Alexander Gray
Impact in
- Instrumentation top 5%
- Astronomy and Astrophysical Research
- Astronomy and Astrophysics top 5%
- Galaxies: Formation, Evolution, Phenomena
- Gamma-ray bursts and supernovae
- Cosmology and Gravitation Theories
Papers in
-
- Algorithms and Data Compression 19
- Machine Learning and Data Classification 15
- Machine Learning and Algorithms 9
- Neural Networks and Applications 9
- Co-authors
- Andrew Moore (9 shared papers)Parikshit Ram (13 shared papers)Ke Yang (1 shared paper)Ting Liu (1 shared paper)Gordon T. Richards (6 shared papers)R. C. Nichol (6 shared papers)Adam D. Myers (4 shared papers)Donald P. Schneider (4 shared papers)
- Journals
- Journal of Machine Learning Research (2 papers)Computational Statistics & Data Analysis (2 papers)The Astrophysical Journal Supplement Series (2 papers)ACM SIGPLAN Notices (1 paper)Frontiers in Oncology (1 paper)
- Partner nations
- United StatesUnited KingdomIreland
In The Last Decade
Alexander Gray
103 papers receiving 3.0k citations
Peers
Comparison fields: 5 of 160
- Instrumentation 222
- Astronomy and Astrophysics 660
- Artificial Intelligence 1.3k
- Computational Mathematics 22
- Signal Processing 407
Countries citing papers authored by Alexander Gray
This map shows the geographic impact of Alexander Gray'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 Alexander Gray with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander Gray more than expected).
Fields of papers citing papers by Alexander Gray
This network shows the impact of papers produced by Alexander Gray. 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 Alexander Gray. The network helps show where Alexander Gray may publish in the future.
Co-authors
The 25 scholars most cited alongside Alexander Gray, 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 106 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | An Investigation of Practical Approximate Nearest Neighbor Algorithms | 2004 | 272 |
| 2 | 2019 | 210 | |
| 3 | 2008 | 206 | |
| 4 | `N-Body' Problems in Statistical Learning | 2000 | 184 |
| 5 | 2004 | 134 | |
| 6 | 2006 | 123 | |
| 7 | Stochastic Alternating Direction Method of Multipliers | 2013 | 119 |
| 8 | 2006 | 117 | |
| 9 | 2003 | 117 | |
| 10 | Detecting spammers with SNARE: spatio-temporal network-level automatic reputation engine | 2009 | 108 |
| 11 | 2009 | 107 | |
| 12 | 2012 | 96 | |
| 13 | 2006 | 71 | |
| 14 | 2010 | 69 | |
| 15 | 2019 | 67 | |
| 16 | 2010 | 64 | |
| 17 | 1995 | 60 | |
| 18 | 2006 | 50 | |
| 19 | An integrated system for multi-rover scientific exploration | 1999 | 49 |
| 20 | 2009 | 44 |
About Alexander Gray
Alexander Gray is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Statistics and Probability and Computational Mechanics, having authored 106 papers that have together received 3.2k indexed citations. Recurring topics across this work include Algorithms and Data Compression (19 papers), Machine Learning and Data Classification (15 papers), Data Management and Algorithms (14 papers), Machine Learning and Algorithms (9 papers), Neural Networks and Applications (9 papers), Statistical Methods and Inference (8 papers), Sparse and Compressive Sensing Techniques (7 papers) and Galaxies: Formation, Evolution, Phenomena (7 papers). The work is most often cited by research in Instrumentation (222 citations), Astronomy and Astrophysics (660 citations), Artificial Intelligence (1.3k citations), Computational Mathematics (22 citations) and Signal Processing (407 citations). Alexander Gray has collaborated with scholars based in United States, United Kingdom and Ireland. Frequent co-authors include Andrew Moore, Parikshit Ram, Ke Yang, Ting Liu, Gordon T. Richards, R. C. Nichol, Adam D. Myers, Donald P. Schneider, Dongryeol Lee and Hua Ouyang. Their work appears in journals such as Journal of Machine Learning Research, Computational Statistics & Data Analysis, The Astrophysical Journal Supplement Series, ACM SIGPLAN Notices and Frontiers in Oncology.
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.