Penne

Subjects: Get full text

Multi-level uncertain fatigue analysis of a truss under incomplete available information by R. B. P. Nonato

Subjects: Get full text

Data-driven upper bounds and event attribution for unprecedented heatwaves by Mark D. Risser, Likun Zhang, Michael F. Wehner

Subjects: Get full text

Exploration of deep-learning-based dose rate estimation model for a large-volume plastic scintillation detector by Byoungil Jeon, Jisung Hwang, Myungkook Moon

Subjects: Get full text

Uncertainty-Aware Multimodal Trajectory Prediction via a Single Inference from a Single Model by Ho Suk, Shiho Kim

Subjects: “…uncertainty quantification…”
Get full text

A Martingale-Free Introduction to Conditional Gaussian Nonlinear Systems by Marios Andreou, Nan Chen

Subjects: Get full text

Best-Estimate Plus Uncertainty Framework for Multiscale, Multiphysics Light Water Reactor Core Analysis by Jason Hou, Maria Avramova, Kostadin Ivanov

“…Similarly, the uncertainty quantification on thermal-hydraulic models is established on a relatively small scale, while these results will be used in Phase III at the core scale, sometimes with different codes or models. …”
Get full text

Aggregating multiple test results to improve medical decision-making. by Lucas Böttcher, Maria R D'Orsogna, Tom Chou

“…We also provide the corresponding uncertainty quantification.…”
Get full text

Adversarial confound regression and uncertainty measurements to classify heterogeneous clinical MRI in Mass General Brigham. by Matthew Leming, Sudeshna Das, Hyungsoon Im

“…By combining MUCRAN and the uncertainty quantification method, we showed consistent and significant increases in the AD detection accuracy for newly collected MGH data (post-2019; 84.6% with MUCRAN vs. 72.5% without MUCRAN) and for data from other hospitals (90.3% from Brigham and Women's Hospital and 81.0% from other hospitals). …”
Get full text

Smolyak-Grid-Based Flutter Analysis with the Stochastic Aerodynamic Uncertainty by Yuting Dai, Chao Yang

“…Afterwards, the methodology for flutter uncertainty quantification due to aerodynamic perturbation was developed, based on the nonintrusive polynomial chaos expansion theory. …”
Get full text

Time-Dependent Reliability-Based Design Optimization Utilizing Nonintrusive Polynomial Chaos by Yao Wang, Shengkui Zeng, Jianbin Guo

“…Polynomial chaos combined with the moving least squares (PCMLS) is presented as a nonintrusive time-dependent surrogate model to conduct uncertainty quantification. Wear is considered to be a critical failure that deteriorates the kinematic reliability and the structural reliability through the changing kinematics. …”
Get full text

Exploring parameter dependence of atomic minima with implicit differentiation by Ivan Maliyov, Petr Grigorev, Thomas D. Swinburne

“…Forward propagation of parameter variation is key for uncertainty quantification, whilst backpropagation has found application for emerging inverse problems such as fine-tuning or targeted design. …”
Get full text

A software tool for applying Bayes' theorem in medical diagnostics by Theodora Chatzimichail, Aristides T. Hatjimihail

“…It provides a framework for their uncertainty quantification and assists in understanding and applying Bayes' theorem in medical diagnostics.…”
Get full text

On Generalized Additive Models for Representation of Solar EUV Irradiance by Daniel A. Brandt, Erick F. Vega, Aaron J. Ridley

“…Abstract In the context of space weather forecasting, solar EUV irradiance specification is needed on multiple time scales, with associated uncertainty quantification for determining the accuracy of downstream parameters. …”
Get full text