Jonas Adler
Jonas Adler
Staff Research Scientist, Google DeepMind
Verified email at - Homepage
Cited by
Cited by
Highly accurate protein structure prediction with AlphaFold
J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, ...
Nature 596 (7873), 583-589, 2021
Highly accurate protein structure prediction for the human proteome
K Tunyasuvunakool, J Adler, Z Wu, T Green, M Zielinski, A ®ídek, ...
Nature 596 (7873), 590-596, 2021
Learned primal-dual reconstruction
J Adler, O Öktem
IEEE transactions on medical imaging, 2018
Solving ill-posed inverse problems using iterative deep neural networks
J Adler, O Öktem
Inverse Problems 33 (12), 124007, 2017
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
Model-based learning for accelerated, limited-view 3-D photoacoustic tomography
A Hauptmann, F Lucka, M Betcke, N Huynh, J Adler, B Cox, P Beard, ...
IEEE transactions on medical imaging 37 (6), 1382-1393, 2018
Banach Wasserstein GAN
J Adler, S Lunz
Neural Information Processing Systems, 2018
Applying and improving AlphaFold at CASP14
J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, ...
Proteins: Structure, Function, and Bioinformatics 89 (12), 1711-1721, 2021
High Accuracy Protein Structure Prediction Using Deep Learning
J Jumper, R Evans, A Pritzel, T Green, M Figurnov, K Tunyasuvunakool, ...
Fourteenth Critical Assessment of Techniques for Protein Structure Prediction, 2020
Deep Bayesian Inversion
J Adler, O Öktem
arXiv preprint arXiv:1811.05910, 2018
Operator Discretization Library (ODL)
J Adler, H Kohr, O Öktem
Software available from https://github. com/odlgroup/odl, 2017
Computational predictions of protein structures associated with COVID-19
J Jumper, K Tunyasuvunakool, P Kohli, D Hassabis, the AlphaFold Team
DeepMind website, 2020
Continuous diffusion for categorical data
S Dieleman, L Sartran, A Roshannai, N Savinov, Y Ganin, PH Richemond, ...
arXiv preprint arXiv:2211.15089, 2022
Task adapted reconstruction for inverse problems
J Adler, S Lunz, O Verdier, CB Schönlieb, O Öktem
Inverse Problems 38 (7), 075006, 2022
Multi-scale learned iterative reconstruction
A Hauptmann, J Adler, S Arridge, O Öktem
IEEE transactions on computational imaging 6, 843-856, 2020
Inferring a continuous distribution of atom coordinates from cryo-EM images using VAEs
D Rosenbaum, M Garnelo, M Zielinski, C Beattie, E Clancy, A Huber, ...
arXiv preprint arXiv:2106.14108, 2021
Learning to solve inverse problems using Wasserstein loss
J Adler, A Ringh, O Öktem, J Karlsson
NIPS 2017 Optimal Transport and Machine Learning, 2017
Computational models in the service of X‐ray and cryo‐electron microscopy structure determination
A Kryshtafovych, J Moult, R Albrecht, GA Chang, K Chao, A Fraser, ...
Proteins: Structure, Function, and Bioinformatics 89 (12), 1633-1646, 2021
Data-driven nonsmooth optimization
S Banert, A Ringh, J Adler, J Karlsson, O Oktem
SIAM Journal on Optimization 30 (1), 102-131, 2020
A unified representation network for segmentation with missing modalities
K Lau, J Adler, J Sjölund
arXiv preprint arXiv:1908.06683, 2019
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