Philippe Gaussier
- Cognitive Neuroscience top 2%
- Social Psychology top 5%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Cellular and Molecular Neuroscience top 10%
- Co-authors
- J.P. BanquetMathias QuoySorin MogaArnaud RevelPierre AndryStéphane ZrehenNicolas CuperlierSofiane Boucenna
- Topics
- Neural dynamics and brain function (20 papers)Memory and Neural Mechanisms (19 papers)Reinforcement Learning in Robotics (13 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
- Partner nations
- FranceSwitzerlandUkraine
In The Last Decade
Philippe Gaussier
89 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 89
- Cognitive Neuroscience 690
- Social Psychology 323
- Artificial Intelligence 307
- Computer Vision and Pattern Recognition 278
- Cellular and Molecular Neuroscience 211
Countries citing papers authored by Philippe Gaussier
This map shows the geographic impact of Philippe Gaussier'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 Philippe Gaussier with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philippe Gaussier more than expected).
Fields of papers citing papers by Philippe Gaussier
This network shows the impact of papers produced by Philippe Gaussier. 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 Philippe Gaussier. The network helps show where Philippe Gaussier may publish in the future.
Co-authorship network of co-authors of Philippe Gaussier
This figure shows the co-authorship network connecting the top 25 collaborators of Philippe Gaussier. A scholar is included among the top collaborators of Philippe Gaussier based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Philippe Gaussier. Philippe Gaussier is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 18 | |
| 3 | 2 | |
| 4 | 15 | |
| 5 | 10 | |
| 6 | 7 | |
| 7 | 33 | |
| 8 | 2 | |
| 9 | 4 | |
| 10 | 20 | |
| 11 | 18 | |
| 12 | 17 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 74 | |
| 16 | Learning and motivational couplings promote smarter behaviors of an animat in an unknown world | 1 |
| 17 | 1 | |
| 18 | 94 | |
| 19 | Taking inspiration from the Hippocampus can help solving robotics problems. | 2 |
| 20 | Perception to Action Conference, 1994 | 2 |
About Philippe Gaussier
Philippe Gaussier is a scholar working on Cognitive Neuroscience, Sensory Systems and Social Psychology, having authored 95 papers that have together received 1.2k indexed citations. Recurring topics across this work include Neural dynamics and brain function (20 papers), Memory and Neural Mechanisms (19 papers) and Reinforcement Learning in Robotics (13 papers). The work is most often cited by research in Cognitive Neuroscience (690 citations), Social Psychology (323 citations) and Computer Vision and Pattern Recognition (278 citations). Philippe Gaussier has collaborated with scholars based in France, Switzerland and Ukraine. Frequent co-authors include J.P. Banquet, Mathias Quoy, Sorin Moga, Arnaud Revel, Pierre Andry, Stéphane Zrehen, Nicolas Cuperlier, Sofiane Boucenna, Carine Giovannangeli and Étienne Save. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.
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.