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math.OC2025
On Parameter Identification in Three-Dimensional Elasticity and Discretisation with Physics-Informed Neural Networks
Federica Caforio, Martin Holler, Matthias Höfler
Physics-informed neural networks have emerged as a powerful tool in the scientific machine learning community, with applications to both forward and inverse problems. While they ha…
math.OC2023
Neural-network-based regularization methods for inverse problems in imaging
Andreas Habring, Martin Holler
This review provides an introduction to - and overview of - the current state of the art in neural-network based regularization methods for inverse problems in imaging. It aims to…