Ozan Öktem

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Jonas AdlerStaff 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
Subhadip MukherjeeAssistant Professor, Department of E&ECE, IIT Kharagpur, IndiaVerified email at ece.iitkgp.ac.in
Andreas HauptmannAcademy Research Fellow & Associate Professor, University of OuluVerified email at oulu.fi
Todd QuintoRobinson Professor of Mathematics, Tufts UniversityVerified email at tufts.edu
Chandrajit BajajComputational Applied Mathematics Chair, Professor of Computer Science,Verified email at cs.utexas.edu
Axel RinghAssistant Professor, Department of Mathematical Sciences, Chalmers University of TechnologyVerified email at chalmers.se
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.lmu.de
Duccio FanelliUniversity of FlorenceVerified email at unifi.it
Johan KarlssonProfessor, 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
Jevgenija RudzusikaKTH Royal Institute of TechnologyVerified email at kth.se
Sebastian BanertPost-doc, University of BremenVerified email at uni-bremen.de

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	830	2018
Solving ill-posed inverse problems using iterative deep neural networks J Adler, O Öktem Inverse Problems 33 (12), 124007, 2017	670	2017
Solving inverse problems using data-driven models S Arridge, P Maass, O Öktem, CB Schönlieb Acta Numerica 28, 1-174, 2019	586	2019
Adversarial regularizers in inverse problems S Lunz, O Öktem, CB Schönlieb Advances in neural information processing systems 31, 2018	246	2018
Deep bayesian inversion J Adler, O Öktem arXiv preprint arXiv:1811.05910, 2018	130	2018
Operator discretization library J Adler, H Kohr, O Öktem ODL, 2017	123*	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	115	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	93	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	76	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	55	2020
Local tomography in electron microscopy ET Quinto, O Öktem SIAM Journal on Applied Mathematics 68 (5), 1282-1303, 2008	49	2008
Task adapted reconstruction for inverse problems J Adler, S Lunz, O Verdier, CB Schönlieb, O Öktem Inverse Problems 38 (7), 075006, 2022	45	2022
Multi-scale learned iterative reconstruction A Hauptmann, J Adler, S Arridge, O Öktem IEEE transactions on computational imaging 6, 843-856, 2020	45	2020
Learned reconstruction methods with convergence guarantees: A survey of concepts and applications S Mukherjee, A Hauptmann, O Öktem, M Pereyra, CB Schönlieb IEEE Signal Processing Magazine 40 (1), 164-182, 2023	42*	2023
Learning to solve inverse problems using Wasserstein loss J Adler, A Ringh, O Öktem, J Karlsson arXiv preprint arXiv:1710.10898, 2017	37	2017
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	36	1998
End-to-end reconstruction meets data-driven regularization for inverse problems S Mukherjee, M Carioni, O Öktem, CB Schönlieb Advances in Neural Information Processing Systems 34, 21413-21425, 2021	35	2021
Molecular cryo‐electron tomography of vitreous tissue sections: current challenges L Norlén, O Öktem, U Skoglund Journal of microscopy 235 (3), 293-307, 2009	35	2009
Indirect image registration with large diffeomorphic deformations C Chen, O Oktem SIAM Journal on Imaging Sciences 11 (1), 575-617, 2018	31	2018
Data-driven nonsmooth optimization S Banert, A Ringh, J Adler, J Karlsson, O Oktem SIAM Journal on Optimization 30 (1), 102-131, 2020	30	2020

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