Roper, Taylor, Hakula, Harri, and Butler, Troy. A machine-learning enabled framework for quantifying uncertainties in parameters of computational models. Retrieved from https://par.nsf.gov/biblio/10627468. Computers & Mathematics with Applications 182.C Web. doi:10.1016/j.camwa.2025.01.030.

Roper, Taylor, Hakula, Harri, & Butler, Troy. A machine-learning enabled framework for quantifying uncertainties in parameters of computational models. Computers & Mathematics with Applications, 182 (C). Retrieved from https://par.nsf.gov/biblio/10627468. https://doi.org/10.1016/j.camwa.2025.01.030

Roper, Taylor, Hakula, Harri, and Butler, Troy. "A machine-learning enabled framework for quantifying uncertainties in parameters of computational models". Computers & Mathematics with Applications 182 (C). Country unknown/Code not available: Elsevier. https://doi.org/10.1016/j.camwa.2025.01.030. https://par.nsf.gov/biblio/10627468.

@article{osti_10627468,
place = {Country unknown/Code not available}, title = {A machine-learning enabled framework for quantifying uncertainties in parameters of computational models}, url = {https://par.nsf.gov/biblio/10627468}, DOI = {10.1016/j.camwa.2025.01.030}, abstractNote = {}, journal = {Computers & Mathematics with Applications}, volume = {182}, number = {C}, publisher = {Elsevier}, author = {Roper, Taylor and Hakula, Harri and Butler, Troy}, }