Hugo Touvron

5 papers receiving 4.0k citations

Hit Papers

Emerging Properties in Self-Supervised Vision Transformers2020202620222024202120202022202250010001.5k2.0k2.5k

Peers

Hugo Touvron
Comparison fields: 5 of 158
  • Computer Vision and Pattern Recognition 2.4k
  • Artificial Intelligence 1.7k
  • Radiology, Nuclear Medicine and Imaging 445
  • Media Technology 407
  • Aerospace Engineering 259
Replace Mathilde Caron with:
Mathilde Caron United States
Chao-Yuan Wu United States
Ishan Misra United States
Spencer Whitehead United States
Laura Gustafson
Eric Mintun United States
Wan‐Yen Lo United States
Clément Farabet United States
Jianguo Zhang China
Sanghyuk Chun South Korea
Hugo Touvron relative to Mathilde Caron United States Mathilde Caron's profile →
Citations per field
00.5×1.7×
Mathilde Caron · 1×
Citations per year

Countries citing papers authored by Hugo Touvron

Since Specialization
Citations

This map shows the geographic impact of Hugo Touvron'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 Hugo Touvron with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hugo Touvron more than expected).

Fields of papers citing papers by Hugo Touvron

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hugo Touvron. 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 Hugo Touvron. The network helps show where Hugo Touvron may publish in the future.

Co-authorship network of co-authors of Hugo Touvron

This figure shows the co-authorship network connecting the top 25 collaborators of Hugo Touvron. A scholar is included among the top collaborators of Hugo Touvron 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 Hugo Touvron. Hugo Touvron is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

7 of 7 papers shown
#WorkIndexed citations
1 0
2 0
3
ConViT: improving vision transformers with soft convolutional inductive biases*breakdown →
478
4
ResMLP: Feedforward Networks for Image Classification With Data-Efficient Trainingbreakdown →
444
5 41
6
Emerging Properties in Self-Supervised Vision Transformersbreakdown →
2519
7
Training data-efficient image transformers & distillation through attentionbreakdown →
607

About Hugo Touvron

Hugo Touvron is a scholar working on Computer Vision and Pattern Recognition, Biophysics and Artificial Intelligence, having authored 7 papers that have together received 4.1k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (4 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Advanced Image and Video Retrieval Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.4k citations), Artificial Intelligence (1.7k citations) and Media Technology (407 citations). Hugo Touvron has collaborated with scholars based in France, Israel and United States. Frequent co-authors include Hervé Jeǵou, Piotr Bojanowski, Mathilde Caron, Armand Joulin, Ishan Misra, Julien Mairal, Alexandre Sablayrolles, Matthijs Douze, Francisco Massa and Matthew L. Leavitt. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, PLoS Computational Biology and Journal of Statistical Mechanics Theory and Experiment.

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.

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