Ozan Öktem

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Jonas AdlerSenior Research Scientist, Google DeepMindVerified email at google.com
Carola-Bibiane SchönliebDAMTP, University of CambridgeVerified email at cam.ac.uk
Simon ARRIDGEUniversity College LondonVerified email at cs.ucl.ac.uk
Peter MaassProfessor Mathematics, University of BremenVerified email at math.uni-bremen.de
Todd QuintoRobinson Professor of Mathematics, Tufts UniversityVerified email at tufts.edu
Subhadip MukherjeeAssistant Professor, University of Bath, UKVerified email at bath.ac.uk
Chandrajit BajajComputational Applied Mathematics Chair, Professor of Computer Science,Verified email at cs.utexas.edu
Andreas HauptmannAcademy Research Fellow & Associate Professor, University of OuluVerified email at oulu.fi
Axel RinghAssistant Professor, Department of Mathematical Sciences, Chalmers University of TechnologyVerified email at chalmers.se
Duccio FanelliUniversity of FlorenceVerified email at unifi.it
Gitta KutyniokBavarian AI Chair for Mathematical Foundations of Artificial Intelligence, LMU MunichVerified email at math.lmu.de
Hector Andrade-LoarcaPostDoc, Ludwig-Maximilians-Universität MünchenVerified email at math.tu-berlin.de
Johan KarlssonAssociate Professor, Department of Mathematics, KTH Royal Institute of TechnologyVerified email at math.kth.se
Abraham J KosterLeiden University Medical CenterVerified email at lumc.nl
Bernd RiegerProfessor, TU DelftVerified email at tudelft.nl
Ivan LazićSenior Scientist at Thermo Fisher Scientific, The NetherlandsVerified email at thermofisher.com
Raimond RavelliMaastricht UniversityVerified email at maastrichtuniversity.nl
Olivier VerdierBergen University CollegeVerified email at hvl.no
Sebastian BanertPost-doc, Lund UniversityVerified email at control.lth.se
Barbara GrisChargée de recherche CNRS, Laboratoire Jacques-Louis Lions (Sorbonne Université)Verified email at sorbonne-universite.fr

Ozan Öktem

Department of Mathematics, KTH - Royal Institute of Technology

Verified email at oktem.se

Inverse Problems Mathematical Analysis Deep Learning Tomography Microscopy


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Learned primal-dual reconstruction J Adler, O Öktem IEEE transactions on medical imaging 37 (6), 1322-1332, 2018	642	2018
Solving ill-posed inverse problems using iterative deep neural networks J Adler, O Öktem Inverse Problems 33 (12), 124007, 2017	542	2017
Solving inverse problems using data-driven models S Arridge, P Maass, O Öktem, CB Schönlieb Acta Numerica 28, 1-174, 2019	409	2019
Adversarial regularizers in inverse problems S Lunz, O Öktem, CB Schönlieb Advances in neural information processing systems 31, 2018	185	2018
Deep bayesian inversion J Adler, O Öktem arXiv preprint arXiv:1811.05910, 2018	103	2018
Operator discretization library J Adler, H Kohr, O Öktem URL https://github. com/odlgroup/odl, 2017	103*	2017
Image formation modeling in cryo-electron microscopy M Vulović, RBG Ravelli, LJ van Vliet, AJ Koster, I Lazić, U Lücken, ... Journal of structural biology 183 (1), 19-32, 2013	98	2013
Simulation of transmission electron microscope images of biological specimens H Rullgård, LG Öfverstedt, S Masich, B Daneholt, O Öktem Journal of microscopy 243 (3), 234-256, 2011	79	2011
Electron tomography: a short overview with an emphasis on the absorption potential model for the forward problem D Fanelli, O Öktem Inverse Problems 24 (1), 013001, 2008	73	2008
Local tomography in electron microscopy ET Quinto, O Öktem SIAM Journal on Applied Mathematics 68 (5), 1282-1303, 2008	45	2008
Learned convex regularizers for inverse problems S Mukherjee, S Dittmer, Z Shumaylov, S Lunz, O Öktem, CB Schönlieb arXiv preprint arXiv:2008.02839, 2020	42	2020
Extension of separately analytic functions and applications to range characterization of the exponential Radon transform O Öktem Annales Polonici Mathematici 70 (1), 195-213, 1998	35	1998
Molecular cryo‐electron tomography of vitreous tissue sections: current challenges L Norlén, O Öktem, U Skoglund Journal of microscopy 235 (3), 293-307, 2009	34	2009
Task adapted reconstruction for inverse problems J Adler, S Lunz, O Verdier, CB Schönlieb, O Öktem Inverse Problems 38 (7), 075006, 2022	31	2022
Multi-scale learned iterative reconstruction A Hauptmann, J Adler, S Arridge, O Öktem IEEE transactions on computational imaging 6, 843-856, 2020	31	2020
Learning to solve inverse problems using Wasserstein loss J Adler, A Ringh, O Öktem, J Karlsson arXiv preprint arXiv:1710.10898, 2017	29	2017
Mathematics of electron tomography O Öktem Springer, 2015	26	2015
Data-driven nonsmooth optimization S Banert, A Ringh, J Adler, J Karlsson, O Oktem SIAM Journal on Optimization 30 (1), 102-131, 2020	25	2020
Indirect image registration with large diffeomorphic deformations C Chen, O Oktem SIAM Journal on Imaging Sciences 11 (1), 575-617, 2018	25	2018
A componentwise iterated relative entropy regularization method with updated prior and regularization parameter H Rullgård, O Öktem, U Skoglund Inverse Problems 23 (5), 2121, 2007	23	2007

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