John Peebles

780 total citations
11 papers, 103 citations indexed

About

John Peebles is a scholar working on Computational Theory and Mathematics, Statistics and Probability and Artificial Intelligence. According to data from OpenAlex, John Peebles has authored 11 papers receiving a total of 103 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computational Theory and Mathematics, 5 papers in Statistics and Probability and 4 papers in Artificial Intelligence. Recurrent topics in John Peebles's work include Complexity and Algorithms in Graphs (5 papers), Markov Chains and Monte Carlo Methods (5 papers) and Graph theory and applications (3 papers). John Peebles is often cited by papers focused on Complexity and Algorithms in Graphs (5 papers), Markov Chains and Monte Carlo Methods (5 papers) and Graph theory and applications (3 papers). John Peebles collaborates with scholars based in United States and Israel. John Peebles's co-authors include Anup Rao, Richard Peng, Jonathan A. Kelner, Michael B. Cohen, Aaron Sidford, Adrian Vladu, Rasmus Kyng, Anak Yodpinyanee, Sushant Sachdeva and Aleksander Mądry and has published in prestigious journals such as SIAM Journal on Computing, Algorithmica and arXiv (Cornell University).

In The Last Decade

John Peebles

11 papers receiving 97 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
John Peebles United States	6	48	44	26	26	16	11	103
Nicolas Hanusse France	5	47 1.0×	24 0.5×	5 0.2×	19 0.7×	46 2.9×	16	122
Olivier Bodini France	6	55 1.1×	49 1.1×	12 0.5×	6 0.2×	3 0.2×	32	109
Ziv Goldfeld United States	7	16 0.3×	56 1.3×	15 0.6×	20 0.8×	44 2.8×	36	162
Roman Matuszewski Poland	3	74 1.5×	105 2.4×	4 0.2×	11 0.4×	5 0.3×	5	146
Jürgen Forster Germany	4	77 1.6×	94 2.1×	9 0.3×	4 0.2×	15 0.9×	7	132
Xavier Pérez‐Giménez Canada	8	63 1.3×	11 0.3×	7 0.3×	24 0.9×	76 4.8×	24	142
Jason M. Altschuler United States	5	22 0.5×	35 0.8×	25 1.0×	5 0.2×	3 0.2×	16	93
Dominique Poulalhon France	9	48 1.0×	30 0.7×	23 0.9×	7 0.3×	7 0.4×	16	176
Jacques Mandler France	2	29 0.6×	21 0.5×	13 0.5×	8 0.3×	44 2.8×	3	77
Meyer Z. Pesenson United States	6	27 0.6×	36 0.8×	2 0.1×	34 1.3×	6 0.4×	8	80

Countries citing papers authored by John Peebles

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of John Peebles

This figure shows the co-authorship network connecting the top 25 collaborators of John Peebles. A scholar is included among the top collaborators of John Peebles 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 John Peebles. John Peebles is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

11 of 11 papers shown

1.

Peebles, John, et al.. (2020). Determinant-Preserving Sparsification of SDDM Matrices. SIAM Journal on Computing. 49(4). FOCS17–350. 3 indexed citations

2.

Diakonikolas, Ilias, et al.. (2019). . 25(1). 1–21. 3 indexed citations

3.

Diakonikolas, Ilias, Daniel M. Kane, & John Peebles. (2018). Testing Identity of Multidimensional Histograms. eScholarship (California Digital Library). 1107–1131. 1 indexed citations

4.

Cohen, Michael B., Jonathan A. Kelner, Rasmus Kyng, et al.. (2018). Solving Directed Laplacian Systems in Nearly-Linear Time through Sparse LU Factorizations. 898–909. 9 indexed citations

5.

Li, Jerry, Aleksander Mądry, John Peebles, & Ludwig Schmidt. (2017). Towards Understanding the Dynamics of Generative Adversarial Networks.. arXiv (Cornell University). 8 indexed citations

6.

Cohen, Michael B., Jonathan A. Kelner, John Peebles, et al.. (2017). Almost-linear-time algorithms for Markov chains and new spectral primitives for directed graphs. DSpace@MIT (Massachusetts Institute of Technology). 410–419. 23 indexed citations

7.

Peebles, John, et al.. (2017). Sublinear-Time Algorithms for Counting Star Subgraphs via Edge Sampling. Algorithmica. 80(2). 668–697. 11 indexed citations

8.

Kyng, Rasmus, et al.. (2017). Sampling random spanning trees faster than matrix multiplication. 730–742. 17 indexed citations

9.

Peng, Richard, Aaron Sidford, Michael B. Cohen, et al.. (2016). Faster Algorithms for Computing the Stationary Distribution, Simulating Random Walks, and More. DSpace@MIT (Massachusetts Institute of Technology). 21 indexed citations

10.

Diakonikolas, Ilias, et al.. (2016). Collision-based Testers are Optimal for Uniformity and Closeness. arXiv (Cornell University). 2019. 2 indexed citations

11.

Yodpinyanee, Anak, et al.. (2011). HMC CS Technical Report CS-2011-1: Faster Dynamic Programming Algorithms for the Cophylogeny Reconstruction Problem. 5 indexed citations

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.

Explore authors with similar magnitude of impact