Ling Guo
- Cognitive Neuroscience top 2%
- Signal Processing top 1%
- Statistical and Nonlinear Physics top 1%
- Artificial Intelligence top 5%
- Statistics, Probability and Uncertainty top 0.5%
- Co-authors
- Alejandro PazosDaniel RiveroGeorge Em KarniadakisDongkun ZhangJulián DoradoLu LuJuan R. RabuñalTao Tang
- Topics
- Probabilistic and Robust Engineering Design (19 papers)Model Reduction and Neural Networks (10 papers)Structural Health Monitoring Techniques (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of Molecular BiologyJournal of Computational Physics
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Ling Guo
50 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 137
- Cognitive Neuroscience 896
- Signal Processing 665
- Statistical and Nonlinear Physics 649
- Artificial Intelligence 462
- Statistics, Probability and Uncertainty 358
Countries citing papers authored by Ling Guo
This map shows the geographic impact of Ling Guo'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 Ling Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ling Guo more than expected).
Fields of papers citing papers by Ling Guo
This network shows the impact of papers produced by Ling Guo. 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 Ling Guo. The network helps show where Ling Guo may publish in the future.
Co-authorship network of co-authors of Ling Guo
This figure shows the co-authorship network connecting the top 25 collaborators of Ling Guo. A scholar is included among the top collaborators of Ling Guo 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 Ling Guo. Ling Guo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisonsbreakdown → | 215 |
| 6 | 1 | |
| 7 | 8 | |
| 8 | 8 | |
| 9 | 184 | |
| 10 | 33 | |
| 11 | 24 | |
| 12 | 28 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 329 | |
| 16 | 312 | |
| 17 | 24 | |
| 18 | 2 | |
| 19 | 1 | |
| 20 | 12 |
About Ling Guo
Ling Guo is a scholar working on Statistics, Probability and Uncertainty, Statistical and Nonlinear Physics and Numerical Analysis, having authored 54 papers that have together received 2.3k indexed citations. Recurring topics across this work include Probabilistic and Robust Engineering Design (19 papers), Model Reduction and Neural Networks (10 papers) and Structural Health Monitoring Techniques (5 papers). The work is most often cited by research in Signal Processing (665 citations), Statistical and Nonlinear Physics (649 citations) and Statistics, Probability and Uncertainty (358 citations). Ling Guo has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Alejandro Pazos, Daniel Rivero, George Em Karniadakis, Dongkun Zhang, Julián Dorado, Lu Lu, Juan R. Rabuñal, Tao Tang, Liang Yan and Apostolos F. Psaros. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Molecular Biology and Journal of Computational Physics.
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.