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20242026
most citedBayesian optimized deep ensemble for uncertainty quantification of deep neural networks: a system safety case study on sodium fast reactor thermal stratification modeling

1 citations · 1 across the 4 of their papers we have counts for

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cs.LG2026

Deploying Frontier Agentic Technology in MOOSEnger, a Multiphysics-Capable AI Assistant

Zaid Abulawi, Mengnan Li, Guillaume Giudicelli +2

The Multiphysics Object-Oriented Simulation Environment (MOOSE) is an open-source finite-element framework for building multiphysics simulation applications. Using a multiphysics e…

cs.LG2024★ 1 cited

Bayesian optimized deep ensemble for uncertainty quantification of deep neural networks: a system safety case study on sodium fast reactor thermal stratification modeling

Zaid Abulawi, Rui Hu, Prasanna Balaprakash +1

Accurate predictions and uncertainty quantification (UQ) are essential for decision-making in risk-sensitive fields such as system safety modeling. Deep ensembles (DEs) are efficie…