Vivien Seguy
Impact in
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- Data Visualization and Analytics
- Advanced Image and Video Retrieval Techniques
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- Geographic Information Systems Studies
Papers in
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- Sparse and Compressive Sensing Techniques 2
- Advanced Adaptive Filtering Techniques 1
- 3D Shape Modeling and Analysis 1
- Co-authors
- Michael T. Gastner (1 shared paper)Marco Cuturi (3 shared papers)Nicolas Courty (1 shared paper)Mathieu Blondel (2 shared papers)Bharath Bhushan Damodaran (1 shared paper)Rémi Flamary (1 shared paper)Nicolas Papadakis (2 shared papers)Jérémie Bigot (2 shared papers)
In The Last Decade
Vivien Seguy
8 papers receiving 128 citations
Peers
Comparison fields: 5 of 68
- Computer Vision and Pattern Recognition 43
- Geography, Planning and Development 11
- Media Technology 17
- Statistics and Probability 14
- Signal Processing 16
Countries citing papers authored by Vivien Seguy
This map shows the geographic impact of Vivien Seguy'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 Vivien Seguy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vivien Seguy more than expected).
Fields of papers citing papers by Vivien Seguy
This network shows the impact of papers produced by Vivien Seguy. 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 Vivien Seguy. The network helps show where Vivien Seguy may publish in the future.
Co-authors
The 9 scholars most cited alongside Vivien Seguy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 38 | |
| 2 | 2019 | 31 | |
| 3 | 2018 | 24 | |
| 4 | Smooth and Sparse Optimal Transport | 2018 | 15 |
| 5 | 2015 | 15 | |
| 6 | 2018 | 10 | |
| 7 | Log-PCA versus Geodesic PCA of histograms in the Wasserstein space | 2017 | 1 |
| 8 | 2021 | 1 |
About Vivien Seguy
Vivien Seguy is a scholar working on Computational Mechanics, Statistical and Nonlinear Physics, Signal Processing, Artificial Intelligence and Computational Theory and Mathematics, having authored 8 papers that have together received 135 indexed citations. Recurring topics across this work include Point processes and geometric inequalities (2 papers), Sparse and Compressive Sensing Techniques (2 papers), Advanced Adaptive Filtering Techniques (1 paper), Data Management and Algorithms (1 paper), Remote-Sensing Image Classification (1 paper), Speech and Audio Processing (1 paper), Geometric Analysis and Curvature Flows (1 paper) and 3D Shape Modeling and Analysis (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (43 citations), Geography, Planning and Development (11 citations), Media Technology (17 citations), Statistics and Probability (14 citations) and Signal Processing (16 citations). Vivien Seguy has collaborated with scholars based in Japan, France and Singapore. Frequent co-authors include Michael T. Gastner, Marco Cuturi, Nicolas Courty, Mathieu Blondel, Bharath Bhushan Damodaran, Rémi Flamary, Nicolas Papadakis, Jérémie Bigot and Hiroshi Sawada. Their work appears in journals such as The Visual Computer, SIAM Journal on Scientific Computing, Proceedings of the National Academy of Sciences, Computer Vision and Image Understanding and EURASIP Journal on Advances in Signal Processing.
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.