Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Husseini, Jamal F."'
This paper investigates the use of probabilistic neural networks (PNNs) to model aleatoric uncertainty, which refers to the inherent variability in the input-output relationships of a system, often characterized by unequal variance or heteroscedastic
Externí odkaz:
http://arxiv.org/abs/2402.13945
Autor:
Pourkamali-Anaraki, Farhad, Husseini, Jamal F., Pineda, Evan J., Bednarcyk, Brett A., Stapleton, Scott E.
This paper introduces a novel two-stage machine learning-based surrogate modeling framework to address inverse problems in scientific and engineering fields. In the first stage of the proposed framework, a machine learning model termed the "learner"
Externí odkaz:
http://arxiv.org/abs/2401.02008
Autor:
Husseini, Jamal F.1 (AUTHOR) jamal_husseini@student.uml.edu, Pineda, Evan J.2 (AUTHOR) evan.j.pineda@nasa.gov, Stapleton, Scott E.1 (AUTHOR) scott_stapleton@uml.edu
Publikováno v:
Materials (1996-1944). Jul2024, Vol. 17 Issue 14, p3411. 14p.
Publikováno v:
In Composites Part A January 2023 164