Guillaume Bellec
- Electrical and Electronic Engineering top 10%
- Cognitive Neuroscience top 10%
- Artificial Intelligence top 10%
- Cellular and Molecular Neuroscience
- Computer Vision and Pattern Recognition
- Co-authors
- Robert LegensteinWolfgang MaassDarjan SalajAnand SubramoneyFranz ScherrDavid KappelGiovanni CherubiniAngeliki Pantazi
- Topics
- Advanced Memory and Neural Computing (8 papers)Neural dynamics and brain function (6 papers)Neural Networks and Applications (4 papers)
- Partner nations
- AustriaSwitzerlandUnited Kingdom
In The Last Decade
Guillaume Bellec
10 papers receiving 394 citations
Hit Papers
Peers
Comparison fields: 5 of 50
- Electrical and Electronic Engineering 319
- Cognitive Neuroscience 244
- Artificial Intelligence 175
- Cellular and Molecular Neuroscience 91
- Computer Vision and Pattern Recognition 23
Countries citing papers authored by Guillaume Bellec
This map shows the geographic impact of Guillaume Bellec'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 Guillaume Bellec with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guillaume Bellec more than expected).
Fields of papers citing papers by Guillaume Bellec
This network shows the impact of papers produced by Guillaume Bellec. 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 Guillaume Bellec. The network helps show where Guillaume Bellec may publish in the future.
Co-authorship network of co-authors of Guillaume Bellec
This figure shows the co-authorship network connecting the top 25 collaborators of Guillaume Bellec. A scholar is included among the top collaborators of Guillaume Bellec 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 Guillaume Bellec. Guillaume Bellec is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 20 | |
| 4 | 18 | |
| 5 | 34 | |
| 6 | A solution to the learning dilemma for recurrent networks of spiking neuronsbreakdown → | 269 |
| 7 | Eligibility traces provide a data-inspired alternative to backpropagation through time | 5 |
| 8 | 32 | |
| 9 | Deep Rewiring: Training very sparse deep networks | 17 |
| 10 | 2 | |
| 11 | Creating audio based experiments as social Web games with the CASimIR framework | 2 |
About Guillaume Bellec
Guillaume Bellec is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Computer Science Applications, having authored 11 papers that have together received 402 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (8 papers), Neural dynamics and brain function (6 papers) and Neural Networks and Applications (4 papers). The work is most often cited by research in Cognitive Neuroscience (244 citations), Electrical and Electronic Engineering (319 citations) and Artificial Intelligence (175 citations). Guillaume Bellec has collaborated with scholars based in Austria, Switzerland and United Kingdom. Frequent co-authors include Robert Legenstein, Wolfgang Maass, Darjan Salaj, Anand Subramoney, Franz Scherr, David Kappel, Giovanni Cherubini, Angeliki Pantazi, Wulfram Gerstner and Stanisław Woźniak. Their work appears in journals such as Nature Communications, Scientific Reports and eLife.
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.