Nicolas Heess
Impact in
- Artificial Intelligence top 0.2%
- Reinforcement Learning in Robotics
- Adversarial Robustness in Machine Learning
- Control and Systems Engineering top 0.5%
- Robot Manipulation and Learning
- Traffic control and management
Papers in
-
- Reinforcement Learning in Robotics 34
- Adversarial Robustness in Machine Learning 8
- Evolutionary Algorithms and Applications 4
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- Generative Adversarial Networks and Image Synthesis 6
- Human Pose and Action Recognition 5
- Advanced Vision and Imaging 5
- Co-authors
- David Silver (8 shared papers)Tom Erez (5 shared papers)Yuval Tassa (7 shared papers)Timothy Lillicrap (5 shared papers)Daan Wierstra (2 shared papers)Jonathan J. Hunt (2 shared papers)Alexander Pritzel (1 shared paper)Christopher K. I. Williams (3 shared papers)
- Journals
- Journal of Neuroscience (1 paper)International Journal of Computer Vision (1 paper)Physical Review Fluids (1 paper)ACM Transactions on Graphics (1 paper)Neural Computation (1 paper)
- Partner nations
- United KingdomUnited StatesCanada
In The Last Decade
Nicolas Heess
57 papers receiving 6.4k citations
Nicolas Heess's Hit Papers
Peers
Comparison fields: 5 of 142
- Artificial Intelligence 2.9k
- Control and Systems Engineering 1.8k
- Computer Vision and Pattern Recognition 1.5k
- Automotive Engineering 707
- Computer Networks and Communications 1.1k
Countries citing papers authored by Nicolas Heess
This map shows the geographic impact of Nicolas Heess'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 Nicolas Heess with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicolas Heess more than expected).
Fields of papers citing papers by Nicolas Heess
This network shows the impact of papers produced by Nicolas Heess. 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 Nicolas Heess. The network helps show where Nicolas Heess may publish in the future.
Co-authors
The 25 scholars most cited alongside Nicolas Heess, 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 59 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Continuous control with deep reinforcement learning Hit paper breakdown → | 2016 | 4934 |
| 2 | 2009 | 139 | |
| 3 | 2018 | 130 | |
| 4 | Learning continuous control policies by stochastic value gradients | 2015 | 114 |
| 5 | 2017 | 110 | |
| 6 | 2020 | 93 | |
| 7 | 2013 | 80 | |
| 8 | 2015 | 68 | |
| 9 | Learning an Embedding Space for Transferable Robot Skills | 2018 | 66 |
| 10 | 2020 | 60 | |
| 11 | Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics | 2014 | 60 |
| 12 | 2010 | 56 | |
| 13 | 2012 | 51 | |
| 14 | Imagination-Augmented Agents for Deep Reinforcement Learning | 2017 | 49 |
| 15 | Visual Boundary Prediction: A Deep Neural Prediction Network and Quality Dissection | 2014 | 49 |
| 16 | Learning by Playing - Solving Sparse Reward Tasks from Scratch | 2018 | 48 |
| 17 | 2022 | 45 | |
| 18 | 2016 | 42 | |
| 19 | Distributed Distributional Deterministic Policy Gradients | 2018 | 34 |
| 20 | 2021 | 34 |
About Nicolas Heess
Nicolas Heess is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Biomedical Engineering and Cognitive Neuroscience, having authored 59 papers that have together received 6.6k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (34 papers), Robot Manipulation and Learning (10 papers), Adversarial Robustness in Machine Learning (8 papers), Generative Adversarial Networks and Image Synthesis (6 papers), Robotic Locomotion and Control (6 papers), Human Pose and Action Recognition (5 papers), Advanced Vision and Imaging (5 papers) and Evolutionary Algorithms and Applications (4 papers). The work is most often cited by research in Artificial Intelligence (2.9k citations), Control and Systems Engineering (1.8k citations), Computer Vision and Pattern Recognition (1.5k citations), Automotive Engineering (707 citations) and Computer Networks and Communications (1.1k citations). Nicolas Heess has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include David Silver, Tom Erez, Yuval Tassa, Timothy Lillicrap, Daan Wierstra, Jonathan J. Hunt, Alexander Pritzel, Christopher K. I. Williams, John Winn and Geoffrey E. Hinton. Their work appears in journals such as Journal of Neuroscience, International Journal of Computer Vision, Physical Review Fluids, ACM Transactions on Graphics 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.