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Simon Kohl
Simon 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
53722021
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
1050*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
7542021
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
5042018
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
3402018
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
1682019
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
1452018
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
1312018
Adversarial Networks for Prostate Cancer Detection
S Kohl, D Bonekamp, HP Schlemmer, K Yaqubi, M Hohenfellner, ...
Machine Learning for Health workshop, NIPS 2017, 2017
127*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
1132020
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
1002020
Context-encoding variational autoencoder for unsupervised anomaly detection
D Zimmerer, SAA Kohl, J Petersen, F Isensee, KH Maier-Hein
MIDL 2019, Conference Abstract, 2018
832018
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
742021
Unsupervised Anomaly Localization using Variational Auto-Encoders
D Zimmerer, F Isensee, J Petersen, S Kohl, K Maier-Hein
MICCAI 2019, 2019
692019
Computational predictions of protein structures associated with COVID-19
J Jumper, K Tunyasuvunakool, P Kohli, D Hassabis, AF Team
DeepMind Website, 2020
66*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
442019
batchgenerators—a python framework for data augmentation
F Isensee, P Jäger, J Wasserthal, D Zimmerer, J Petersen, S Kohl, ...
Zenodo https://doi. org/10.5281/zenodo 3632567, 2020
23*2020
Deep Probabilistic Modeling of Glioma Growth
J Petersen, PF Jäger, F Isensee, SAA Kohl, U Neuberger, W Wick, ...
MICCAI 2019, 2019
222019
A Case for the Score: Identifying Image Anomalies using Variational Autoencoder Gradients
D Zimmerer, J Petersen, SAA Kohl, KH Maier-Hein
Medical Imaging meets NeurIPS workshop, NeurIPS 2018, 2018
142018
Shallow‐impurity‐related binding energy and linear optical absorption in ring‐shaped quantum dots and quantum‐well wires under applied electric field
SAA Kohl, RL Restrepo, ME Mora‐Ramos, CA Duque
Physica Status Solidi (b) 252 (4), 786-794, 2015
132015
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Articles 1–20