Daan Wierstra
- Artificial Intelligence top 0.02%
- Reinforcement Learning in Robotics 10
- Evolutionary Algorithms and Applications 10
- Neural Networks and Applications 7
- Metaheuristic Optimization Algorithms Research 6
- Gaussian Processes and Bayesian Inference 4
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- Generative Adversarial Networks and Image Synthesis 5
- Control and Systems Engineering top 0.1%
- Automotive Engineering top 0.1%
- Computer Networks and Communications top 0.1%
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- Neural dynamics and brain function 4
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- Advanced Multi-Objective Optimization Algorithms 3
- Co-authors
- David SilverAlex GravesKoray KavukcuogluDemis HassabisCharles BeattieDharshan KumaranMartin RiedmillerIoannis Antonoglou
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionControl and Systems Engineering
- Journals
- Journal of Machine Learning Research (2 papers)Logic Journal of IGPL (1 paper)Advanced Robotics (1 paper)
- Partner nations
- SwitzerlandUnited StatesUnited Kingdom
In The Last Decade
Daan Wierstra
34 papers receiving 24.1k citations
Hit Papers
Peers
Comparison fields: 5 of 203
- Artificial Intelligence 11.3k
- Computer Vision and Pattern Recognition 4.6k
- Control and Systems Engineering 4.9k
- Automotive Engineering 2.5k
- Computer Networks and Communications 4.4k
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-authorship network
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
| # | Work | ||
|---|---|---|---|
| 1 | Imagination-Augmented Agents for Deep Reinforcement Learning | 2017 | 49 |
| 2 | Recurrent Environment Simulators | 2017 | 9 |
| 3 | 2017 | 29 | |
| 4 | Continuous control with deep reinforcement learningbreakdown → | 2016 | 4888 |
| 5 | Variational Intrinsic Control | 2016 | 4 |
| 6 | Meta-Learning with Memory-Augmented Neural Networks | 2016 | 3 |
| 7 | Towards Conceptual Compression | 2016 | 45 |
| 8 | Meta-learning with memory-augmented neural networksbreakdown → | 2016 | 657 |
| 9 | 2016 | 32 | |
| 10 | DRAW: A Recurrent Neural Network For Image Generationbreakdown → | 2015 | 478 |
| 11 | Weight Uncertainty in Neural Networkbreakdown → | 2015 | 363 |
| 12 | Human-level control through deep reinforcement learningbreakdown → | 2015 | 17153 |
| 13 | Stochastic Back-propagation and Variational Inference in Deep Latent Gaussian Models. | 2014 | 30 |
| 14 | Variational Learning for Recurrent Spiking Networks | 2011 | 22 |
| 15 | Efficient Natural Evolution Strategies Evolution Strategies and Evolutionary Programming Track | 2009 | 1 |
| 16 | 2008 | 126 | |
| 17 | Natural Evolution Strategies | 2008 | 152 |
| 18 | Evolino: Hybrid Neuroevolution / Optimal Linear Search for Sequence Prediction | 2005 | 18 |
| 19 | Evolino: hybrid neuroevolution / optimal linear search for sequence learning | 2005 | 56 |
| 20 | 2004 | 14 |
About Daan Wierstra
Daan Wierstra is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Graphics and Computer-Aided Design, having authored 35 papers that have together received 25.0k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (10 papers), Evolutionary Algorithms and Applications (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 Advanced Multi-Objective Optimization Algorithms (3 papers). The work is most often cited by research in Artificial Intelligence (11.3k citations), Computer Vision and Pattern Recognition (4.6k citations) and Control and Systems Engineering (4.9k 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, Dharshan Kumaran, Martin Riedmiller, Ioannis Antonoglou, Stig Petersen and Shane Legg. Their work appears in journals such as Journal of Machine Learning Research, Logic Journal of IGPL, Advanced Robotics, Nature 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.