Class
Article
College
College of Engineering
Department
Mechanical and Aerospace Engineering Department
Faculty Mentor
Som Dutta
Presentation Type
Poster Presentation
Abstract
Neural Networks have surged to popularity in many fields because of their ability to model complex functions. However, for most scientists, this comes at the cost of interpretability.
The aim of this research is to compile the different methods to uncertainty quantification in Neural Networks and apply them to a CFD problem.
Location
Logan, UT
Start Date
4-9-2024 11:30 AM
End Date
4-9-2024 12:20 PM
Included in
Uncertainty Quantification in Neural Networks for CFD
Logan, UT
Neural Networks have surged to popularity in many fields because of their ability to model complex functions. However, for most scientists, this comes at the cost of interpretability.
The aim of this research is to compile the different methods to uncertainty quantification in Neural Networks and apply them to a CFD problem.