David A. Barajas‐Solano

Randomized physics-informed machine learning for uncertainty quantification in high-dimensional inverse problems

2024 · Journal of Computational Physics

We propose the randomized physics-informed conditional Karhunen-Loève expansion (rPICKLE) method for uncertainty quantification in high-dimensional inverse problems. In rPICKLE, the states and parameters of the governing partial differential equation (PDE) are approximated via truncated conditional …