Anna Ma
Impact in
- Computational Mathematics top 5%
- Tensor decomposition and applications
- Computational Mechanics top 5%
- Sparse and Compressive Sensing Techniques
Papers in
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- Sparse and Compressive Sensing Techniques 20
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- Stochastic Gradient Optimization Techniques 9
- Co-authors
- Deanna Needell (16 shared papers)Aaditya Ramdas (2 shared papers)Cynthia Rush (2 shared papers)Dror Baron (2 shared papers)Yves van Gennip (1 shared paper)Daniel Moyer (1 shared paper)Jing Qin (7 shared papers)You Zhou (1 shared paper)
- Journals
- SIAM Journal on Matrix Analysis and Applications (4 papers)Inverse Problems and Imaging (2 papers)Applied and Computational Harmonic Analysis (1 paper)BIT Numerical Mathematics (1 paper)Numerical Linear Algebra with Applications (1 paper)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Anna Ma
23 papers receiving 252 citations
Peers
Comparison fields: 5 of 45
- Computational Mathematics 36
- Computational Mechanics 188
- Numerical Analysis 48
- Computational Theory and Mathematics 96
- Artificial Intelligence 155
Countries citing papers authored by Anna Ma
This map shows the geographic impact of Anna Ma'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 Anna Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anna Ma more than expected).
Fields of papers citing papers by Anna Ma
This network shows the impact of papers produced by Anna Ma. 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 Anna Ma. The network helps show where Anna Ma may publish in the future.
Co-authors
The 22 scholars most cited alongside Anna Ma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 126 | |
| 2 | 2021 | 35 | |
| 3 | 2021 | 27 | |
| 4 | 2018 | 15 | |
| 5 | 2019 | 12 | |
| 6 | 2018 | 11 | |
| 7 | 2019 | 4 | |
| 8 | 2019 | 4 | |
| 9 | 2023 | 4 | |
| 10 | 2020 | 3 | |
| 11 | 2014 | 3 | |
| 12 | 2017 | 3 | |
| 13 | 2019 | 3 | |
| 14 | Adapted Stochastic Gradient Descent for Linear Systems with Missing Data | 2017 | 2 |
| 15 | 2018 | 2 | |
| 16 | 2020 | 2 | |
| 17 | 2020 | 2 | |
| 18 | 2021 | 2 | |
| 19 | 2019 | 2 | |
| 20 | 2024 | 1 |
About Anna Ma
Anna Ma is a scholar working on Computational Mechanics, Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing and Statistics and Probability, having authored 26 papers that have together received 266 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (20 papers), Stochastic Gradient Optimization Techniques (9 papers), Blind Source Separation Techniques (5 papers), Image and Signal Denoising Methods (5 papers), Microwave Imaging and Scattering Analysis (4 papers), Tensor decomposition and applications (4 papers), Markov Chains and Monte Carlo Methods (3 papers) and Statistical Methods and Inference (3 papers). The work is most often cited by research in Computational Mathematics (36 citations), Computational Mechanics (188 citations), Numerical Analysis (48 citations), Computational Theory and Mathematics (96 citations) and Artificial Intelligence (155 citations). Anna Ma has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Deanna Needell, Aaditya Ramdas, Cynthia Rush, Dror Baron, Yves van Gennip, Daniel Moyer, Jing Qin, You Zhou, Andrea L. Bertozzi and Chenxi Huang. Their work appears in journals such as SIAM Journal on Matrix Analysis and Applications, Inverse Problems and Imaging, Applied and Computational Harmonic Analysis, BIT Numerical Mathematics and Numerical Linear Algebra with 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.