Carmeliza Navasca
- Computational Mathematics top 0.5%
- Computational Theory and Mathematics top 5%
- Computational Mechanics top 10%
- Statistical and Nonlinear Physics top 10%
- Signal Processing
- Co-authors
- Na LiChristino TamonMichael BrazellStefan KindermannLieven De LathauwerKirsten MorrisArthur J. KrenerXiaofei Wang
- Topics
- Tensor decomposition and applications (16 papers)Sparse and Compressive Sensing Techniques (11 papers)Image and Signal Denoising Methods (4 papers)
- Journals
- Chemometrics and Intelligent Laboratory SystemsNonlinear AnalysisLinear Algebra and its Applications
- Partner nations
- United StatesAustriaChina
In The Last Decade
Carmeliza Navasca
21 papers receiving 339 citations
Peers
Comparison fields: 5 of 51
- Computational Mathematics 238
- Computational Theory and Mathematics 126
- Computational Mechanics 73
- Statistical and Nonlinear Physics 48
- Signal Processing 39
Countries citing papers authored by Carmeliza Navasca
This map shows the geographic impact of Carmeliza Navasca'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 Carmeliza Navasca with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carmeliza Navasca more than expected).
Fields of papers citing papers by Carmeliza Navasca
This network shows the impact of papers produced by Carmeliza Navasca. 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 Carmeliza Navasca. The network helps show where Carmeliza Navasca may publish in the future.
Co-authorship network of co-authors of Carmeliza Navasca
This figure shows the co-authorship network connecting the top 25 collaborators of Carmeliza Navasca. A scholar is included among the top collaborators of Carmeliza Navasca 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 Carmeliza Navasca. Carmeliza Navasca is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 14 | |
| 2 | 4 | |
| 3 | 2 | |
| 4 | 4 | |
| 5 | 8 | |
| 6 | 7 | |
| 7 | 2 | |
| 8 | 3 | |
| 9 | 146 | |
| 10 | 17 | |
| 11 | 9 | |
| 12 | 1 | |
| 13 | 51 | |
| 14 | 5 | |
| 15 | Swamp reducing technique for tensor decomposition | 40 |
| 16 | 9 | |
| 17 | 8 | |
| 18 | 2 | |
| 19 | 1 | |
| 20 | 16 |
About Carmeliza Navasca
Carmeliza Navasca is a scholar working on Computational Mathematics, Computational Mechanics and Numerical Analysis, having authored 22 papers that have together received 351 indexed citations. Recurring topics across this work include Tensor decomposition and applications (16 papers), Sparse and Compressive Sensing Techniques (11 papers) and Image and Signal Denoising Methods (4 papers). The work is most often cited by research in Computational Mathematics (238 citations), Computational Theory and Mathematics (126 citations) and Numerical Analysis (34 citations). Carmeliza Navasca has collaborated with scholars based in United States, Austria and China. Frequent co-authors include Na Li, Christino Tamon, Michael Brazell, Stefan Kindermann, Na Li, Lieven De Lathauwer, Kirsten Morris, Arthur J. Krener, Xiaofei Wang and Zhuo‐Heng He. Their work appears in journals such as Chemometrics and Intelligent Laboratory Systems, Nonlinear Analysis and Linear Algebra and its Applications.
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.