J
Jonas Adler
Researcher at Royal Institute of Technology
Publications - 35
Citations - 14475
Jonas Adler is an academic researcher from Royal Institute of Technology. The author has contributed to research in topics: Artificial neural network & Inverse problem. The author has an hindex of 14, co-authored 34 publications receiving 2551 citations.
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Journal ArticleDOI
Highly accurate protein structure prediction with AlphaFold
John M. Jumper,Richard O. Evans,Alexander Pritzel,Tim Green,Michael Figurnov,Olaf Ronneberger,Kathryn Tunyasuvunakool,Russell Bates,Augustin Žídek,Anna Potapenko,Alex Bridgland,Clemens Meyer,Simon A. A. Kohl,Andrew J. Ballard,Andrew Cowie,Bernardino Romera-Paredes,Stanislav Nikolov,R. D. Jain,Jonas Adler,Trevor Back,Stig Petersen,David Reiman,Ellen Clancy,Michal Zielinski,Martin Steinegger,Michalina Pacholska,Tamas Berghammer,Sebastian Bodenstein,David L. Silver,Oriol Vinyals,Andrew W. Senior,Koray Kavukcuoglu,Pushmeet Kohli,Demis Hassabis +33 more
TL;DR: For example, AlphaFold as mentioned in this paper predicts protein structures with an accuracy competitive with experimental structures in the majority of cases using a novel deep learning architecture. But the accuracy is limited by the fact that no homologous structure is available.
Journal ArticleDOI
Highly accurate protein structure prediction for the human proteome
Kathryn Tunyasuvunakool,Jonas Adler,Zachary Wu,Tim Green,Michal Zielinski,Augustin Žídek,Alex Bridgland,Andrew Cowie,Clemens Meyer,Agata Laydon,Sameer Velankar,Gerard J. Kleywegt,Alex Bateman,Richard Evans,Alexander Pritzel,Michael Figurnov,Olaf Ronneberger,Russell Bates,Simon A. A. Kohl,Anna Potapenko,Andrew J. Ballard,Bernardino Romera-Paredes,Stanislav Nikolov,R. D. Jain,Ellen Clancy,David Reiman,Stig Petersen,Andrew W. Senior,Koray Kavukcuoglu,Ewan Birney,Pushmeet Kohli,John M. Jumper,Demis Hassabis +32 more
TL;DR: The AlphaFold2 dataset as discussed by the authors is a large-scale and high-accuracy structure prediction dataset for protein structures, which is used to evaluate the structural properties of proteins.
Journal ArticleDOI
Learned Primal-Dual Reconstruction
Jonas Adler,Ozan Öktem +1 more
TL;DR: The Learned Primal-Dual algorithm for tomographic reconstruction accounts for a (possibly non-linear) forward operator in a deep neural network by unrolling a proximal primal-dual optimization method, but where the proximal operators have been replaced with convolutional neural networks.
Journal ArticleDOI
Solving ill-posed inverse problems using iterative deep neural networks
Jonas Adler,Ozan Öktem +1 more
TL;DR: In this article, a partially learned approach for the solution of ill-posed inverse problems with not necessarily linear forward operators is proposed, which builds on ideas from classical regularisation theory.
Journal ArticleDOI
Learned Primal-dual Reconstruction
Jonas Adler,Ozan Öktem +1 more
TL;DR: In this article, the learned primal-dual (LPD) algorithm is proposed for tomographic reconstruction, where the proximal operators have been replaced with convolutional neural networks and the algorithm is trained end-to-end, working directly from raw measured data.