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Alexander Pritzel
Alexander Pritzel
Deepmind
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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
214552021
Continuous control with deep reinforcement learning
TP Lillicrap, JJ Hunt, A Pritzel, N Heess, T Erez, Y Tassa, D Silver, ...
arXiv preprint arXiv:1509.02971, 2015
156242015
Simple and scalable predictive uncertainty estimation using deep ensembles
B Lakshminarayanan, A Pritzel, C Blundell
Advances in neural information processing systems 30, 2017
54242017
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
19792021
Protein complex prediction with AlphaFold-Multimer
R Evans, M O’Neill, A Pritzel, N Antropova, A Senior, T Green, A Žídek, ...
biorxiv, 2021.10. 04.463034, 2021
15892021
Deep exploration via bootstrapped DQN
I Osband, C Blundell, A Pritzel, B Van Roy
Advances in neural information processing systems 29, 2016
13932016
Pathnet: Evolution channels gradient descent in super neural networks
C Fernando, D Banarse, C Blundell, Y Zwols, D Ha, AA Rusu, A Pritzel, ...
arXiv preprint arXiv:1701.08734, 2017
9322017
Vector-based navigation using grid-like representations in artificial agents
A Banino, C Barry, B Uria, C Blundell, T Lillicrap, P Mirowski, A Pritzel, ...
Nature 557 (7705), 429-433, 2018
6922018
Darla: Improving zero-shot transfer in reinforcement learning
I Higgins, A Pal, A Rusu, L Matthey, C Burgess, A Pritzel, M Botvinick, ...
International Conference on Machine Learning, 1480-1490, 2017
4852017
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
4002023
Neural episodic control
A Pritzel, B Uria, S Srinivasan, AP Badia, O Vinyals, D Hassabis, ...
International conference on machine learning, 2827-2836, 2017
3952017
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
335*2021
Never give up: Learning directed exploration strategies
AP Badia, P Sprechmann, A Vitvitskyi, D Guo, B Piot, S Kapturowski, ...
arXiv preprint arXiv:2002.06038, 2020
3162020
Model-free episodic control
C Blundell, B Uria, A Pritzel, Y Li, A Ruderman, JZ Leibo, J Rae, ...
arXiv preprint arXiv:1606.04460, 2016
287*2016
Learning skillful medium-range global weather forecasting
R Lam, A Sanchez-Gonzalez, M Willson, P Wirnsberger, M Fortunato, ...
Science 382 (6677), 1416-1421, 2023
256*2023
Accurate proteome-wide missense variant effect prediction with AlphaMissense
J Cheng, G Novati, J Pan, C Bycroft, A Žemgulytė, T Applebaum, A Pritzel, ...
Science 381 (6664), eadg7492, 2023
1992023
Scrambling in the black hole portrait
G Dvali, D Flassig, C Gomez, A Pritzel, N Wintergerst
Physical Review D 88 (12), 124041, 2013
1132013
Memory-based parameter adaptation
P Sprechmann, SM Jayakumar, JW Rae, A Pritzel, AP Badia, B Uria, ...
arXiv preprint arXiv:1802.10542, 2018
1092018
Targeted free energy estimation via learned mappings
P Wirnsberger, AJ Ballard, G Papamakarios, S Abercrombie, S Racanière, ...
The Journal of Chemical Physics 153 (14), 2020
772020
Black holes and quantumness on macroscopic scales
D Flassig, A Pritzel, N Wintergerst
Physical Review D 87 (8), 084007, 2013
712013
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Articles 1–20