HelioWebRomain Jolivet
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A[Romain Jolivet]
AC["Associated Concepts (25)"]
AW["Authored Works (11)"]
CA["Linked Co-Authors (23)"]
CI["Linked Collaborating Institutions (20)"]
A== dcterms:relation ==>AC
AW== author ==>A
AW== author ==>CA
AW== affil ==>CI
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click AW "#authored-works"
click CA "#co-authors"
click CI "#collaborating-institutions"
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- ORCiD
- https://orcid.org/0000-0002-9896-3651
- OpenAlex ID
- https://openalex.org/A5052546409 (API record)
Associated Concepts [?]
- Geology
- Physics
- Seismology
- Biology
- Engineering
- Paleontology
- Geography
- Aerospace engineering
- Thermodynamics
- Computer science
- Slip (aerodynamics)
- Fault (geology)
- Quantum mechanics
- Tectonics
- Geodesy
- Artificial intelligence
- Astronomy
- Remote sensing
- Computer vision
- Optics
- Civil engineering
- Interferometry
- Synthetic aperture radar
- Interferometric synthetic aperture radar
- Mathematics
Authored Works
sorted by decreasing year, and then by display-name
- Spatial patterns of long-term forearc uplift inferred from river profiles, and their comparison with short-term deformation
- Seismogenic Potential of the Subduction in Northern Chile
- Postseismic Deformation due to the Mw 7.2, 2021 Nippes Earthquake: an Analysis of the Rheological Properties
- Monitoring and modeling of the Sacramento Valley aquifer (California) using geodetic and piezometric measurements
- Exploring Physical Properties and Processing Choices at the Origin of Misclosure and Associated Biases in InSAR Time Series: a Case Study in Normandie (France)
- Dramatic subsidence in Balochistan (Pakistan) due to extensive water withdrawal measured with InSAR
- Autonomous Extraction of Millimeter-scale Deformation in InSAR Time Series Using Deep Learning, and application to the San Andreas Fault
- Signature of transition to supershear rupture speed in coseismic off-fault damage zone
- Complex Fault Rupture Geometry and Slip Distribution of the Mw7.2 Nippes Earthquake, Haiti.
- Citizen seismology helps decipher the 2021 Haiti earthquake
- Autonomous Detection of Groundwater Level Variations in InSAR Time Series Using Deep Learning
Linked Co-Authors
- Anthony Lomax
- B. Raimbault
- Bar Oryan
- Bertrand Rouet‐Leduc
- Boris Gailleton
- Chris Rollins
- Donald F. Argus
- E. Calais
- Jean‐Arthur Olive
- Jorge Jara
- Kristel Chanard
- Kurama Okubo
- Kurt C. Solander
- Laurent Longuevergne
- Liuwei Xu
- Lucile Bruhat
- Marion Y. Thomas
- Pablo Lara
- Quentin Blétery
- Stacy Larochelle
- Yann Klinger
- Yo Fukushima
- Zacharie Duputel
Linked Collaborating Institutions
- California Institute of Technology
- Direction des Applications Militaires, Ile-de-France
- Ecole Normale Superieure, Paris, France
- Geological and Nuclear Science Ltd, New Zealand
- Geophysical Institute of Peru
- Helmholtz Center for Geosciences, Potsdam
- Jet Propulsion Laboratory
- Kyoto University, Japan
- Laboratoire de Geologie de l'ENS
- Los Alamos National Laboratory, New Mexico
- National Research Center for Disaster Prevention, Japan
- New Mexico Institute of Mining and Technology
- Observatoire de la Cote d'Azur, France
- State University of Haiti
- Tohoku University, Japan
- Universite de Rennes 1, France
- University of California, Los Angeles
- University of Edinburgh, UK
- University of Liege, Belgium
- Woods Hole Oceanographic Institute, Massachusetts
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