755 citations · 1.6k across the 34 of their papers we have counts for
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Learned iterative networks: An operator learning perspective
Andreas Hauptmann, Ozan Öktem
Learned image reconstruction has become a pillar in computational imaging and inverse problems. Among the most successful approaches are learned iterative networks, which are formu…
Improving the Generalisation of Learned Reconstruction Frameworks
Emilien Valat, Ozan Öktem
Ensuring proper generalization is a critical challenge in applying data-driven methods for solving inverse problems in imaging, as neural networks reconstructing an image must perf…
Deep Micro Solvers for Rough-Wall Stokes Flow in a Heterogeneous Multiscale Method
Emanuel Ström, Anna-Karin Tornberg, Ozan Öktem
We propose a learned precomputation for the heterogeneous multiscale method (HMM) for rough-wall Stokes flow. A Fourier neural operator is used to approximate local averages over m…
Data-driven multi-agent modelling of calcium interactions in cell culture: PINN vs Regularized Least-squares
Aurora Poggi, Giuseppe Alessio D'Inverno, Hjalmar Brismar +3
Data-driven discovery of dynamics in biological systems allows for better observation and characterization of processes, such as calcium signaling in cell culture. Recent advanceme…