2 papers
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…
eess.IV2025
Energy-based models for inverse imaging problems
Andreas Habring, Martin Holler, Thomas Pock +1
In this chapter we provide a thorough overview of the use of energy-based models (EBMs) in the context of inverse imaging problems. EBMs are probability distributions modeled via G…