2 papers
cs.LG2020
Objective-Sensitive Principal Component Analysis for High-Dimensional Inverse Problems
Maksim Elizarev, Andrei Mukhin, Aleksey Khlyupin
We present a novel approach for adaptive, differentiable parameterization of large-scale random fields. If the approach is coupled with any gradient-based optimization algorithm, i…
math.OC2019
Adaptive Strategies For Efficient Model Reduction In High-Dimensional Inverse Problems
Andrei Mukhin, Aleksey Khlyupin
This work explores a novel approach for adaptive, differentiable parametrization of large-scale non-stationary random fields. Coupled with any gradient-based algorithm, the method…