19 citations · 19 across the 3 of their papers we have counts for
5 papers
Gaussian Process Regression constrained by Boundary Value Problems
Mamikon Gulian, Ari Frankel, Laura Swiler
We develop a framework for Gaussian processes regression constrained by boundary value problems. The framework may be applied to infer the solution of a well-posed boundary value p…
A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges
Laura Swiler, Mamikon Gulian, Ari Frankel +2
Gaussian process regression is a popular Bayesian framework for surrogate modeling of expensive data sources. As part of a broader effort in scientific machine learning, many recen…
An active learning high-throughput microstructure calibration framework for solving inverse structure-process problems in materials informatics
Anh Tran, John A. Mitchell, Laura P. Swiler +1
Determining a process-structure-property relationship is the holy grail of materials science, where both computational prediction in the forward direction and materials design in t…
Tensor Basis Gaussian Process Models of Hyperelastic Materials
Ari Frankel, Reese Jones, Laura Swiler
In this work, we develop Gaussian process regression (GPR) models of hyperelastic material behavior. First, we consider the direct approach of modeling the components of the Cauchy…
Sensitivity analysis of a computational model of the IKK-NF-κB-IκBα-A20 signal transduction network
Jaewook Joo, Steve Plimpton, Shawn Martin +2
The NF-κB signaling network plays an important role in many different compartments of the immune system during immune activation. Using a computational model of the NF-κB signaling…