Volgen
Jonas Adler
Jonas Adler
Staff Research Scientist, Google DeepMind
Geverifieerd e-mailadres voor google.com - Homepage
Titel
Geciteerd door
Geciteerd door
Jaar
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
169042021
Highly accurate protein structure prediction for the human proteome
K Tunyasuvunakool, J Adler, Z Wu, T Green, M Zielinski, A Žídek, ...
Nature 596 (7873), 590-596, 2021
17082021
Learned primal-dual reconstruction
J Adler, O Öktem
IEEE transactions on medical imaging, 2018
7662018
Solving ill-posed inverse problems using iterative deep neural networks
J Adler, O Öktem
Inverse Problems 33 (12), 124007, 2017
6272017
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
2902018
Banach Wasserstein GAN
J Adler, S Lunz
Neural Information Processing Systems, 2018
2442018
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
2132021
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
1432020
Deep Bayesian Inversion
J Adler, O Öktem
arXiv preprint arXiv:1811.05910, 2018
1252018
Operator Discretization Library (ODL)
J Adler, H Kohr, O Öktem
Software available from https://github. com/odlgroup/odl, 2017
121*2017
Computational predictions of protein structures associated with COVID-19
J Jumper, K Tunyasuvunakool, P Kohli, D Hassabis, the AlphaFold Team
DeepMind website, 2020
73*2020
Multi-scale learned iterative reconstruction
A Hauptmann, J Adler, S Arridge, O Öktem
IEEE transactions on computational imaging 6, 843-856, 2020
422020
Task adapted reconstruction for inverse problems
J Adler, S Lunz, O Verdier, CB Schönlieb, O Öktem
Inverse Problems 38 (7), 075006, 2022
412022
Learning to solve inverse problems using Wasserstein loss
J Adler, A Ringh, O Öktem, J Karlsson
NIPS 2017 Optimal Transport and Machine Learning, 2017
362017
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
352021
Continuous diffusion for categorical data
S Dieleman, L Sartran, A Roshannai, N Savinov, Y Ganin, PH Richemond, ...
arXiv preprint arXiv:2211.15089, 2022
322022
Data-driven nonsmooth optimization
S Banert, A Ringh, J Adler, J Karlsson, O Oktem
SIAM Journal on Optimization 30 (1), 102-131, 2020
282020
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
272021
A unified representation network for segmentation with missing modalities
K Lau, J Adler, J Sjölund
arXiv preprint arXiv:1908.06683, 2019
262019
Exploiting prior knowledge about biological macromolecules in cryo-EM structure determination
D Kimanius, G Zickert, T Nakane, J Adler, S Lunz, CB Schönlieb, O Öktem, ...
IUCrJ 8 (1), 60-75, 2021
202021
Het systeem kan de bewerking nu niet uitvoeren. Probeer het later opnieuw.
Artikelen 1–20