John Peebles
Impact in
- Statistics and Probability top 10%
- Markov Chains and Monte Carlo Methods
Papers in
-
- Complexity and Algorithms in Graphs 5
- Advanced Graph Theory Research 2
-
- Markov Chains and Monte Carlo Methods 5
- Co-authors
- Anup Rao (4 shared papers)Richard Peng (4 shared papers)Michael B. Cohen (3 shared papers)Aaron Sidford (3 shared papers)Jonathan A. Kelner (3 shared papers)Adrian Vladu (2 shared papers)Rasmus Kyng (2 shared papers)Anak Yodpinyanee (2 shared papers)
- Journals
- SIAM Journal on Computing (1 paper)Algorithmica (1 paper)arXiv (Cornell University) (2 papers)eScholarship (California Digital Library) (1 paper)DSpace@MIT (Massachusetts Institute of Technology) (2 papers)
- Partner nations
- United StatesIsrael
In The Last Decade
John Peebles
11 papers receiving 97 citations
Peers
Comparison fields: 5 of 40
- Computational Mathematics 4
- Statistics and Probability 26
- Computational Theory and Mathematics 48
- Statistical and Nonlinear Physics 26
- Artificial Intelligence 44
Countries citing papers authored by John Peebles
This map shows the geographic impact of John Peebles'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 John Peebles with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Peebles more than expected).
Fields of papers citing papers by John Peebles
This network shows the impact of papers produced by John Peebles. 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 John Peebles. The network helps show where John Peebles may publish in the future.
Co-authors
The 18 scholars most cited alongside John Peebles, 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 | 2017 | 23 | |
| 2 | Faster Algorithms for Computing the Stationary Distribution, Simulating Random Walks, and More | 2016 | 21 |
| 3 | 2017 | 17 | |
| 4 | 2017 | 11 | |
| 5 | 2018 | 9 | |
| 6 | Towards Understanding the Dynamics of Generative Adversarial Networks. | 2017 | 8 |
| 7 | HMC CS Technical Report CS-2011-1: Faster Dynamic Programming Algorithms for the Cophylogeny Reconstruction Problem | 2011 | 5 |
| 8 | 2019 | 3 | |
| 9 | 2020 | 3 | |
| 10 | 2016 | 2 | |
| 11 | Testing Identity of Multidimensional Histograms | 2018 | 1 |
About John Peebles
John Peebles is a scholar working on Computational Theory and Mathematics, Statistics and Probability, Artificial Intelligence, Geometry and Topology and Infectious Diseases, having authored 11 papers that have together received 103 indexed citations. Recurring topics across this work include Markov Chains and Monte Carlo Methods (5 papers), Complexity and Algorithms in Graphs (5 papers), Graph theory and applications (3 papers), Machine Learning and Algorithms (2 papers), Algorithms and Data Compression (2 papers), Advanced Graph Theory Research (2 papers), Optimization and Search Problems (1 paper) and Distributed systems and fault tolerance (1 paper). The work is most often cited by research in Computational Mathematics (4 citations), Statistics and Probability (26 citations), Computational Theory and Mathematics (48 citations), Statistical and Nonlinear Physics (26 citations) and Artificial Intelligence (44 citations). John Peebles has collaborated with scholars based in United States and Israel. Frequent co-authors include Anup Rao, Richard Peng, Michael B. Cohen, Aaron Sidford, Jonathan A. Kelner, Adrian Vladu, Rasmus Kyng, Anak Yodpinyanee, Sushant Sachdeva and Ronitt Rubinfeld. Their work appears in journals such as SIAM Journal on Computing, Algorithmica, arXiv (Cornell University), eScholarship (California Digital Library) and DSpace@MIT (Massachusetts Institute of Technology).
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.