Bertrand Rouet‐Leduc

968 total citations
27 papers, 617 citations indexed

About

Bertrand Rouet‐Leduc is a scholar working on Geophysics, Artificial Intelligence and Condensed Matter Physics. According to data from OpenAlex, Bertrand Rouet‐Leduc has authored 27 papers receiving a total of 617 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Geophysics, 15 papers in Artificial Intelligence and 4 papers in Condensed Matter Physics. Recurrent topics in Bertrand Rouet‐Leduc's work include earthquake and tectonic studies (15 papers), Seismology and Earthquake Studies (14 papers) and Earthquake Detection and Analysis (12 papers). Bertrand Rouet‐Leduc is often cited by papers focused on earthquake and tectonic studies (15 papers), Seismology and Earthquake Studies (14 papers) and Earthquake Detection and Analysis (12 papers). Bertrand Rouet‐Leduc collaborates with scholars based in United States, France and Japan. Bertrand Rouet‐Leduc's co-authors include Claudia Hulbert, Paul A. Johnson, Chris Marone, Christopher X. Ren, David Bolton, Jacques Rivière, Kipton Barros, Turab Lookman, C. J. Humphreys and Ian W. McBrearty and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Bertrand Rouet‐Leduc

26 papers receiving 593 citations

Peers

Bertrand Rouet‐Leduc

GEOPH

CMP

Masayuki Kano Japan

Gang Luo China

Ossian O’Reilly United States

В. Б. Смирнов Russia

Lei Fu China

Carl Carlson United States

G. Paparo Italy

Michio Otsuki Japan

Zhicheng Lü China

V. Hadjicontis Greece

Masayuki Kano Japan

Bertrand Rouet‐Leduc

269 ×0.7

GEOPH

108 ×0.3

72 ×1.1

27 ×0.5

63 ×1.8

CMP

Citations per year, relative to Bertrand Rouet‐Leduc Bertrand Rouet‐Leduc (= 1×) peers Masayuki Kano

Countries citing papers authored by Bertrand Rouet‐Leduc

Since Specialization

Citations

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

Fields of papers citing papers by Bertrand Rouet‐Leduc

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bertrand Rouet‐Leduc. 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 Bertrand Rouet‐Leduc. The network helps show where Bertrand Rouet‐Leduc may publish in the future.

Co-authorship network of co-authors of Bertrand Rouet‐Leduc

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

All Works

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20 of 20 papers shown

Kaneko, Yoshihiro, et al.. (2025). Machine learning predicts meter-scale laboratory earthquakes. Nature Communications. 16(1). 9593–9593.

Abolt, Charles J., et al.. (2024). Advancing the Limits of InSAR to Detect Crustal Displacement from Low-Magnitude Earthquakes through Deep Learning. Remote Sensing. 16(11). 2019–2019. 2 indexed citations

Rouet‐Leduc, Bertrand & Claudia Hulbert. (2024). Automatic detection of methane emissions in multispectral satellite imagery using a vision transformer. Nature Communications. 15(1). 3801–3801. 26 indexed citations

Jolivet, Romain, Jorge Jara, Bertrand Rouet‐Leduc, et al.. (2023). Daily to Centennial Behavior of Aseismic Slip Along the Central Section of the North Anatolian Fault. Journal of Geophysical Research Solid Earth. 128(7). 12 indexed citations

Johnson, Christopher, Philippe Roux, Daniel T. Trugman, et al.. (2023). Mapping Glacier Basal Sliding Applying Machine Learning. Journal of Geophysical Research Earth Surface. 128(11). 3 indexed citations

Blétery, Quentin, et al.. (2023). Rapid Source Characterization of the Maule Earthquake Using Prompt Elasto‐Gravity Signals. Journal of Geophysical Research Solid Earth. 128(9). 4 indexed citations

Blétery, Quentin, et al.. (2022). Instantaneous tracking of earthquake growth with elastogravity signals. Nature. 606(7913). 319–324. 27 indexed citations

Johnson, Paul A., Bertrand Rouet‐Leduc, L. J. Pyrak‐Nolte, et al.. (2021). Laboratory earthquake forecasting: A machine learning competition. Proceedings of the National Academy of Sciences. 118(5). 72 indexed citations

Hulbert, Claudia, Bertrand Rouet‐Leduc, Romain Jolivet, & Paul A. Johnson. (2020). An exponential build-up in seismic energy suggests a months-long nucleation of slow slip in Cascadia. Nature Communications. 11(1). 4139–4139. 28 indexed citations

10.

Ren, Christopher X., Claudia Hulbert, Paul E. Johnson, & Bertrand Rouet‐Leduc. (2020). Machine learning and fault rupture: a review. EarthArXiv (OSF Preprints). 1 indexed citations

11.

Rouet‐Leduc, Bertrand, Claudia Hulbert, Ian W. McBrearty, & Paul A. Johnson. (2020). Probing Slow Earthquakes With Deep Learning. Geophysical Research Letters. 47(4). e2019GL085870–e2019GL085870. 44 indexed citations

12.

Rouet‐Leduc, Bertrand, et al.. (2019). Deep learning InSAR: atmospheric noise removal and small deformation signal extraction from InSAR time series using a convolutional autoencoder. AGU Fall Meeting Abstracts. 2019. 4 indexed citations

13.

Bolton, David, Parisa Shokouhi, Bertrand Rouet‐Leduc, et al.. (2019). Characterizing Acoustic Signals and Searching for Precursors during the Laboratory Seismic Cycle Using Unsupervised Machine Learning. Seismological Research Letters. 90(3). 1088–1098. 42 indexed citations

14.

Hulbert, Claudia, Bertrand Rouet‐Leduc, Ian W. McBrearty, & Paul A. Johnson. (2018). Patterns in Seismic Energy and Earthquake Hazard in Northern Chile. AGU Fall Meeting Abstracts. 2018. 1 indexed citations

15.

Hulbert, Claudia, Bertrand Rouet‐Leduc, Paul A. Johnson, et al.. (2018). Similarity of fast and slow earthquakes illuminated by machine learning. Nature Geoscience. 12(1). 69–74. 107 indexed citations

16.

Rouet‐Leduc, Bertrand, Claudia Hulbert, David Bolton, et al.. (2017). Fault Friction Constitutive Law Derived From Continuous Acoustic Emissions by Machine Learning. arXiv (Cornell University). 1 indexed citations

17.

Rouet‐Leduc, Bertrand, Claudia Hulbert, Kipton Barros, Turab Lookman, & C. J. Humphreys. (2017). Automatized convergence of optoelectronic simulations using active machine learning. Applied Physics Letters. 111(4). 10 indexed citations

18.

Rouet‐Leduc, Bertrand, Kipton Barros, Turab Lookman, & C. J. Humphreys. (2016). Optimisation of GaN LEDs and the reduction of efficiency droop using active machine learning. Scientific Reports. 6(1). 24862–24862. 41 indexed citations

19.

Barros, Kipton, et al.. (2015). Distributed Database Kriging for Adaptive Sampling ( D 2 K A S ). Computer Physics Communications. 192. 138–147. 21 indexed citations

20.

Rouet‐Leduc, Bertrand, Kipton Barros, Christoph Junghans, et al.. (2014). Spatial adaptive sampling in multiscale simulation. Computer Physics Communications. 185(7). 1857–1864. 18 indexed citations

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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