Jeffrey C. Lagarias

183 papers receiving 9.8k citations

Hit Papers

Convergence Properties of the Nelder--Mead Simplex Method...1998202620072016199810002.0k3.0k4.0k5.0k

Peers

Jeffrey C. Lagarias
Comparison fields: 5 of 210
  • Computational Theory and Mathematics 2.2k
  • Mathematical Physics 1.6k
  • Artificial Intelligence 1.3k
  • Computer Vision and Pattern Recognition 1.2k
  • Electrical and Electronic Engineering 1.2k
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Countries citing papers authored by Jeffrey C. Lagarias

Since Specialization
Citations

This map shows the geographic impact of Jeffrey C. Lagarias'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 Jeffrey C. Lagarias with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeffrey C. Lagarias more than expected).

Fields of papers citing papers by Jeffrey C. Lagarias

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeffrey C. Lagarias. 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 Jeffrey C. Lagarias. The network helps show where Jeffrey C. Lagarias may publish in the future.

Co-authorship network of co-authors of Jeffrey C. Lagarias

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 3
3 2
4
p-adic path set fractals
1
5
The Takagi function and its properties (Functions in Number Theory and Their Probabilistic Aspects)
6
6 17
7
The 3x+1 problem: An annotated bibliography
33
8 7
9 3
10
Haar Bases for L 2 (R n ) and Algebraic Number Theory
18
11
Minimax and Hamiltonian Dynamics of Excitatory-Inhibitory Networks
13
12 60
13 13
14 4
15 4
16 64
17 64
18
On the Capacity of Disjointly Shared Networks.
3
19 209
20 7

About Jeffrey C. Lagarias

Jeffrey C. Lagarias is a scholar working on Algebra and Number Theory, Discrete Mathematics and Combinatorics and Theoretical Computer Science, having authored 192 papers that have together received 10.8k indexed citations. Recurring topics across this work include Mathematical Dynamics and Fractals (49 papers), Analytic Number Theory Research (32 papers) and Benford’s Law and Fraud Detection (19 papers). The work is most often cited by research in Mathematical Physics (1.6k citations), Algebra and Number Theory (683 citations) and Computational Theory and Mathematics (2.2k citations). Jeffrey C. Lagarias has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include James A. Reeds, Margaret H. Wright, Paul E. Wright, Yang Wang, Ingrid Daubechies, Andrew Odlyzko, Ingrid Daubechies, David Bayer, John H. Conway and Colin L. Mallows. Their work appears in journals such as Materials Science and Engineering A, Mathematics of Computation and Communications in Mathematical Physics.

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.

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