Hypercomplex Automatic Differentiation Uncertainty Quantification (HYPAD-UQ) in Hydrocode Simulations
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Results for “Uncertainty quantification”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Uncertainty Quantification and Calibration of the E3SM Land Model using an Embedded Model Error Approach
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Iyengar, Nikhil [Sandia National Laboratories (SNL↗
Uncertainty Quantification of Mechanical Damage in Carbon-Carbon Composites
Investigates the effect of changing input parameters and analyze the variation in macroscopic and microscopic damage behavior.
Skweres, Sean Braddock [Sandia National Laboratori↗
Uncertainty Quantification of Neural Network Models via Langevin Sampling
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Safta, Cosmin [Sandia National Laboratories (SNL-C↗
Uncertainty Quantification in Computational Science: from Physical Models to Neural Networks
Tutorial at the upcoming BIRS workshop https://www.birs.ca/events/2025/5-day-workshops/25w5381/schedule
Sargsyan, Khachik [Sandia National Laboratories (S↗
Panel: Shared Opportunities in Uncertainty Quantification in Support of CFD Validation
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Lance, Blake [Sandia National Laboratories (SNL-NM↗
Reduced-Basis Methods for Uncertainty Quantification with application to High-Speed Flows
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Blonigan, Patrick Joseph [Sandia National Laborato↗
Final Technical Report: Probabilistic Learning, Dimension Reduction, and Spectral Representations for High-Dimensional Uncertainty Quantification
Final Technical Report
Ghanem, Roger [University of Southern California] ↗
Uncertainty Quantification of Transport coefficient datasets in simulations of warm dense matter
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Stanek, Lucas James [Sandia National Laboratories ↗
Monte Carlo uncertainty quantification and sensitivity analysis for the C5G7 benchmark
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Clements, Kayla [Oregon State University ]↗
NeurAM: nonlinear dimensionality reduction for uncertainty quantification through neural active manifolds
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Schiavazzi, Daniele [University of Notre Dame]↗
Stein variational inference and sparsification for uncertainty quantification of physical neural networks
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Jones, Reese Edward [Sandia National Laboratories ↗
Beyond Point Estimates: Benchmarking Uncertainty Quantification Methods on the AION-1 Astronomical Foundation Model
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Narvaez, Karla Tame [Fermilab] (ORCID:000000022249↗
Evaluating Fastener Joint Performance: Advances in Modeling and Uncertainty Quantification From the Sandia Mechanics Challenge
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Mersch, John Philip [Sandia National Laboratories ↗
Neural operators for accelerated uncertainty quantification in ice-sheet modeling
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Perego, Mauro [Sandia National Laboratories (SNL-N↗
Advancing Nuclear Data Uncertainty Quantification: EMU and Machine Learning
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Astronomy and AstroPhysics↗
Latent trajectory analysis for uncertainty quantification in generative AI
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Krofcheck, Daniel Joseph [Sandia National Laborato↗
Separable Uncertainty Quantification in Materials Experiments with Variational Deep Material Networks
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Robertson, Andreas Euan [Sandia National Laborator↗