Daan Wierstra
Impact in
- Artificial Intelligence top 0.02%
- Reinforcement Learning in Robotics
- Adversarial Robustness in Machine Learning
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- Robotic Path Planning Algorithms
Papers in
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- Evolutionary Algorithms and Applications 10
- Reinforcement Learning in Robotics 10
- Neural Networks and Applications 7
- Metaheuristic Optimization Algorithms Research 6
- Gaussian Processes and Bayesian Inference 4
- Adversarial Robustness in Machine Learning 3
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- Generative Adversarial Networks and Image Synthesis 5
- Co-authors
- David Silver (3 shared papers)Alex Graves (2 shared papers)Koray Kavukcuoglu (2 shared papers)Demis Hassabis (3 shared papers)Charles Beattie (1 shared paper)Andrei A. Rusu (1 shared paper)Martin Riedmiller (1 shared paper)Shane Legg (1 shared paper)
- Journals
- Journal of Machine Learning Research (2 papers)Logic Journal of IGPL (1 paper)Nature (1 paper)Advanced Robotics (1 paper)Neural Computation (1 paper)
- Partner nations
- SwitzerlandUnited StatesUnited Kingdom
In The Last Decade
Daan Wierstra
35 papers receiving 24.7k citations
Daan Wierstra's Hit Papers
Peers
Comparison fields: 5 of 202
- Artificial Intelligence 11.5k
- Computer Vision and Pattern Recognition 4.7k
- Control and Systems Engineering 4.9k
- Automotive Engineering 2.5k
- Computer Networks and Communications 4.5k
Countries citing papers authored by Daan Wierstra
This map shows the geographic impact of Daan Wierstra's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daan Wierstra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daan Wierstra more than expected).
Fields of papers citing papers by Daan Wierstra
This network shows the impact of papers produced by Daan Wierstra. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daan Wierstra. The network helps show where Daan Wierstra may publish in the future.
Co-authors
The 25 scholars most cited alongside Daan Wierstra, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Human-level control through deep reinforcement learning Hit paper breakdown → | 2015 | 17656 |
| 2 | Continuous control with deep reinforcement learning Hit paper breakdown → | 2016 | 4934 |
| 3 | Meta-learning with memory-augmented neural networks Hit paper breakdown → | 2016 | 661 |
| 4 | DRAW: A Recurrent Neural Network For Image Generation Hit paper breakdown → | 2015 | 478 |
| 5 | Weight Uncertainty in Neural Network Hit paper breakdown → | 2015 | 367 |
| 6 | Natural Evolution Strategies | 2008 | 154 |
| 7 | 2007 | 154 | |
| 8 | 2008 | 126 | |
| 9 | 2008 | 125 | |
| 10 | 2010 | 109 | |
| 11 | Evolino: hybrid neuroevolution / optimal linear search for sequence learning | 2005 | 57 |
| 12 | 2009 | 56 | |
| 13 | 2006 | 56 | |
| 14 | 2009 | 53 | |
| 15 | 2013 | 53 | |
| 16 | 2009 | 51 | |
| 17 | Imagination-Augmented Agents for Deep Reinforcement Learning | 2017 | 49 |
| 18 | 2010 | 46 | |
| 19 | Towards Conceptual Compression | 2016 | 44 |
| 20 | 2016 | 44 |
About Daan Wierstra
Daan Wierstra is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Electrical and Electronic Engineering and Statistical and Nonlinear Physics, having authored 35 papers that have together received 25.5k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (10 papers), Reinforcement Learning in Robotics (10 papers), Neural Networks and Applications (7 papers), Metaheuristic Optimization Algorithms Research (6 papers), Generative Adversarial Networks and Image Synthesis (5 papers), Neural dynamics and brain function (4 papers), Gaussian Processes and Bayesian Inference (4 papers) and Adversarial Robustness in Machine Learning (3 papers). The work is most often cited by research in Artificial Intelligence (11.5k citations), Computer Vision and Pattern Recognition (4.7k citations), Control and Systems Engineering (4.9k citations), Automotive Engineering (2.5k citations) and Computer Networks and Communications (4.5k citations). Daan Wierstra has collaborated with scholars based in Switzerland, United States and United Kingdom. Frequent co-authors include David Silver, Alex Graves, Koray Kavukcuoglu, Demis Hassabis, Charles Beattie, Andrei A. Rusu, Martin Riedmiller, Shane Legg, Stig Petersen and Marc G. Bellemare. Their work appears in journals such as Journal of Machine Learning Research, Logic Journal of IGPL, Nature, Advanced Robotics and Neural Computation.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.