3 papers
cs.LG2023
On Active Learning for Gaussian Process-based Global Sensitivity Analysis
Mohit Chauhan, Mariel Ojeda-Tuz, Ryan Catarelli +3
This paper explores the application of active learning strategies to adaptively learn Sobol indices for global sensitivity analysis. We demonstrate that active learning for Sobol i…
physics.data-an2023
Learning thermodynamically constrained equations of state with uncertainty
Himanshu Sharma, Jim A. Gaffney, Dimitrios Tsapetis +1
Numerical simulations of high energy-density experiments require equation of state (EOS) models that relate a material's thermodynamic state variables -- specifically pressure, vol…
cs.SE2023
UQpy v4.1: Uncertainty Quantification with Python
Dimitrios Tsapetis, Michael D. Shields, Dimitris G. Giovanis +9
This paper presents the latest improvements introduced in Version 4 of the UQpy, Uncertainty Quantification with Python, library. In the latest version, the code was restructured t…