William G. Faris
- Mathematical Physics top 2%
- Applied Mathematics top 2%
- Computational Theory and Mathematics top 2%
- Statistical and Nonlinear Physics top 5%
- Atomic and Molecular Physics, and Optics
- Co-authors
- G. Jona‐LasinioRichard LavineBarry SimonRobert BurtonRobert S. MaierR. A. MinlosDavid M. BressoudJean Lacroix
- Topics
- Spectral Theory in Mathematical Physics (12 papers)Numerical methods in inverse problems (6 papers)Stochastic processes and statistical mechanics (5 papers)
- Journals
- Journal of the American Statistical AssociationCommunications in Mathematical PhysicsNeural Networks
- Partner nations
- United StatesSwitzerlandFrance
In The Last Decade
William G. Faris
39 papers receiving 681 citations
Peers
Comparison fields: 5 of 59
- Mathematical Physics 482
- Applied Mathematics 228
- Computational Theory and Mathematics 205
- Statistical and Nonlinear Physics 202
- Atomic and Molecular Physics, and Optics 158
Countries citing papers authored by William G. Faris
This map shows the geographic impact of William G. Faris'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 William G. Faris with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William G. Faris more than expected).
Fields of papers citing papers by William G. Faris
This network shows the impact of papers produced by William G. Faris. 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 William G. Faris. The network helps show where William G. Faris may publish in the future.
Co-authorship network of co-authors of William G. Faris
This figure shows the co-authorship network connecting the top 25 collaborators of William G. Faris. A scholar is included among the top collaborators of William G. Faris based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with William G. Faris. William G. Faris is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 8 | |
| 3 | 27 | |
| 4 | 4 | |
| 5 | 9 | |
| 6 | 2 | |
| 7 | Confirmation in Experimental Mathematics: A Case Study. | 1 |
| 8 | 8 | |
| 9 | 1 | |
| 10 | 5 | |
| 11 | The Value of a Random Game: The Advantage of Rationality. | 3 |
| 12 | 5 | |
| 13 | 17 | |
| 14 | 1 | |
| 15 | 5 | |
| 16 | 13 | |
| 17 | 109 | |
| 18 | 17 | |
| 19 | 53 | |
| 20 | 2 |
About William G. Faris
William G. Faris is a scholar working on Mathematical Physics, Statistical and Nonlinear Physics and Applied Mathematics, having authored 40 papers that have together received 792 indexed citations. Recurring topics across this work include Spectral Theory in Mathematical Physics (12 papers), Numerical methods in inverse problems (6 papers) and Stochastic processes and statistical mechanics (5 papers). The work is most often cited by research in Mathematical Physics (482 citations), Applied Mathematics (228 citations) and Statistical and Nonlinear Physics (202 citations). William G. Faris has collaborated with scholars based in United States, Switzerland and France. Frequent co-authors include G. Jona‐Lasinio, Richard Lavine, Barry Simon, Robert Burton, Robert S. Maier, R. A. Minlos, David M. Bressoud, Jean Lacroix and Philippe Bougerol. Their work appears in journals such as Journal of the American Statistical Association, Communications in Mathematical Physics and Neural Networks.
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.