| Human-level control through deep reinforcement learning V Mnih, K Kavukcuoglu, D Silver, AA Rusu, J Veness, MG Bellemare, ... nature 518 (7540), 529-533, 2015 | 22666 | 2015 |
| 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 | 8285 | 2021 |
| Improved protein structure prediction using potentials from deep learning AW Senior, R Evans, J Jumper, J Kirkpatrick, L Sifre, T Green, C Qin, ... Nature 577 (7792), 706-710, 2020 | 2082 | 2020 |
| AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models M Varadi, S Anyango, M Deshpande, S Nair, C Natassia, G Yordanova, ... Nucleic acids research 50 (D1), D439-D444, 2022 | 1219 | 2022 |
| 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 | 1045 | 2021 |
| Starcraft ii: A new challenge for reinforcement learning O Vinyals, T Ewalds, S Bartunov, P Georgiev, AS Vezhnevets, M Yeo, ... arXiv preprint arXiv:1708.04782, 2017 | 806 | 2017 |
| 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 | 539 | 2018 |
| Massively parallel methods for deep reinforcement learning A Nair, P Srinivasan, S Blackwell, C Alcicek, R Fearon, A De Maria, ... arXiv preprint arXiv:1507.04296, 2015 | 519 | 2015 |
| Deepmind lab C Beattie, JZ Leibo, D Teplyashin, T Ward, M Wainwright, H Küttler, ... arXiv preprint arXiv:1612.03801, 2016 | 469 | 2016 |
| Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13) AW Senior, R Evans, J Jumper, J Kirkpatrick, L Sifre, T Green, C Qin, ... Proteins: Structure, Function, and Bioinformatics 87 (12), 1141-1148, 2019 | 249 | 2019 |
| De novo structure prediction with deeplearning based scoring R Evans, J Jumper, J Kirkpatrick, L Sifre, T Green, C Qin, A Zidek, ... Annu Rev Biochem 77 (363-382), 6, 2018 | 128 | 2018 |
| 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 …, 2020 | 125 | 2020 |
| 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 | 116 | 2021 |
| Pushing the frontiers of density functionals by solving the fractional electron problem J Kirkpatrick, B McMorrow, DHP Turban, AL Gaunt, JS Spencer, ... Science 374 (6573), 1385-1389, 2021 | 112 | 2021 |
| Spectral inference networks: Unifying spectral methods with deep learning D Pfau, S Petersen, A Agarwal, D Barrett, K Stachenfeld arXiv preprint arXiv:1806.02215 2, 2018 | 27* | 2018 |
| AlphaFold 2 J Jumper, R Evans, A Pritzel, T Green, M Figurnov, K Tunyasuvunakool, ... In Fourteenth Critical Assessment of Techniques for Protein Structure …, 2020 | 7 | 2020 |
| Vector-based Navigation using Grid-like Representations in Artificial Agents. A Pritzel, A Banino, B Uria, BC Zhang, C Barry, C Blundell, C Beattie, ... | 2 | 2018 |
| Response to Comment on “Pushing the frontiers of density functionals by solving the fractional electron problem” J Kirkpatrick, B McMorrow, DHP Turban, AL Gaunt, JS Spencer, ... Science 377 (6606), eabq4282, 2022 | 1 | 2022 |
| Training spectral inference neural networks using bilevel optimization DB Pfau, S Petersen, A Agarwal, D Barrett, K Stachenfeld US Patent App. 16/972,491, 2021 | | 2021 |
| Discriminating alpha-synuclein strains in Parkinson's disease and multiple system atrophy AW Senior, R Evans, J Jumper, J Kirkpatrick, L Sifre, T Green, C Qin, ... | | 2020 |
David SilverDeepMind, UCLVerified email at google.com
