Hubert Soyer
Impact in
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function
- Neural and Behavioral Psychology Studies
- Memory and Neural Mechanisms
- EEG and Brain-Computer Interfaces
- Artificial Intelligence top 5%
- Reinforcement Learning in Robotics
Papers in
-
- Reinforcement Learning in Robotics 3
- Topic Modeling 3
- Natural Language Processing Techniques 3
- Co-authors
- Dharshan Kumaran (2 shared papers)Demis Hassabis (1 shared paper)Zeb Kurth‐Nelson (1 shared paper)Matthew Botvinick (2 shared papers)Joel Z. Leibo (1 shared paper)Jane X. Wang (1 shared paper)Dhruva Tirumala (2 shared papers)Wojciech Marian Czarnecki (1 shared paper)
- Journals
- Nature Neuroscience (1 paper)Lecture notes in computer science (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)arXiv (Cornell University) (2 papers)
- Partner nations
- United KingdomGermanyItaly
In The Last Decade
Hubert Soyer
9 papers receiving 710 citations
Hubert Soyer's Hit Papers
Peers
Comparison fields: 5 of 89
- Cognitive Neuroscience 260
- Artificial Intelligence 318
- Computer Vision and Pattern Recognition 191
- General Decision Sciences 11
- Media Technology 33
Countries citing papers authored by Hubert Soyer
This map shows the geographic impact of Hubert Soyer'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 Hubert Soyer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hubert Soyer more than expected).
Fields of papers citing papers by Hubert Soyer
This network shows the impact of papers produced by Hubert Soyer. 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 Hubert Soyer. The network helps show where Hubert Soyer may publish in the future.
Co-authors
The 25 scholars most cited alongside Hubert Soyer, 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 | Prefrontal cortex as a meta-reinforcement learning system Hit paper breakdown → | 2018 | 340 |
| 2 | 2016 | 190 | |
| 3 | 2019 | 123 | |
| 4 | 2014 | 51 | |
| 5 | Size (and Domain) Matters: Evaluating Semantic Word Space Representations for Biomedical Text | 2012 | 17 |
| 6 | Uncovering Surprising Behaviors in Reinforcement Learning via Worst-case Analysis | 2018 | 6 |
| 7 | V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control | 2020 | 3 |
| 8 | Japanese to English Machine Translation using Preordering and Compositional Distributed Semantics | 2014 | 3 |
| 9 | 2015 | 2 |
About Hubert Soyer
Hubert Soyer is a scholar working on Artificial Intelligence, Molecular Biology, Computer Vision and Pattern Recognition, Cognitive Neuroscience and Experimental and Cognitive Psychology, having authored 9 papers that have together received 735 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (3 papers), Topic Modeling (3 papers), Natural Language Processing Techniques (3 papers), Advanced Vision and Imaging (1 paper), Mental Health Research Topics (1 paper), Image and Signal Denoising Methods (1 paper), Neural dynamics and brain function (1 paper) and Neural and Behavioral Psychology Studies (1 paper). The work is most often cited by research in Cognitive Neuroscience (260 citations), Artificial Intelligence (318 citations), Computer Vision and Pattern Recognition (191 citations), General Decision Sciences (11 citations) and Media Technology (33 citations). Hubert Soyer has collaborated with scholars based in United Kingdom, Germany and Italy. Frequent co-authors include Dharshan Kumaran, Demis Hassabis, Zeb Kurth‐Nelson, Matthew Botvinick, Joel Z. Leibo, Jane X. Wang, Dhruva Tirumala, Wojciech Marian Czarnecki, Lasse Espeholt and Simon Schmitt. Their work appears in journals such as Nature Neuroscience, Lecture notes in computer science, Proceedings of the AAAI Conference on Artificial Intelligence and arXiv (Cornell University).
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.