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GRIFDIR: Graph Resolution-Invariant FEM Diffusion Models in Function Spaces over Irregular Domains
James Rowbottom, Elizabeth L. Baker, Nick Huang +3
Score-based diffusion models in infinite-dimensional function spaces provide a mathematically principled framework for modelling function-valued data, offering key advantages such…
CMAD: Cooperative Multi-Agent Diffusion via Stochastic Optimal Control
Riccardo Barbano, Alexander Denker, Zeljko Kereta +2
Continuous-time generative models have achieved remarkable success in image restoration and synthesis. However, controlling the composition of multiple pre-trained models remains a…
Learning Regularization Functionals for Inverse Problems: A Comparative Study
Johannes Hertrich, Hok Shing Wong, Alexander Denker +16
In recent years, a variety of learned regularization frameworks for solving inverse problems in imaging have emerged. These offer flexible modeling together with mathematical insig…
Iterative Importance Fine-tuning of Diffusion Models
Alexander Denker, Shreyas Padhy, Francisco Vargas +1
Diffusion models are an important tool for generative modelling, serving as effective priors in applications such as imaging and protein design. A key challenge in applying diffusi…
Convergence Properties of Score-Based Models for Linear Inverse Problems Using Graduated Optimisation
Pascal Fernsel, Željko Kereta, Alexander Denker
The incorporation of generative models as regularisers within variational formulations for inverse problems has proven effective across numerous image reconstruction tasks. However…