E. Gardner

4.7k total citations · 1 hit paper
33 papers, 3.1k citations indexed

About

E. Gardner is a scholar working on Condensed Matter Physics, Artificial Intelligence and Statistical and Nonlinear Physics. According to data from OpenAlex, E. Gardner has authored 33 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Condensed Matter Physics, 15 papers in Artificial Intelligence and 10 papers in Statistical and Nonlinear Physics. Recurrent topics in E. Gardner's work include Theoretical and Computational Physics (18 papers), Neural Networks and Applications (15 papers) and Neural dynamics and brain function (8 papers). E. Gardner is often cited by papers focused on Theoretical and Computational Physics (18 papers), Neural Networks and Applications (15 papers) and Neural dynamics and brain function (8 papers). E. Gardner collaborates with scholars based in United Kingdom, France and Finland. E. Gardner's co-authors include Bernard Derrida, Bernard Derrida, Alfred Zippelius, Peter Mottishaw, D. J. Wallace, Andrew Canning, Chris Flynn, Ann Bruce, C. Itzykson and Hanoch Gutfreund and has published in prestigious journals such as Nuclear Physics B, Monthly Notices of the Royal Astronomical Society and Europhysics Letters (EPL).

In The Last Decade

E. Gardner

33 papers receiving 3.0k citations

Hit Papers

The space of interactions in neural network models 1988 2026 2000 2013 1988 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
E. Gardner United Kingdom 24 1.8k 985 878 870 452 33 3.1k
Hanoch Gutfreund Israel 31 2.0k 1.1× 1.4k 1.4× 1.1k 1.3× 724 0.8× 825 1.8× 89 4.4k
Wolfgang Kinzel Germany 39 1.1k 0.6× 417 0.4× 1.9k 2.2× 1.4k 1.7× 451 1.0× 171 4.4k
H.-J. Sommers Germany 24 373 0.2× 453 0.5× 981 1.1× 1.1k 1.3× 158 0.3× 33 2.4k
Florent Krząkała France 32 1.4k 0.8× 144 0.1× 993 1.1× 1.4k 1.6× 348 0.8× 114 4.0k
R. M. Westervelt United States 36 934 0.5× 404 0.4× 700 0.8× 1.6k 1.9× 1.1k 2.5× 99 4.5k
Sudeshna Sinha India 37 692 0.4× 639 0.6× 185 0.2× 2.4k 2.8× 498 1.1× 162 3.6k
Hidetoshi Nishimori Japan 33 2.9k 1.6× 125 0.1× 2.3k 2.6× 1.1k 1.2× 471 1.0× 153 6.0k
Wolfgang Schwarz Germany 30 320 0.2× 653 0.7× 81 0.1× 798 0.9× 417 0.9× 129 3.1k
Juan M. R. Parrondo Spain 34 721 0.4× 702 0.7× 420 0.5× 4.0k 4.6× 114 0.3× 101 5.1k
D J Amit Israel 22 345 0.2× 380 0.4× 674 0.8× 245 0.3× 183 0.4× 35 1.3k

Countries citing papers authored by E. Gardner

Since Specialization
Citations

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

Fields of papers citing papers by E. Gardner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by E. Gardner. 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 E. Gardner. The network helps show where E. Gardner may publish in the future.

Co-authorship network of co-authors of E. Gardner

This figure shows the co-authorship network connecting the top 25 collaborators of E. Gardner. A scholar is included among the top collaborators of E. Gardner 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 E. Gardner. E. Gardner 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.
Gardner, E., H. J. Lehto, Kirsi Lehto, et al.. (2020). The detection of solid phosphorus and fluorine in the dust from the coma of comet 67P/Churyumov–Gerasimenko. Monthly Notices of the Royal Astronomical Society. 499(2). 1870–1873. 6 indexed citations
2.
Gardner, E., Victor P. Debattista, A. C. Robin, S. Vásquez, & M. Zoccali. (2014). N-body simulation insights into the X-shaped bulge of the Milky Way: kinematics and distance to the Galactic Centre. Monthly Notices of the Royal Astronomical Society. 438(4). 3275–3290. 31 indexed citations
3.
Lehto, Kirsi, H. J. Lehto, E. Gardner, et al.. (2012). Time Trek: a 13.7 km long nature trail leading through the history of the Universe and the Earth. International Journal of Astrobiology. 12(1). 1–7. 2 indexed citations
4.
Gardner, E. & Chris Flynn. (2010). Probing the Galaxy's bars via the Hercules stream. Monthly Notices of the Royal Astronomical Society. 38 indexed citations
5.
Gardner, E., P. Nurmi, Chris Flynn, & Seppo Mikkola. (2010). The effect of the solar motion on the flux of long-period comets. Monthly Notices of the Royal Astronomical Society. 411(2). 947–954. 19 indexed citations
6.
Gardner, E. & Bernard Derrida. (1989). Three unfinished works on the optimal storage capacity of networks. Journal of Physics A Mathematical and General. 22(12). 1983–1994. 122 indexed citations
7.
Gardner, E., et al.. (1989). The phase space of interactions in neural networks with definite symmetry. Journal of Physics A Mathematical and General. 22(12). 1995–2008. 30 indexed citations
8.
Gardner, E., Stephan Mertens, & Alfred Zippelius. (1989). Retrieval properties of a neural network with an asymmetric learning rule. Journal of Physics A Mathematical and General. 22(12). 2009–2018. 8 indexed citations
9.
Gardner, E. & Bernard Derrida. (1989). The probability distribution of the partition function of the random energy model. Journal of Physics A Mathematical and General. 22(12). 1975–1981. 29 indexed citations
10.
Gardner, E., et al.. (1989). Training with noise and the storage of correlated patterns in a neural network model. Journal of Physics A Mathematical and General. 22(12). 2019–2030. 35 indexed citations
11.
Gardner, E.. (1987). Maximum Storage Capacity in Neural Networks. Europhysics Letters (EPL). 4(4). 481–485. 216 indexed citations
12.
Gardner, E., Bernard Derrida, & Peter Mottishaw. (1987). Zero temperature parallel dynamics for infinite range spin glasses and neural networks. Journal de physique. 48(5). 741–755. 102 indexed citations
13.
Derrida, Bernard, E. Gardner, & Alfred Zippelius. (1987). An Exactly Solvable Asymmetric Neural Network Model. Europhysics Letters (EPL). 4(2). 167–173. 399 indexed citations
14.
Derrida, Bernard & E. Gardner. (1986). Metastable states of a spin glass chain at 0 temperature. Journal de physique. 47(6). 959–965. 41 indexed citations
15.
Gardner, E.. (1986). Structure of metastable states in the Hopfield model. Journal of Physics A Mathematical and General. 19(16). L1047–L1052. 93 indexed citations
16.
Gardner, E. & Bernard Derrida. (1985). Zero temperature magnetization of a one-dimensional spin glass. Journal of Statistical Physics. 39(3-4). 367–377. 17 indexed citations
17.
Gardner, E.. (1985). Spin glasses with p-spin interactions. Nuclear Physics B. 257. 747–765. 233 indexed citations
18.
Gardner, E.. (1984). A spin glass model on a hierarchical lattice. Journal de physique. 45(11). 1755–1763. 32 indexed citations
19.
Gardner, E.. (1983). The Schwinger-Dyson equation for the gluon propagator in 2+1 and in 3+1 dimensions. Journal of Physics G Nuclear Physics. 9(2). 139–160. 15 indexed citations
20.
Gardner, E.. (1981). The massless Schwinger model. Journal of Physics G Nuclear Physics. 7(12). L269–L273. 6 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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