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Topic · Artificial Intelligence

Neural Networks and Applications

Neural Networks and Applications is a research topic within Artificial Intelligence. Science Explorer counts 99k research works in it since 1950. 10.0% of them reached the world's top 10% most cited for their field and year.

This cluster of papers covers a wide range of topics related to neural networks, including backpropagation learning, self-organizing maps, radial basis function networks, deep learning, and applications such as pattern classification and function approximation.

  • Neural Networks
  • Self-Organizing Maps
  • Backpropagation Learning
  • Radial Basis Function Networks
  • Deep Learning
  • Artificial Neural Networks
  • Recurrent Neural Networks
  • Feedforward Neural Networks
  • Pattern Classification
  • Function Approximation
Research works
99k
fractional, since 1950
In the world top 10%
9.8k
per year above
Top-10% rate
10.0%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+63%
the tick is no change
Largest producer
China
40% of the 10 largest, 2022-now
Neural Networks and Applications

Which countries lead Neural Networks and Applications research?

By volume, China and the United States publish the most (5.3k and 2.7k works in 2022-now).

By volume, 2022-now

  1. 1 China 5.3k works
  2. 2 United States 2.7k works
  3. 3 India 1.7k works
  4. 4 Japan 626 works
  5. 5 Germany 603 works
  6. 6 United Kingdom 550 works
  7. 7 France 509 works
  8. 8 Russia 469 works
  9. 9 Italy 461 works
  10. 10 South Korea 389 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 39.7%United States: 20.5%India: 12.6%Japan: 4.7%6 others listed: 22.5%40%largest
China5,257 · 39.7%United States2,719 · 20.5%India1,674 · 12.6%Japan626 · 4.7%6 others listed2,981 · 22.5%

Shares of the rows listed above, not of the whole node.

Which institutions lead Neural Networks and Applications research?

By volume in 2022-now, Centre National de la Recherche Scientifique publishes the most Neural Networks and Applications research, followed by Chinese Academy of Sciences and Russian Academy of Sciences.

By volume, 2022-now

  1. 1 Centre National de la Recherche ScientifiqueFrance 175 works
  2. 2 Chinese Academy of SciencesChina 173 works
  3. 3 Russian Academy of SciencesRussia 102 works
  4. 4 Tsinghua UniversityChina 79 works
  5. 5 University of Electronic Science and Technology of ChinaChina 78 works
  6. 6 Zhejiang UniversityChina 78 works
  7. 7 Shanghai Jiao Tong UniversityChina 74 works
  8. 8 Southeast UniversityChina 73 works
  9. 9 École Polytechnique Fédérale de LausanneSwitzerland 70 works
  10. 10 Xidian UniversityChina 63 works

Who are the leading researchers in Neural Networks and Applications?

The most-cited researchers publishing on Neural Networks and Applications include Zhong Lin Wang, Yoshua Bengio and Geoffrey E. Hinton.

  1. 1 Zhong Lin Wang United States 491k citations
  2. 2 Yoshua Bengio Canada 476k citations
  3. 3 Geoffrey E. Hinton Canada 454k citations
  4. 4 George Davey Smith United Kingdom 435k citations
  5. 5 Richard M. Durbin United Kingdom 410k citations
  6. 6 Robert John Tibshirani United States 396k citations
  7. 7 Steven L. Salzberg United States 372k citations
  8. 8 Xiangyu Zhang 327k citations
  9. 9 Karl John Friston United Kingdom 310k citations
  10. 10 Donald B. Rubin United States 301k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Neural Networks and Applications?

The most cited paper in Neural Networks and Applications is "Random Forests" (Leo Breiman, 2001), with 132,956 citations. Next come "Long Short-Term Memory" (102,418) and "Deep learning" (84,939).

Most cited papers
#PaperReleasedCitations
1 Random Forests Leo Breiman · Machine Learning Open access Oct 2001 132,956
2 Long Short-Term Memory Sepp Hochreiter, Jürgen Schmidhuber · Neural Computation Nov 1997 102,418
3 Deep learning Yann LeCun, Yoshua Bengio, Geoffrey E. Hinton · Nature Open access 26 May 2015 84,939
4 Gradient-based learning applied to document recognition Yann LeCun, Léon Bottou, Yoshua Bengio et al. · Proceedings of the IEEE Open access 1998 59,921
5 Particle swarm optimization James C. Kennedy, R.C. Eberhart Conference paper 19 Nov 2002 48,693
All 97 most cited papers, with filters and sorting

Where is Neural Networks and Applications research done?

The largest centres of Neural Networks and Applications research in 2022-now are Beijing (China), Shanghai (China), Nanjing (China) and Xi'an (China). Among places with at least 20 works in it, it is an unusually large share of all research in Tijuana and El Paso.

Largest cities, 2022-now

  1. 1 BeijingChina 918 works
  2. 2 ShanghaiChina 330 works
  3. 3 NanjingChina 280 works
  4. 4 Xi'anChina 273 works
  5. 5 TokyoJapan 233 works
  6. 6 ChengduChina 217 works
  7. 7 GuangzhouChina 210 works
  8. 8 SeoulSouth Korea 201 works
  9. 9 WuhanChina 200 works
  10. 10 HangzhouChina 193 works

Where it is the local speciality

  1. TijuanaMX · 20.5 works18×
  2. El PasoUS · 24.1 works8.6×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Neural Networks and Applications than the world average.

See Neural Networks and Applications on the map

Where is the best place to study Neural Networks and Applications?

Among universities, judged by research, Southeast University, City University of Hong Kong and Nanyang Technological University score highest, combining citation excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 19.24%fractional works in this field (log) →share of work in the world top 10% →Northeastern Univers…Southeast UniversityCity University of H…Nanyang Technologica…
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Citation excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Southeast UniversityChina 69.724.3%3.1×73 +157.7%
2City University of Hong KongChina 64.918.9%4.2×38 +97.9%
3Nanyang Technological UniversitySingapore 62.316.6%3.5×44 +107.8%
4Northeastern UniversityChina 62.126.0%4.0×56 +127.6%
5Zhejiang UniversityChina 61.220.2%1.8×78 +257.1%
6University of Electronic Science and Technology of ChinaChina 59.713.6%4.5×78 +138.1%
7Xidian UniversityChina 59.618.0%5.5×63 +244.2%
8École Polytechnique Fédérale de LausanneSwitzerland 59.53.6%10.8×70 +392.2%
9Hunan UniversityChina 59.431.1%3.1×35 +173.8%
10National University of SingaporeSingapore 58.920.1%1.9×36 +205.9%

Universities only. The score blends citation excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Neural Networks and Applications, country by country

Is Neural Networks and Applications research growing?

Output in 2022-2025 was 63% higher than in 2018-2021, peaking in 2024. The fastest-growing topics are Neural Networks and Applications.

still counting19801990200020102020
grewheldshrank

The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Neural Networks and Applications as a percentage of every work published that year, 0.11% in 2024.

still counting0.20%0.40%Neural Networks and Applications0.096% in 202519801990200020102020

Fractional works of Neural Networks and Applications over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Neural Networks and Applications10.1% in 2025200020102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.

Questions people ask

Who leads neural network research?

By volume in 2022-now, Centre National de la Recherche Scientifique publishes the most Neural Networks and Applications research, followed by Chinese Academy of Sciences and Russian Academy of Sciences. By volume, China and the United States publish the most (5.3k and 2.7k works in 2022-now).

What are the best universities for machine learning research?

By volume in 2022-now, Centre National de la Recherche Scientifique publishes the most Neural Networks and Applications research, followed by Chinese Academy of Sciences and Russian Academy of Sciences.

Which institutions lead Neural Networks and Applications research?
All 1,273 questions in the Question Catalogue

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