Péter Földiák

3.3k total citations
28 papers, 2.1k citations indexed

About

Péter Földiák is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Cellular and Molecular Neuroscience. According to data from OpenAlex, Péter Földiák has authored 28 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Cognitive Neuroscience, 17 papers in Artificial Intelligence and 5 papers in Cellular and Molecular Neuroscience. Recurrent topics in Péter Földiák's work include Neural dynamics and brain function (18 papers), Neural Networks and Applications (13 papers) and Visual perception and processing mechanisms (9 papers). Péter Földiák is often cited by papers focused on Neural dynamics and brain function (18 papers), Neural Networks and Applications (13 papers) and Visual perception and processing mechanisms (9 papers). Péter Földiák collaborates with scholars based in United Kingdom, Germany and Italy. Péter Földiák's co-authors include David I. Perrett, Horace Barlow, Christian Keysers, D. Xiao, Malcolm P. Young, Mike W. Oram, Frank Sengpiel, Dominik Endres, Dengke Xiao and Edmund T. Rolls and has published in prestigious journals such as Trends in Neurosciences, Current Biology and Journal of Neurophysiology.

In The Last Decade

Péter Földiák

28 papers receiving 2.0k citations

Peers

Péter Földiák
Comparison fields: 5 of 98
  • Cognitive Neuroscience 1.5k
  • Artificial Intelligence 661
  • Computer Vision and Pattern Recognition 347
  • Cellular and Molecular Neuroscience 344
  • Signal Processing 249
Replace Günther Palm with:
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Michael Spratling United Kingdom
Pietro Berkes United States
Stephen José Hanson United States
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Citations per field, relative to Péter Földiák
Péter Földiák · 1×
Citations per year, relative to Péter Földiák
Péter Földiák · 1×

Countries citing papers authored by Péter Földiák

Since Specialization
Citations

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

Fields of papers citing papers by Péter Földiák

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Péter Földiák

This figure shows the co-authorship network connecting the top 25 collaborators of Péter Földiák. A scholar is included among the top collaborators of Péter Földiák 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 Péter Földiák. Péter Földiák 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
# Work Indexed citations
1 1
2 10
3 3
4 8
5
Interpreting the neural code with Formal Concept Analysis
2
6 18
7
An application of formal concept analysis to neural decoding
1
8
Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms
13
9 4
10 22
11 54
12 43
13 64
14
Sparse neural representation for semantic indexing
3
15
Sparse coding in the primate cortex
128
16 181
17 13
18 361
19
Adaptation and decorrelation in the cortex
208
20 182

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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