E. Gardner

33 papers receiving 3.0k citations

Hit Papers

The space of interactions in neural network models 1988 · 668 citations
6681988202620002013200400600

Peers

E. Gardner
Comparison fields: 5 of 102
  • Condensed Matter Physics 878
  • Statistical and Nonlinear Physics 870
  • Artificial Intelligence 1.8k
  • Cognitive Neuroscience 985
  • Acoustics and Ultrasonics 39
Replace Wolfgang Kinzel with:
Wolfgang Kinzel Germany
Hanoch Gutfreund Israel
Hidetoshi Nishimori Japan
Florent Krząkała France
H.-J. Sommers Germany
Federico Ricci‐Tersenghi Italy
Michael M. Wolf Germany
Francesco Petruccione South Africa
Andreas Winter Germany
Alexander K. Hartmann Germany
E. Gardner relative to Wolfgang Kinzel Germany Wolfgang Kinzel's profile →
Citations per field
00.5×3.1×
Wolfgang Kinzel · 1×
Citations per year

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-authors

The 25 scholars most cited alongside E. Gardner, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with E. Gardner Line = papers co-authored together E. Gardner links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1
The space of interactions in neural network models
Hit paper breakdown →
1988668
2 1987399
3 1988354
4 1985233
5 1984224
6 1987216
7 1989122
8 1987102
9 198693
10 198675
11 198773
12 198962
13 198751
14 198849
15 198641
16 201038
17 198437
18 198935
19 198633
20 198432

About E. Gardner

E. Gardner is a scholar working on Condensed Matter Physics, Statistical and Nonlinear Physics, Mathematical Physics, Artificial Intelligence and Cognitive Neuroscience, having authored 33 papers that have together received 3.1k indexed citations. Recurring topics across this work include Theoretical and Computational Physics (18 papers), Neural Networks and Applications (15 papers), Neural dynamics and brain function (8 papers), Complex Network Analysis Techniques (5 papers), Stochastic processes and statistical mechanics (5 papers), Neural Networks Stability and Synchronization (4 papers), Complex Systems and Time Series Analysis (4 papers) and Model Reduction and Neural Networks (4 papers). The work is most often cited by research in Condensed Matter Physics (878 citations), Statistical and Nonlinear Physics (870 citations), Artificial Intelligence (1.8k citations), Cognitive Neuroscience (985 citations) and Acoustics and Ultrasonics (39 citations). E. Gardner has collaborated with scholars based in United Kingdom, France and Finland. Frequent 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. Their work appears in journals such as Monthly Notices of the Royal Astronomical Society, Europhysics Letters (EPL), Nuclear Physics B, International Journal of Astrobiology and Journal of Statistical 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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