Solving ill-posed inverse problems using iterative deep neural networks. - Jonas Adler; Ozan Öktem (CoRR, 2017)

Learning to solve inverse problems using Wasserstein loss. - Jonas Adler; Axel Ringh; Ozan Öktem; Johan Karlsson (CoRR, 2017)

Banach Wasserstein GAN. - Jonas Adler; Sebastian Lunz (NeurIPS, 2018)

A modified fuzzy C means algorithm for shading correction in craniofacial CBCT images. - Awais Ashfaq; Jonas Adler (CoRR, 2018)

Deep Learning Framework for Digital Breast Tomosynthesis Reconstruction. - Nikita Moriakov; Koen Michielsen; Jonas Adler; Ritse Mann; Ioannis Sechopoulos; Jonas Teuwen (CoRR, 2018)

Task adapted reconstruction for inverse problems. - Jonas Adler; Sebastian Lunz; Olivier Verdier; Carola-Bibiane Schönlieb; Ozan Öktem (CoRR, 2018)

Deep Bayesian Inversion. - Jonas Adler; Ozan Öktem (CoRR, 2018)

Learned Primal-Dual Reconstruction. - Jonas Adler; Ozan Öktem (IEEE Trans. Medical Imaging, 2018)

Model-Based Learning for Accelerated, Limited-View 3-D Photoacoustic Tomography. - Andreas Hauptmann; Felix Lucka; Marta M. Betcke; Nam Huynh; Jonas Adler; Ben T. Cox; Paul C. Beard; Sébastien Ourselin; Simon R. Arridge (IEEE Trans. Medical Imaging, 2018)

A unified representation network for segmentation with missing modalities. - Kenneth Lau; Jonas Adler; Jens Sjölund (CoRR, 2019)

Data-driven Methods in Inverse Problems. - Jonas Adler (2019)

Kernel of CycleGAN as a principal homogeneous space. - Nikita Moriakov; Jonas Adler; Jonas Teuwen (ICLR, 2020)

Kernel of CycleGAN as a Principle homogeneous space. - Nikita Moriakov; Jonas Adler; Jonas Teuwen (CoRR, 2020)

On the unreasonable effectiveness of CNNs. - Andreas Hauptmann; Jonas Adler (CoRR, 2020)

Data-Driven Nonsmooth Optimization. - Sebastian Banert; Axel Ringh; Jonas Adler; Johan Karlsson; Ozan Öktem (SIAM J. Optim., 2020)

Multi-Scale Learned Iterative Reconstruction. - Andreas Hauptmann; Jonas Adler; Simon R. Arridge; Ozan Öktem (IEEE Trans. Computational Imaging, 2020)

Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs. - Dan Rosenbaum; Marta Garnelo; Michal Zielinski; Charlie Beattie; Ellen Clancy; Andrea Huber; Pushmeet Kohli; Andrew W. Senior; John Jumper; Carl Doersch; S. M. Ali Eslami; Olaf Ronneberger; et al. (CoRR, 2021)

Continuous diffusion for categorical data. - Sander Dieleman; Laurent Sartran; Arman Roshannai; Nikolay Savinov; Yaroslav Ganin; Pierre H. Richemond; Arnaud Doucet; Robin Strudel; Chris Dyer; Conor Durkan; Curtis Hawthorne; Rémi Leblond; et al. (CoRR, 2022)

Accelerated Forward-Backward Optimization Using Deep Learning. - Sebastian Banert; Jevgenija Rudzusika; Ozan Öktem; Jonas Adler (SIAM J. Optim., 2024)