3 citations · 4 across the 7 of their papers we have counts for
3 papers · 1 filter
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…
On the Relation between Rectified Flows and Optimal Transport
Johannes Hertrich, Antonin Chambolle, Julie Delon
This paper investigates the connections between rectified flows, flow matching, and optimal transport. Flow matching is a recent approach to learning generative models by estimatin…
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…