Follow
Simon Kohl
Simon Kohl
Other namesSimon A. A. Kohl
Research Scientist, DeepMind
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
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
275872021
nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation
F Isensee, PF Jaeger, SAA Kohl, J Petersen, KH Maier-Hein
Nature methods 18 (2), 203-211, 2021
4652*2021
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
23012021
The liver tumor segmentation benchmark (lits)
P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ...
Medical Image Analysis 84, 102680, 2023
11952023
nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation
F Isensee, J Petersen, A Klein, D Zimmerer, PF Jaeger, S Kohl, ...
MICCAI 2018, Medical Segmentation Decathlon Challenge Entry, 2018
9892018
A Probabilistic U-Net for Segmentation of Ambiguous Images
SAA Kohl, B Romera-Paredes, C Meyer, J De Fauw, JR Ledsam, ...
Advances in Neural Information Processing Systems (NeurIPS spotlight), 2018
6182018
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
3152021
Classification of cancer at prostate MRI: deep learning versus clinical PI-RADS assessment
P Schelb, S Kohl, JP Radtke, M Wiesenfarth, P Kickingereder, ...
Radiology 293 (3), 607-617, 2019
3012019
Retina U-Net: Embarrassingly simple exploitation of segmentation supervision for medical object detection
PF Jaeger, SAA Kohl, S Bickelhaupt, F Isensee, TA Kuder, HP Schlemmer, ...
ML4H Workshop, NeurIPS 2019, 2018
2482018
Contrastive training for improved out-of-distribution detection
J Winkens, R Bunel, AG Roy, R Stanforth, V Natarajan, JR Ledsam, ...
arXiv preprint arXiv:2007.05566, 2020
2472020
Radiomic machine learning for characterization of prostate lesions with MRI: comparison to ADC values
D Bonekamp, S Kohl, M Wiesenfarth, P Schelb, JP Radtke, M Götz, ...
Radiology 289 (1), 128-137, 2018
2102018
Unsupervised Anomaly Localization using Variational Auto-Encoders
D Zimmerer, F Isensee, J Petersen, S Kohl, K Maier-Hein
MICCAI 2019, 2019
1662019
Adversarial Networks for Prostate Cancer Detection
S Kohl, D Bonekamp, HP Schlemmer, K Yaqubi, M Hohenfellner, ...
Machine Learning for Health workshop, NIPS 2017, 2017
162*2017
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
1552020
Context-encoding variational autoencoder for unsupervised anomaly detection
D Zimmerer, SAA Kohl, J Petersen, F Isensee, KH Maier-Hein
MIDL 2019, Conference Abstract, 2018
1492018
Computational predictions of protein structures associated with COVID-19
J Jumper, K Tunyasuvunakool, P Kohli, D Hassabis, AF Team
DeepMind Website, 2020
107*2020
A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities
SAA Kohl, B Romera-Paredes, KH Maier-Hein, DJ Rezende, SM Eslami, ...
Medical Imaging meets NeurIPS Workshop, NeurIPS 2019, 2019
912019
This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence. A. Cowie, B. Romera-Paredes, S. Nikolov, R. Jain, J
J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, ...
Adler, T. Back, S. Petersen, D. Reiman, E. Clancy, M. Zielinski, M …, 2021
652021
batchgenerators—a python framework for data augmentation
F Isensee, P Jäger, J Wasserthal, D Zimmerer, J Petersen, S Kohl, ...
Zenodo 3632567, 2020
62*2020
Augustin ˇZıdek, Anna Potapenko, Alex Bridgland, Clemens Meyer, Simon AA Kohl, Andrew J
J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, ...
412021
The system can't perform the operation now. Try again later.
Articles 1–20