François Chollet
- Computer Vision and Pattern Recognition top 0.05%
- Cognitive Neuroscience top 0.2%
- Artificial Intelligence top 0.2%
- Radiology, Nuclear Medicine and Imaging top 0.2%
- Neurology top 0.1%
- Co-authors
- R. S. J. FrackowiakRichard G. WiseIsabelle LoubinouxKarl FristonOlivier RascolJérémie ParienteVittorio Di PieroA Rascol
- Topics
- Stroke Rehabilitation and Recovery (31 papers)Transcranial Magnetic Stimulation Studies (25 papers)Acute Ischemic Stroke Management (17 papers)
- Journals
- CirculationPLoS ONENeuroImage
- Partner nations
- FranceUnited StatesUnited Kingdom
In The Last Decade
François Chollet
124 papers receiving 21.2k citations
Hit Papers
Peers
Comparison fields: 5 of 225
- Computer Vision and Pattern Recognition 6.1k
- Cognitive Neuroscience 4.6k
- Artificial Intelligence 3.8k
- Radiology, Nuclear Medicine and Imaging 3.2k
- Neurology 2.9k
Countries citing papers authored by François Chollet
This map shows the geographic impact of François Chollet'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 François Chollet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites François Chollet more than expected).
Fields of papers citing papers by François Chollet
This network shows the impact of papers produced by François Chollet. 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 François Chollet. The network helps show where François Chollet may publish in the future.
Co-authorship network of co-authors of François Chollet
This figure shows the co-authorship network connecting the top 25 collaborators of François Chollet. A scholar is included among the top collaborators of François Chollet 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 François Chollet. François Chollet 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 | 11 | |
| 3 | 16 | |
| 4 | Deep learning with Pythonbreakdown → | 520 |
| 5 | Deep Learning with R | 61 |
| 6 | Keras: The Python Deep Learning librarybreakdown → | 596 |
| 7 | DeepMath - Deep Sequence Models for Premise Selection | 15 |
| 8 | Deep Learning with Separable Convolutions | 7 |
| 9 | 3 | |
| 10 | 0 | |
| 11 | 10 | |
| 12 | 3 | |
| 13 | 1 | |
| 14 | 38 | |
| 15 | 92 | |
| 16 | 31 | |
| 17 | 87 | |
| 18 | 328 | |
| 19 | 3 | |
| 20 | 16 |
About François Chollet
François Chollet is a scholar working on Rehabilitation, Neurology and Neurology, having authored 128 papers that have together received 22.0k indexed citations. Recurring topics across this work include Stroke Rehabilitation and Recovery (31 papers), Transcranial Magnetic Stimulation Studies (25 papers) and Acute Ischemic Stroke Management (17 papers). The work is most often cited by research in Neurology (2.9k citations), Computer Vision and Pattern Recognition (6.1k citations) and Rehabilitation (1.7k citations). François Chollet has collaborated with scholars based in France, United States and United Kingdom. Frequent co-authors include R. S. J. Frackowiak, Richard G. Wise, Isabelle Loubinoux, Karl Friston, Olivier Rascol, Jérémie Pariente, Vittorio Di Piero, A Rascol, Raymond J. Dolan and Jean–Luc Nespoulous. Their work appears in journals such as Circulation, PLoS ONE and NeuroImage.
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.