3 citations · 4 across the 7 of their papers we have counts for
9 papers
Limit Points of Reflow with Minibatch Optimal Transport
Antonin Chambolle, Johannes Hertrich
Rectified flows, also called flow matching or stochastic interpolants, are generative models that learn a time-dependent vector field steering a probability curve between two proba…
A Stability Benchmark of Generative Regularizers for Inverse Problems
Alexander Denker, Johannes Hertrich, Sebastian Neumayer
Generative (diffusion) priors demonstrate remarkable performance in addressing inverse problems in imaging. Yet, for scientific and medical imaging, it is crucial that reconstructi…
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…
Plug-and-Play Half-Quadratic Splitting for Ptychography
Alexander Denker, Johannes Hertrich, Zeljko Kereta +3
Ptychography is a coherent diffraction imaging method that uses phase retrieval techniques to reconstruct complex-valued images. It achieves this by sequentially illuminating overl…
Fast Summation of Radial Kernels via QMC Slicing
Johannes Hertrich, Tim Jahn, Michael Quellmalz
The fast computation of large kernel sums is a challenging task, which arises as a subproblem in any kernel method. We approach the problem by slicing, which relies on random proje…
Importance Corrected Neural JKO Sampling
Johannes Hertrich, Robert Gruhlke
In order to sample from an unnormalized probability density function, we propose to combine continuous normalizing flows (CNFs) with rejection-resampling steps based on importance…
Infinity-Laplacians on Scalar- and Vector-Valued Functions and Optimal Lipschitz Extensions on Graphs
Johannes Hertrich
Extending functions from boundary values plays an important role in various applications. In this thesis we consider discrete and continuous formulations of the problem based on $p…