Ronan Le Bras

74 papers receiving 1.9k citations

Hit Papers

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Peers

Ronan Le Bras
Comparison fields: 5 of 127
  • Artificial Intelligence 1.2k
  • Computer Vision and Pattern Recognition 590
  • Geophysics 131
  • Materials Chemistry 121
  • Information Systems 97
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Rong Hu China
Alexander Mordvintsev United States
Ludwig Schubert United States
Javier Muguerza Spain
Zhifei Zhang China
Timothy Dozat United States
Karthikeyan Natesan Ramamurthy United States
Shotaro Akaho Japan
Samuel Bowman United States
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Countries citing papers authored by Ronan Le Bras

Since Specialization
Citations

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

Fields of papers citing papers by Ronan Le Bras

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ronan Le Bras. 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 Ronan Le Bras. The network helps show where Ronan Le Bras may publish in the future.

Co-authorship network of co-authors of Ronan Le Bras

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 3
3 2
4 57
5 108
6 98
7
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8 55
9 15
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G-DAUG: Generative Data Augmentation for Commonsense Reasoning
5
11
Ground-truth observations and modeling of an extensive air-gun seismic survey recorded at two hydroacoustic stations of the IMS network
1
12 1
13
Localization using P-phases recorded on the CTBT IMS hydro-acoustic stations
2
14
Evaluation of NET-VISA association and location performance using Ground Truth events and RSTT model based SSSCs
1
15
Relative location method in hydroacoustics and application to several examples including a seismic survey for which ground truth is available.
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Variable elimination in the Fourier domain
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A computational challenge problem in materials discovery: synthetic problem generator and real-world datasets
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Double-wheel graphs are graceful
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Infrasound Event Analysis into the IDC Operations
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Supervised Classification Methods for Seismic Phase Identification
3

About Ronan Le Bras

Ronan Le Bras is a scholar working on Artificial Intelligence, Geophysics and Oceanography, having authored 78 papers that have together received 1.9k indexed citations. Recurring topics across this work include Topic Modeling (29 papers), Natural Language Processing Techniques (24 papers) and Seismic Waves and Analysis (12 papers). The work is most often cited by research in Artificial Intelligence (1.2k citations), Computer Vision and Pattern Recognition (590 citations) and Health Informatics (29 citations). Ronan Le Bras has collaborated with scholars based in United States, Denmark and United Kingdom. Frequent co-authors include Yejin Choi, Chandra Bhagavatula, Maxwell Forbes, Jack Hessel, Keisuke Sakaguchi, Ari Holtzman, Ximing Lu, Peter West, Lifu Huang and Sean Welleck. Their work appears in journals such as Communications of the ACM, The Journal of the Acoustical Society of America and Bulletin of the Seismological Society of America.

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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