🧑‍🔬 Daan Wierstra

🏛️ Affiliations

🏢Google DeepMindLondon · United Kingdom2008–2018 · 20 papers🔬Dalle Molle Institute for Artificial Intelligence ResearchLugano · Switzerland2005–2010 · 19 papers🏢GoogleMountain View · United States2015–2019 · 10 papers🎓École Polytechnique Fédérale de LausanneLausanne · Switzerland2010–2011 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

🧭 Fields, topics and concepts

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

📅 Works by year

2010s

📄 Papers

The most cited first (OpenAlex and our library).

1. Stochastic Backpropagation and Approximate Inference in Deep Generative Models (2014 · 2,765 citations)
   The paper addresses a long-standing difficulty with deep directed generative models: sampling from them is easy, but inferring their hidden variables efficiently has been hard.
2. Matching Networks for One Shot Learning (2016 · 1,197 citations)
   The paper addresses one-shot learning: how to train a neural network to recognize a new class when only one or a few labeled examples are available.

All works

15 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 ↗arXiv:1312.5602 · no summary yetVolodymyr Mnih et al.2013 · 5,030 citations
2. Stochastic Backpropagation and Approximate Inference in Deep Generative ModelsarXiv:1401.4082Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra2014 · 2,765 citations
3. Weight Uncertainty in Neural Networks ↗arXiv (Cornell University) · no summary yetCharles Blundell et al.2015 · 1,217 citations
4. Matching Networks for One Shot LearningarXiv:1606.04080Oriol Vinyals, Charles Blundell, Timothy Lillicrap, et al.2016 · 1,197 citations
5. DRAW: A Recurrent Neural Network For Image Generation ↗arXiv:1502.04623 · no summary yetKarol Gregor et al.2015 · 947 citations
6. Weight Uncertainty in Neural Network ↗International Conference on Machine Learning · no summary yetCharles Blundell et al.2015 · 840 citations
7. PathNet: Evolution Channels Gradient Descent in Super Neural Networks ↗arXiv:1701.08734 · no summary yetChrisantha Fernando et al.2017 · 667 citations
8. Neural scene representation and rendering ↗Science · no summary yetS. M. Ali Eslami et al.2018 · 518 citations
9. Imagination-Augmented Agents for Deep Reinforcement Learning ↗arXiv (Cornell University) · no summary yetThéophane Weber et al.2017 · 241 citations
10. Towards Conceptual Compression ↗neural information processing systems · no summary yetKarol Gregor et al.2016 · 118 citations
11. Neural Episodic Control ↗arXiv:1703.01988 · no summary yetAlexander Pritzel et al.2017 · 91 citations
12. Stochastic search using the natural gradient ↗International Conference on Machine Learning · no summary yetYi Sun et al.2009 · 81 citations
13. Learning model-based planning from scratch ↗arXiv (Cornell University) · no summary yetRazvan Pascanu et al.2017 · 76 citations
14. Relational recurrent neural networks ↗arXiv (Cornell University) · no summary yetAdam Santoro et al.2018 · 43 citations
15. Learning to Search with MCTSnets ↗arXiv:1802.04697 · no summary yetArthur Guez et al.2018 · 30 citations

🤝 Co-authors here

3 co-authors with a page, the most papers together first.

• Koray Kavukcuoglu
• Oriol Vinyals
• Timothy Lillicrap

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
• Science
• neural information processing systems

🔗 Cited by

Papers of our library cite their works 1,630 times (of the 149,439 papers whose bibliographies we read); 107 citing papers with a page here →.

Updated 31 October 2026

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