Murray Browne
Impact in
- Computational Mathematics top 2%
- Tensor decomposition and applications
- Signal Processing top 5%
- Blind Source Separation Techniques
Papers in ⓘ
-
- Technology Assessment and Management 1
- Co-authors
- Michael W. Berry (7 shared papers)Amy N. Langville (1 shared paper)V. Paúl Pauca (1 shared paper)Robert J. Plemmons (1 shared paper)John C. Martin (1 shared paper)
- Journals
- Computational Statistics & Data Analysis (1 paper)Applied Numerical Mathematics (1 paper)Computational and Mathematical Organization Theory (1 paper)Society for Industrial and Applied Mathematics eBooks (2 papers)WORLD SCIENTIFIC eBooks (1 paper)
- Partner nations
- United States
In The Last Decade
Murray Browne
7 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 153
- Computational Mathematics 60
- Signal Processing 252
- Computer Vision and Pattern Recognition 324
- Media Technology 95
- Artificial Intelligence 326
Countries citing papers authored by Murray Browne
This map shows the geographic impact of Murray Browne'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 Murray Browne with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Murray Browne more than expected).
Fields of papers citing papers by Murray Browne
This network shows the impact of papers produced by Murray Browne. 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 Murray Browne. The network helps show where Murray Browne may publish in the future.
Co-authors
The 5 scholars most cited alongside Murray Browne, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Algorithms and applications for approximate nonnegative matrix factorization Hit paper breakdown → | 2006 | 1022 |
| 2 | 2005 | 88 | |
| 3 | 2005 | 65 | |
| 4 | 2006 | 40 | |
| 5 | Understanding Search Engines: Mathematical Modeling and Text Retrieval (Software, Environments, Tools), Second Edition | 2005 | 13 |
| 6 | 2008 | 13 | |
| 7 | 2007 | 5 |
About Murray Browne
Murray Browne is a scholar working on Safety, Risk, Reliability and Quality, Information Systems, Statistical and Nonlinear Physics, Management Science and Operations Research and Computational Theory and Mathematics, having authored 7 papers that have together received 1.2k indexed citations. Recurring topics across this work include Technology Assessment and Management (1 paper), Complex Network Analysis Techniques (1 paper), Advanced Text Analysis Techniques (1 paper), Face and Expression Recognition (1 paper), Natural Language Processing Techniques (1 paper), Topic Modeling (1 paper), Semantic Web and Ontologies (1 paper) and Data Quality and Management (1 paper). The work is most often cited by research in Computational Mathematics (60 citations), Signal Processing (252 citations), Computer Vision and Pattern Recognition (324 citations), Media Technology (95 citations) and Artificial Intelligence (326 citations). Murray Browne has collaborated with scholars based in United States. Frequent co-authors include Michael W. Berry, Amy N. Langville, V. Paúl Pauca, Robert J. Plemmons and John C. Martin. Their work appears in journals such as Computational Statistics & Data Analysis, Applied Numerical Mathematics, Computational and Mathematical Organization Theory, Society for Industrial and Applied Mathematics eBooks and WORLD SCIENTIFIC eBooks.
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.