12 citations · 12 across the 4 of their papers we have counts for
4 papers
Pullback Flow Matching on Data Manifolds
Friso de Kruiff, Erik Bekkers, Ozan Öktem +2
We propose Pullback Flow Matching (PFM), a novel framework for generative modeling on data manifolds. Unlike existing methods that assume or learn restrictive closed-form manifold…
End-to-end reconstruction meets data-driven regularization for inverse problems
Subhadip Mukherjee, Marcello Carioni, Ozan Öktem +1
We propose an unsupervised approach for learning end-to-end reconstruction operators for ill-posed inverse problems. The proposed method combines the classical variational framewor…
Adversarially learned iterative reconstruction for imaging inverse problems
Subhadip Mukherjee, Ozan Öktem, Carola-Bibiane Schönlieb
In numerous practical applications, especially in medical image reconstruction, it is often infeasible to obtain a large ensemble of ground-truth/measurement pairs for supervised l…
Tunable Ampere phase plate for low dose imaging of biomolecular complexes
Amir H. Tavabi, Marco Beleggia, Vadim Migunov +5
A novel device that can be used as a tunable support-free phase plate for transmission electron microscopy of weakly scattering specimens is described. The device relies on the gen…