18 citations · 33 across the 5 of their papers we have counts for
5 papers
Bayesian calibration of interatomic potentials for binary alloys
Arun Hegde, Elan Weiss, Wolfgang Windl +2
Developing reliable interatomic potential models with quantified predictive accuracy is crucial for atomistic simulations. Commonly used potentials, such as those constructed throu…
Representing Model Discrepancy in Bound-to-Bound Data Collaboration
Wenyu Li, Arun Hegde, James Oreluk +2
We extended the existing methodology in Bound-to-Bound Data Collaboration (B2BDC), an optimization-based deterministic uncertainty quantification (UQ) framework, to explicitly take…
Diagnostics of Data-Driven Models: Uncertainty Quantification of PM7 Semi-Empirical Quantum Chemical Method
James Oreluk, Zhenyuan Liu, Arun Hegde +4
We report an evaluation of a semi-empirical quantum chemical method PM7 from the perspective of uncertainty quantification. Specifically, we apply Bound-to-Bound Data Collaboration…
Consistency Analysis for Massively Inconsistent Datasets in Bound-to-Bound Data Collaboration
Arun Hegde, Wenyu Li, James Oreluk +2
Bound-to-Bound Data Collaboration (B2BDC) provides a natural framework for addressing both forward and inverse uncertainty quantification problems. In this approach, QOI (quantity…
Scale-Bridging Model Development for Coal Particle Devolatilization
Benjamin B Schroeder, Sean T Smith, Philip J Smith +6
When performing large-scale, high-performance computations of multi-physics applications, it is common to limit the complexity of physics sub-models comprising the simulation. For…