4 citations · 5 across the 5 of their papers we have counts for
5 papers
Active operator learning with predictive uncertainty quantification for partial differential equations
Nick Winovich, Mitchell Daneker, Lu Lu +1
With the increased prevalence of neural operators being used to provide rapid solutions to partial differential equations (PDEs), understanding the accuracy of model predictions an…
ADEPT: A Noninvasive Method for Determining Elastic Parameters of Valve Tissue
Wensi Wu, Mitchell Daneker, Christian Herz +5
Computer simulation of "virtual interventions" may inform optimal valve repair for a given patient prior to intervention. However, the paucity of noninvasive methods to determine i…
Identifying heterogeneous micromechanical properties of biological tissues via physics-informed neural networks
Wensi Wu, Mitchell Daneker, Kevin T. Turner +2
The heterogeneous micromechanical properties of biological tissues have profound implications across diverse medical and engineering domains. However, identifying full-field hetero…
Effective Data Sampling Strategies and Boundary Condition Constraints of Physics-Informed Neural Networks for Identifying Material Properties in Solid Mechanics
Wensi Wu, Mitchell Daneker, Matthew A. Jolley +2
Material identification is critical for understanding the relationship between mechanical properties and the associated mechanical functions. However, material identification is a…
Systems Biology: Identifiability analysis and parameter identification via systems-biology informed neural networks
Mitchell Daneker, Zhen Zhang, George Em Karniadakis +1
The dynamics of systems biological processes are usually modeled by a system of ordinary differential equations (ODEs) with many unknown parameters that need to be inferred from no…