Luis Tenorio
- Astronomy and Astrophysics top 5%
- Geophysics top 5%
- Nuclear and High Energy Physics top 10%
- Ocean Engineering top 5%
- Artificial Intelligence top 10%
- Co-authors
- John A. ScalesEldad HaberPing MaCharles H. LineweaverMaarten V. de HoopR. D. van der HilstLior HoreshP. M. Lubin
- Topics
- Sparse and Compressive Sensing Techniques (10 papers)Numerical methods in inverse problems (8 papers)Seismic Imaging and Inversion Techniques (8 papers)
- Partner nations
- United StatesSpainItaly
In The Last Decade
Luis Tenorio
59 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Astronomy and Astrophysics 521
- Geophysics 477
- Nuclear and High Energy Physics 230
- Ocean Engineering 166
- Artificial Intelligence 141
Countries citing papers authored by Luis Tenorio
This map shows the geographic impact of Luis Tenorio'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 Luis Tenorio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luis Tenorio more than expected).
Fields of papers citing papers by Luis Tenorio
This network shows the impact of papers produced by Luis Tenorio. 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 Luis Tenorio. The network helps show where Luis Tenorio may publish in the future.
Co-authorship network of co-authors of Luis Tenorio
This figure shows the co-authorship network connecting the top 25 collaborators of Luis Tenorio. A scholar is included among the top collaborators of Luis Tenorio 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 Luis Tenorio. Luis Tenorio is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 5 | |
| 5 | 15 | |
| 6 | 8 | |
| 7 | 7 | |
| 8 | 2 | |
| 9 | Efficient Learning of Practical Markov Random Fields with Exact Inference. | 1 |
| 10 | 3 | |
| 11 | 83 | |
| 12 | Imaging and characterizing structure in Earth's deep interior | 1 |
| 13 | 6 | |
| 14 | 29 | |
| 15 | 14 | |
| 16 | 5 | |
| 17 | 2 | |
| 18 | 8 | |
| 19 | 4 | |
| 20 | 173 |
About Luis Tenorio
Luis Tenorio is a scholar working on Statistics, Probability and Uncertainty, Mathematical Physics and Statistics and Probability, having authored 61 papers that have together received 1.6k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (10 papers), Numerical methods in inverse problems (8 papers) and Seismic Imaging and Inversion Techniques (8 papers). The work is most often cited by research in Geophysics (477 citations), Astronomy and Astrophysics (521 citations) and Nuclear and High Energy Physics (230 citations). Luis Tenorio has collaborated with scholars based in United States, Spain and Italy. Frequent co-authors include John A. Scales, Eldad Haber, Ping Ma, Charles H. Lineweaver, Maarten V. de Hoop, R. D. van der Hilst, Lior Horesh, P. M. Lubin, P. Keegstra and Sang‐Heon Shim. Their work appears in journals such as Science, Journal of Geophysical Research Atmospheres and Environmental Science & Technology.
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.