Ryan G. James

827 total citations
21 papers, 464 citations indexed

About

Ryan G. James is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Ryan G. James has authored 21 papers receiving a total of 464 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Statistical and Nonlinear Physics, 7 papers in Artificial Intelligence and 5 papers in Computational Theory and Mathematics. Recurrent topics in Ryan G. James's work include Neural Networks and Applications (6 papers), Neural dynamics and brain function (4 papers) and Complex Network Analysis Techniques (4 papers). Ryan G. James is often cited by papers focused on Neural Networks and Applications (6 papers), Neural dynamics and brain function (4 papers) and Complex Network Analysis Techniques (4 papers). Ryan G. James collaborates with scholars based in United States, United Kingdom and France. Ryan G. James's co-authors include James P. Crutchfield, Christopher J. Ellison, Elizabeth Bradley, Joshua Garland, W. J. Stronge, Bahram Ravani, John R. Mahoney, Virgil Griffith, Edwin K. P. Chong and Glenn R. Krakower and has published in prestigious journals such as Physical Review Letters, Journal of Clinical Investigation and Journal of Applied Physics.

In The Last Decade

Ryan G. James

19 papers receiving 455 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ryan G. James United States 13 162 137 106 74 53 21 464
Leon Glass Canada 6 130 0.8× 244 1.8× 85 0.8× 67 0.9× 79 1.5× 8 681
Kateřina Hlaváčková‐Schindler Austria 6 134 0.8× 245 1.8× 140 1.3× 153 2.1× 61 1.2× 21 672
Zoran Levnajić Slovenia 13 282 1.7× 159 1.2× 75 0.7× 54 0.7× 119 2.2× 31 636
Artemy Kolchinsky United States 13 171 1.1× 202 1.5× 113 1.1× 15 0.2× 129 2.4× 36 687
Dimitri Volchenkov Germany 11 163 1.0× 44 0.3× 38 0.4× 56 0.8× 45 0.8× 63 498
Oliver Obst Australia 11 98 0.6× 172 1.3× 236 2.2× 22 0.3× 40 0.8× 36 474
Danuta Makowiec Poland 13 155 1.0× 86 0.6× 25 0.2× 219 3.0× 45 0.8× 72 551
Renate Wackerbauer United States 12 270 1.7× 123 0.9× 34 0.3× 79 1.1× 54 1.0× 24 460
Dean Korošak Slovenia 15 209 1.3× 61 0.4× 30 0.3× 45 0.6× 107 2.0× 40 1.0k
Tijana T. Ivancevic Australia 13 147 0.9× 79 0.6× 67 0.6× 56 0.8× 21 0.4× 43 513

Countries citing papers authored by Ryan G. James

Since Specialization
Citations

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

Fields of papers citing papers by Ryan G. James

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ryan G. James. 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 Ryan G. James. The network helps show where Ryan G. James may publish in the future.

Co-authorship network of co-authors of Ryan G. James

This figure shows the co-authorship network connecting the top 25 collaborators of Ryan G. James. A scholar is included among the top collaborators of Ryan G. James 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 Ryan G. James. Ryan G. James 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
1.
James, Ryan G., et al.. (2020). Correlated structural evolution within multiplex networks. Journal of Complex Networks. 8(2). 2 indexed citations
2.
James, Ryan G., Christopher J. Ellison, & James P. Crutchfield. (2018). dit: a Python package for discrete information theory. The Journal of Open Source Software. 3(25). 738–738. 35 indexed citations
3.
James, Ryan G., et al.. (2018). Unique Information and Secret Key Agreement. Entropy. 21(1). 12–12. 18 indexed citations
4.
Hilbert, Martin, et al.. (2018). The Complementary Importance of Static Structure and Temporal Dynamics in Teamwork Communication. Human Communication Research. 44(4). 427–448. 3 indexed citations
5.
James, Ryan G., et al.. (2017). Anatomy of a Spin: The Information-Theoretic Structure of Classical Spin Systems. Entropy. 19(5). 214–214. 10 indexed citations
6.
James, Ryan G., John R. Mahoney, & James P. Crutchfield. (2017). Information trimming: Sufficient statistics, mutual information, and predictability from effective channel states. Physical review. E. 95(6). 60102–60102.
7.
James, Ryan G., et al.. (2016). Elusive present: Hidden past and future dependency and why we build models. Physical review. E. 93(2). 22143–22143. 8 indexed citations
8.
James, Ryan G., et al.. (2016). Information Flows? A Critique of Transfer Entropies. Physical Review Letters. 116(23). 238701–238701. 93 indexed citations
9.
Garland, Joshua, Ryan G. James, & Elizabeth Bradley. (2016). Leveraging information storage to select forecast-optimal parameters for delay-coordinate reconstructions. Physical review. E. 93(2). 22221–22221. 23 indexed citations
10.
Garland, Joshua, Ryan G. James, & Elizabeth Bradley. (2014). Quantifying Time-Series Predictability through Structural Complexity.. arXiv (Cornell University). 1 indexed citations
11.
Garland, Joshua, Ryan G. James, & Elizabeth Bradley. (2014). Model-free quantification of time-series predictability. Physical Review E. 90(5). 52910–52910. 54 indexed citations
12.
James, Ryan G., John R. Mahoney, Christopher J. Ellison, & James P. Crutchfield. (2014). Many roads to synchrony: Natural time scales and their algorithms. Physical Review E. 89(4). 42135–42135. 17 indexed citations
13.
Griffith, Virgil, Edwin K. P. Chong, Ryan G. James, Christopher J. Ellison, & James P. Crutchfield. (2014). Intersection Information Based on Common Randomness. Entropy. 16(4). 1985–2000. 49 indexed citations
14.
James, Ryan G., et al.. (2014). Chaos forgets and remembers: Measuring information creation, destruction, and storage. Physics Letters A. 378(30-31). 2124–2127. 16 indexed citations
15.
Ellison, Christopher J., John R. Mahoney, Ryan G. James, James P. Crutchfield, & Juergen Reichardt. (2011). Information symmetries in irreversible processes. Chaos An Interdisciplinary Journal of Nonlinear Science. 21(3). 37107–37107. 15 indexed citations
16.
Crutchfield, James P., Christopher J. Ellison, Ryan G. James, & John R. Mahoney. (2010). Synchronization and Control in Intrinsic and Designed Computation: An\n Information-Theoretic Analysis of Competing Models of Stochastic Computation. eScholarship (California Digital Library). 16 indexed citations
17.
Kwon, C., James L. Young, Ryan G. James, et al.. (2007). Local Current Transport and Current Sharing Between Filaments in Striated Coated Conductors With Artificial Defects. IEEE Transactions on Applied Superconductivity. 17(2). 3191–3194. 4 indexed citations
18.
Kwon, C., et al.. (2007). Effects of local artificial defects in multifilamentary coated conductors with patterned links. Journal of Applied Physics. 101(8). 1 indexed citations
19.
Stronge, W. J., Ryan G. James, & Bahram Ravani. (2001). Oblique impact with friction and tangential compliance. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 359(1789). 2447–2465. 40 indexed citations
20.
Krakower, Glenn R., et al.. (1988). Regional adipocyte precursors in the female rat. Influence of ovarian factors.. Journal of Clinical Investigation. 81(3). 641–648. 21 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.

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