2 citations · 5 across the 6 of their papers we have counts for
6 papers
Well-Posedness and Efficient Algorithms for Inverse Optimal Transport with Bregman Regularization
Chenglong Bao, Zanyu Li, Yunan Yang
This work analyzes the inverse optimal transport (IOT) problem under Bregman regularization. We establish well-posedness results, including existence, uniqueness (up to equivalence…
Operator learning meets inverse problems: A probabilistic perspective
Nicholas H. Nelsen, Yunan Yang
Operator learning offers a robust framework for approximating mappings between infinite-dimensional function spaces. It has also become a powerful tool for solving inverse problems…
Learning where to learn: Training data distribution optimization for scientific machine learning
Nicolas Guerra, Nicholas H. Nelsen, Yunan Yang
In scientific machine learning, models are routinely deployed with parameter values or boundary conditions far from those used in training. This paper studies the learning-where-to…
An Analysis of Constraint-Relaxation in PDE-Based Inverse Problems
Tristan van Leeuwen, Yunan Yang
Inverse problems are ubiquitous in science and engineering. Many of these are naturally formulated as a PDE-constrained optimization problem. These non-linear, large-scale, constra…
Adjoint Monte Carlo Method
Russel Caflisch, Yunan Yang
This survey explores the development of adjoint Monte Carlo methods for solving optimization problems governed by kinetic equations, a common challenge in areas such as plasma cont…
Adaptive Preconditioned Gradient Descent with Energy
Hailiang Liu, Levon Nurbekyan, Xuping Tian +1
We propose an adaptive step size with an energy approach for a suitable class of preconditioned gradient descent methods. We focus on settings where the preconditioning is applied…