Anna Ma

21 papers receiving 238 citations

Peers

Anna Ma
Comparison fields: 5 of 44
  • Computational Mathematics 32
  • Numerical Analysis 47
  • Computational Mechanics 179
  • Computational Theory and Mathematics 91
  • Artificial Intelligence 151
Replace Wen-Ting Wu with:
Wen-Ting Wu China
Petar Maymounkov United States
John P. May United States
Pavel Dvurechensky Russia
Khalide Jbilou France
Adi Shraibman Israel
Brian Bullins United States
Dennis Amelunxen United Kingdom
Masayuki Noro Japan
Peter J. C. Dickinson Netherlands
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Citations per field
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Citations per year

Countries citing papers authored by Anna Ma

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Anna Ma Line = papers co-authored together Anna Ma links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015124
2 202135
3 202126
4 201814
5 201912
6 20189
7 20194
8 20193
9 20203
10 20173
11 20233
12
Adapted Stochastic Gradient Descent for Linear Systems with Missing Data
20172
13 20142
14 20182
15 20202
16 20202
17 20212
18 20241
19 20231
20 20231

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 24 papers that have together received 252 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (18 papers), Stochastic Gradient Optimization Techniques (9 papers), Blind Source Separation Techniques (5 papers), Tensor decomposition and applications (4 papers), Markov Chains and Monte Carlo Methods (3 papers), Microwave Imaging and Scattering Analysis (3 papers), Statistical Methods and Inference (3 papers) and Image and Signal Denoising Methods (3 papers). The work is most often cited by research in Computational Mathematics (32 citations), Numerical Analysis (47 citations), Computational Mechanics (179 citations), Computational Theory and Mathematics (91 citations) and Artificial Intelligence (151 citations). Anna Ma has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Deanna Needell, Aaditya Ramdas, Dror Baron, Cynthia Rush, Yves van Gennip, Daniel Moyer, You Zhou, Andrea L. Bertozzi, Chenxi Huang and Saiprasad Ravishankar. Their work appears in journals such as SIAM Journal on Matrix Analysis and Applications, Inverse Problems and Imaging, Applied and Computational Harmonic Analysis, Numerical Linear Algebra with Applications and IEEE Transactions on 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.

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