---
title: "David Silver · Google DeepMind — author profile and papers"
description: "David Silver, Google DeepMind: 2 papers on Elamur Research (2016–2023), h-index 66 — affiliations, topics, co-authors and who cites them…"
canonical: "https://research.elamur.ai/free/en/authors/david-silver/"
---
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# David Silver

David Silver has 2 papers in our library, in 2016–2023, most of them on [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/); often with [Andrew M. Dai](https://md.research.elamur.ai/free/en/authors/andrew-m-dai/), [Gemini Robotics Team](https://md.research.elamur.ai/free/en/authors/gemini-robotics-team/), [Jean-Baptiste Alayrac](https://md.research.elamur.ai/free/en/authors/jean-baptiste-alayrac/).

2 papers in our library · 2016–2023

[OpenAlex](https://openalex.org/A5091771290) · [ORCID](https://orcid.org/0000-0002-5197-2892) · [Wikidata](https://www.wikidata.org/wiki/Q25208036) · [**h-index 66**](https://openalex.org/authors/A5091771290) · [125 works](https://openalex.org/works?filter=author.id:A5091771290) · [155,900 citations](https://openalex.org/works?filter=author.id:A5091771290&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/david-silver/#papers) · [🔗 Cited 4,581 times in our library](https://md.research.elamur.ai/free/en/authors/david-silver/cited-by/) · [19 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #1037](https://md.research.elamur.ai/free/en/paper-stars/page/11/#star-1037)

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=David+Silver) · [Semantic Scholar](https://www.semanticscholar.org/search?q=David+Silver) · [dblp](https://dblp.org/search?q=David+Silver) · [ACL Anthology](https://aclanthology.org/search/?q=David+Silver)

## Affiliations

[🏢**Google DeepMind** London · United Kingdom 2013–2025 · 52 papersEmployment since 2013*current*](https://md.research.elamur.ai/free/en/companies/google-deepmind/) · [🏢**Google** London · United Kingdom 2025 · 1 paper*current*](https://md.research.elamur.ai/free/en/companies/google-united-kingdom/) · [🏢**Google** Mountain View · United States 2015–2021 · 24 papers](https://md.research.elamur.ai/free/en/companies/google/) · [🎓**University College London** London · United Kingdom 2010–2021 · 23 papersEmployment](https://md.research.elamur.ai/free/en/universities/university-college-london/) · [🎓**University of Alberta** Edmonton · Canada 2005–2009 · 11 papersEducation until 2009](https://md.research.elamur.ai/free/en/universities/university-of-alberta/) · [🎓**University of Michigan** Ann Arbor · United States 2019–2021 · 2 papers](https://md.research.elamur.ai/free/en/universities/university-of-michigan/) · [🏥**Royal Devon and Exeter Hospital** Exeter · United Kingdom 2018–2019 · 2 papers](https://ror.org/03jrh3t05) · [🎓**Massachusetts Institute of Technology** Cambridge · United States 2010–2011 · 2 papers](https://md.research.elamur.ai/free/en/universities/massachusetts-institute-of-technology/) · [🎓**Carnegie Mellon University** Pittsburgh · United States 2009–2010 · 2 papers](https://md.research.elamur.ai/free/en/universities/carnegie-mellon-university/) · [🎓**University of Cambridge** Cambridge · United Kingdom 1997Education until 1997](https://md.research.elamur.ai/free/en/universities/university-of-cambridge/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

## Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 5 The field of science this work belongs to (OpenAlex fields).[Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Language and Linguistics · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/)

🧭 Topics 1 Research subjects and languages the work is about.[Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/)

## Works by year

### 2020s

[**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/david-silver/year/2023/)

### 2010s

[**2016** 1 paper](https://md.research.elamur.ai/free/en/authors/david-silver/year/2016/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Gemini: A Family of Highly Capable Multimodal Models](https://md.research.elamur.ai/free/en/papers/gemini-team-2023-gemini-family-highly-capable-multimodal/)** *(2023 · 3,050 citations)* Gemini 1.0 is Google's model family designed to handle several modalities from the very start, rather than attaching vision or speech to a finished text model.
2. **[Reinforcement Learning with Unsupervised Auxiliary Tasks](https://md.research.elamur.ai/free/en/papers/jaderberg-2016-reinforcement-learning-unsupervised-auxiliary-tasks/)** *(2016 · 319 citations)* Deep RL agents usually learn only from extrinsic reward, which is often sparse. That leaves most of the information in an agent's observation stream unused. Jaderberg et al. (DeepMind) propose UNREAL (UNsupervised REinforcement and Auxiliary Learning), which extends the A3C actor-critic with extra objectives that…

## All works

21 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

1. **[Playing Atari with Deep Reinforcement Learning ↗](https://arxiv.org/abs/1312.5602) arXiv:1312.5602 · no summary yet**Volodymyr Mnih et al.*2013 · 5,030 citations*
2. **[Improved protein structure prediction using potentials from deep learning ↗](https://doi.org/10.1038/s41586-019-1923-7) Nature · no summary yet**Andrew Senior et al.*2020 · 3,388 citations*
3. **[Deep Reinforcement Learning with Double Q-learning ↗](https://arxiv.org/abs/1509.06461) arXiv:1509.06461 · no summary yet**Hado van Hasselt, Arthur Guez, David Silver*2015 · 3,368 citations*
4. [**Gemini: A Family of Highly Capable Multimodal Models arXiv:2312.11805**Gemini Team, Rohan Anil, Sebastian Borgeaud, et al.*2023 · 3,050 citations*](https://md.research.elamur.ai/free/en/papers/gemini-team-2023-gemini-family-highly-capable-multimodal/)
5. **[Asynchronous Methods for Deep Reinforcement Learning ↗](https://arxiv.org/abs/1602.01783) arXiv:1602.01783 · ICML 2016 · no summary yet**Volodymyr Mnih et al.*2016 · 1,955 citations*
6. **[Human-level performance in 3D multiplayer games with population-based reinforcement learning ↗](https://doi.org/10.1126/science.aau6249) Science · no summary yet**Max Jaderberg et al.*2019 · 682 citations*
7. **[StarCraft II: A New Challenge for Reinforcement Learning ↗](https://arxiv.org/abs/1708.04782) arXiv (Cornell University) · no summary yet**Oriol Vinyals et al.*2017 · 680 citations*
8. **[Fast gradient-descent methods for temporal-difference learning with linear function approximation ↗](https://doi.org/10.1145/1553374.1553501) International Conference on Machine Learning · no summary yet**Richard S. Sutton et al.*2009 · 500 citations*
9. **[Applying and improving AlphaFold at CASP14 ↗](https://doi.org/10.1002/prot.26257) Proteins Structure Function and Bioinformatics · no summary yet**John Jumper et al.*2021 · 395 citations*
10. [**Reinforcement Learning with Unsupervised Auxiliary Tasks arXiv:1611.05397**Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, et al.*2016 · 319 citations*](https://md.research.elamur.ai/free/en/papers/jaderberg-2016-reinforcement-learning-unsupervised-auxiliary-tasks/)
11. **[FeUdal Networks for Hierarchical Reinforcement Learning ↗](https://arxiv.org/abs/1703.01161) arXiv (Cornell University) · no summary yet**Alexander Vezhnevets et al.*2017 · 272 citations*
12. **[Imagination-Augmented Agents for Deep Reinforcement Learning ↗](https://arxiv.org/abs/1707.06203) arXiv (Cornell University) · no summary yet**Théophane Weber et al.*2017 · 241 citations*
13. **[Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation ↗](https://openalex.org/W2134042548) neural information processing systems · no summary yet**Shalabh Bhatnagar et al.*2009 · 161 citations*
14. **[Unsupervised Predictive Memory in a Goal-Directed Agent ↗](https://arxiv.org/abs/1803.10760) arXiv (Cornell University) · no summary yet**Greg Wayne et al.*2018 · 140 citations*
15. **[Decoupled Neural Interfaces using Synthetic Gradients ↗](https://arxiv.org/abs/1608.05343) arXiv (Cornell University) · no summary yet**Max Jaderberg et al.*2016 · 100 citations*
16. **[Monte-Carlo simulation balancing ↗](https://doi.org/10.1145/1553374.1553495) International Conference on Machine Learning · no summary yet**David Silver, Gerald J. Tesauro*2009 · 92 citations*
17. **[Fast reinforcement learning with generalized policy updates ↗](https://doi.org/10.1073/pnas.1907370117) Proceedings of the National Academy of Sciences · no summary yet**André da Motta Salles Barreto et al.*2020 · 81 citations*
18. **[Learning to Win by Reading Manuals in a Monte-Carlo Framework ↗](https://aclanthology.org/P11-1028/) Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies · no summary yet**S.R.K. Branavan, David Silver, Regina Barzilay*2011 · 73 citations*
19. **[Learning to Search with MCTSnets ↗](https://arxiv.org/abs/1802.04697) arXiv:1802.04697 · no summary yet**Arthur Guez et al.*2018 · 30 citations*
20. **[DataRater: Meta-Learned Dataset Curation ↗](https://doi.org/10.52202/085713-0677) neural information processing systems · no summary yet**Dan A. Calian et al.*2025 · 4 citations*
21. **[Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence Non-Linear Monte-Carlo Search in Civilization II ↗](https://openalex.org/W7095177486) no summary yet**S. R. K. Branavan, David Silver, Regina Barzilay*2012*

## Co-authors here

12 of 14 co-authors with a page, the most papers together first.

- [Andrew M. Dai](https://md.research.elamur.ai/free/en/authors/andrew-m-dai/)
- [Gemini Robotics Team](https://md.research.elamur.ai/free/en/authors/gemini-robotics-team/)
- [Jean-Baptiste Alayrac](https://md.research.elamur.ai/free/en/authors/jean-baptiste-alayrac/)
- [Jiahui Yu](https://md.research.elamur.ai/free/en/authors/jiahui-yu/)
- [Joel Z Leibo](https://md.research.elamur.ai/free/en/authors/joel-z-leibo/)
- [Katie Millican](https://md.research.elamur.ai/free/en/authors/katie-millican/)
- [Koray Kavukcuoglu](https://md.research.elamur.ai/free/en/authors/koray-kavukcuoglu/)
- [Max Jaderberg](https://md.research.elamur.ai/free/en/authors/max-jaderberg/)
- [Melvin Johnson](https://md.research.elamur.ai/free/en/authors/melvin-johnson/)
- [Radu Soricut](https://md.research.elamur.ai/free/en/authors/radu-soricut/)
- [Rohan Anil](https://md.research.elamur.ai/free/en/authors/rohan-anil/)
- [Sebastian Borgeaud](https://md.research.elamur.ai/free/en/authors/sebastian-borgeaud/)

## Venues

Where their works here were published, the most works first, with the editions of those that have a page.

- International Conference on Machine Learning ×2
- neural information processing systems ×2
- Nature
- Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies
- Proceedings of the National Academy of Sciences
- Proteins Structure Function and Bioinformatics
- Science

## Cited by

Papers of our library cite their works 4,581 times (of the 149,439 papers whose bibliographies we read); [895 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/david-silver/cited-by/).

Updated 2 November 2026