Joseph F. Murray
- Structural Biology top 5%
- Signal Processing top 2%
- Blind Source Separation Techniques 6
-
- Image and Signal Denoising Methods 4
- Computational Mechanics top 5%
- Sparse and Compressive Sensing Techniques 6
-
- Motor Control and Adaptation 2
-
- Sports Performance and Training 2
-
- Neural Networks and Applications 2
-
- Image Processing Techniques and Applications 2
-
- Statistical and numerical algorithms 1
- Co-authors
- Kenneth Kreutz-DelgadoGordon F. HughesBhaskar D. RaoKjersti EnganTerrence J. SejnowskiTe-Won LeeCharles ElkanReinhard E. Flick
- Journals
- Surface Science (1 paper)Neural Computation (2 papers)Journal of Machine Learning Research (1 paper)
- Partner nations
- United StatesGermanyFrance
In The Last Decade
Joseph F. Murray
20 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 123
- Structural Biology 36
- Signal Processing 270
- Computer Vision and Pattern Recognition 426
- Computational Mechanics 357
- Computer Networks and Communications 355
Countries citing papers authored by Joseph F. Murray
This map shows the geographic impact of Joseph F. Murray'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 Joseph F. Murray with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joseph F. Murray more than expected).
Fields of papers citing papers by Joseph F. Murray
This network shows the impact of papers produced by Joseph F. Murray. 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 Joseph F. Murray. The network helps show where Joseph F. Murray may publish in the future.
Co-authorship network
The 17 scholars most cited alongside Joseph F. Murray, 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 | 2022 | 3 | |
| 2 | 2019 | 0 | |
| 3 | 2010 | 1 | |
| 4 | 2007 | 146 | |
| 5 | 2007 | 22 | |
| 6 | 2006 | 36 | |
| 7 | 2006 | 24 | |
| 8 | 2005 | 198 | |
| 9 | Visual recognition, inference and coding using learned sparse overcomplete representations | 2005 | 15 |
| 10 | 2005 | 29 | |
| 11 | 2005 | 15 | |
| 12 | Dictionary Learning Algorithms for Sparse Representationbreakdown → | 2003 | 550 |
| 13 | Hard drive failure prediction using non-parametric statistical methods | 2003 | 68 |
| 14 | 2003 | 106 | |
| 15 | 2002 | 157 | |
| 16 | 2001 | 54 | |
| 17 | 1982 | 6 | |
| 18 | 1982 | 0 | |
| 19 | 1981 | 6 | |
| 20 | 1980 | 6 |
About Joseph F. Murray
Joseph F. Murray is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Hardware and Architecture, having authored 22 papers that have together received 1.5k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (6 papers), Blind Source Separation Techniques (6 papers), Image and Signal Denoising Methods (4 papers), Motor Control and Adaptation (2 papers), Sports Performance and Training (2 papers), Neural Networks and Applications (2 papers), Image Processing Techniques and Applications (2 papers) and Statistical and numerical algorithms (1 paper). The work is most often cited by research in Structural Biology (36 citations), Signal Processing (270 citations) and Computer Vision and Pattern Recognition (426 citations). Joseph F. Murray has collaborated with scholars based in United States, Germany and France. Frequent co-authors include Kenneth Kreutz-Delgado, Gordon F. Hughes, Bhaskar D. Rao, Kjersti Engan, Terrence J. Sejnowski, Te-Won Lee, Charles Elkan, Reinhard E. Flick, Kevin L. Briggman and Srinivas C. Turaga. Their work appears in journals such as Surface Science, Neural Computation and Journal of Machine Learning Research.
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.