Neural Computation

3.2k papers and 314.2k indexed citations

About

The 3.2k papers published in Neural Computation in the last decades have received a total of 314.2k indexed citations. Papers published in Neural Computation usually cover Cognitive Neuroscience (1.7k papers), Artificial Intelligence (1.5k papers) and Cellular and Molecular Neuroscience (637 papers) specifically the topics of Neural dynamics and brain function (1.5k papers), Neural Networks and Applications (1.1k papers) and Advanced Memory and Neural Computing (529 papers). The most active scholars publishing in Neural Computation are Jürgen Schmidhuber, Sepp Hochreiter, David Mackay, Geoffrey E. Hinton, Terrence J. Sejnowski, Simon Osindero, Yee‐Whye Teh, Anthony J. Bell, Bernhard Schölkopf and Geoffrey E. Hinton.

In The Last Decade

Neural Computation

3.1k papers receiving 296.6k citations

Peers

Neural Computation
Comparison fields: 5 of 242
  • Artificial Intelligence 119.7k
  • Cognitive Neuroscience 82.7k
  • Computer Vision and Pattern Recognition 61.5k
  • Electrical and Electronic Engineering 39.9k
  • Signal Processing 37.7k
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Citations per field, relative to Neural Computation
Neural Computation · 1×
Citations per year, relative to Neural Computation
Neural Computation · 1×

Countries where authors publish in Neural Computation

Since Specialization
Citations

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

Fields of papers published in Neural Computation

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Neural Computation. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Neural Computation.

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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