Science Explorer Back to mapMap
Discussion
Topic · Computational Mechanics

Sparse and Compressive Sensing Techniques

Sparse and Compressive Sensing Techniques is a research topic within Computational Mechanics. Science Explorer counts 27k research works in it since 1959. 9.7% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the theory and applications of compressed sensing, including sparse representation, signal recovery, convex optimization, matrix completion, dictionary learning, orthogonal matching pursuit, robust reconstruction, and sparsity in signal processing.

  • Compressed Sensing
  • Sparse Representation
  • Signal Recovery
  • Convex Optimization
  • Matrix Completion
  • Sparse Approximation
  • Dictionary Learning
  • Orthogonal Matching Pursuit
  • Robust Reconstruction
  • Sparsity in Signal Processing
Research works
27k
fractional, since 1959
In the world top 10%
2.7k
per year above
Top-10% rate
9.7%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
-13%
the tick is no change
Largest producer
China
60% of the 10 largest, 2022-now
Sparse and Compressive Sensing Techniques

Which countries lead Sparse and Compressive Sensing Techniques research?

By volume, China and the United States publish the most (3.1k and 834 works in 2022-now).

By volume, 2022-now

  1. 1 China 3.1k works
  2. 2 United States 834 works
  3. 3 India 255 works
  4. 4 France 189 works
  5. 5 Germany 160 works
  6. 6 Japan 153 works
  7. 7 United Kingdom 147 works
  8. 8 Italy 106 works
  9. 9 South Korea 87 works
  10. 10 Canada 83 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: 60.2%United States: 16.5%India: 5.0%France: 3.7%6 others listed: 14.5%60%largest
China3,051 · 60.2%United States834 · 16.5%India255 · 5.0%France189 · 3.7%6 others listed737 · 14.5%

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

Which institutions lead Sparse and Compressive Sensing Techniques research?

By volume in 2022-now, University of Electronic Science and Technology of China publishes the most Sparse and Compressive Sensing Techniques research, followed by Chinese Academy of Sciences and Xidian University.

By volume, 2022-now

  1. 1 University of Electronic Science and Technology of ChinaChina 111 works
  2. 2 Chinese Academy of SciencesChina 110 works
  3. 3 Xidian UniversityChina 83 works
  4. 4 Centre National de la Recherche ScientifiqueFrance 65 works
  5. 5 National University of Defense TechnologyChina 64 works
  6. 6 Harbin Institute of TechnologyChina 54 works
  7. 7 Beijing Institute of TechnologyChina 51 works
  8. 8 Zhejiang UniversityChina 45 works
  9. 9 Beijing University of Posts and TelecommunicationsChina 40 works
  10. 10 Sun Yat-sen UniversityChina 38 works

Who are the leading researchers in Sparse and Compressive Sensing Techniques?

The most-cited researchers publishing on Sparse and Compressive Sensing Techniques include Kaiming He, Yoshua Bengio and Robert John Tibshirani.

  1. 1 Kaiming He Israel 562k citations
  2. 2 Yoshua Bengio Canada 476k citations
  3. 3 Robert John Tibshirani United States 396k citations
  4. 4 Xiangyu Zhang 327k citations
  5. 5 Karl John Friston United Kingdom 310k citations
  6. 6 Trevor Hastie United States 301k citations
  7. 7 Xiaogang Wang China 260k citations
  8. 8 Yann LeCun United States 256k citations
  9. 9 Andrew Zisserman United Kingdom 255k citations
  10. 10 Vladimir N. Vapnik United States 227k 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 Sparse and Compressive Sensing Techniques?

The most cited paper in Sparse and Compressive Sensing Techniques is "Compressed sensing" (David L. Donoho, 2006), with 23,533 citations. Next come "Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images" (18,093) and "Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information" (15,931).

Most cited papers
#PaperReleasedCitations
1 Compressed sensing David L. Donoho · IEEE Transactions on Information Theory Apr 2006 23,533
2 Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images Stuart Geman, Donald Geman · IEEE Transactions on Pattern Analysis and Machine Intelligence Nov 1984 18,093
3 Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information Emmanuel J. Candès, Justin K. Romberg, Terence Tao · IEEE Transactions on Information Theory 25 Jan 2006 15,931
4 Regularization Paths for Generalized Linear Models via Coordinate Descent. Jerome H. Friedman, Trevor Hastie, Rob Tibshirani · PubMed Open access 2010 14,024
5 A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems Amir Beck, Marc Teboulle · SIAM Journal on Imaging Sciences 2009 12,347
All 99 most cited papers, with filters and sorting

Where is Sparse and Compressive Sensing Techniques research done?

The largest centres of Sparse and Compressive Sensing Techniques research in 2022-now are Beijing (China), Xi'an (China), Nanjing (China) and Shanghai (China). Among places with at least 20 works in it, it is an unusually large share of all research in Guilin.

Largest cities, 2022-now

  1. 1 BeijingChina 529 works
  2. 2 Xi'anChina 222 works
  3. 3 NanjingChina 206 works
  4. 4 ShanghaiChina 190 works
  5. 5 ChengduChina 180 works
  6. 6 GuangzhouChina 130 works
  7. 7 ChongqingChina 112 works
  8. 8 HangzhouChina 109 works
  9. 9 ShenzhenChina 104 works
  10. 10 ChangshaChina 102 works

Where it is the local speciality

  1. GuilinCN · 29.3 works6.0×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Sparse and Compressive Sensing Techniques than the world average.

See Sparse and Compressive Sensing Techniques on the map

Where is the best place to study Sparse and Compressive Sensing Techniques?

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

0%10%20%30%mean 18.74%fractional works in this field (log) →share of work in the world top 10% →Westlake UniversityCity University of H…University of Hong K…Hong Kong Polytechni…
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.

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
1City University of Hong KongChina 68.720.0%6.8×20 +0.6%
2Westlake UniversityChina 65.524.5%13.6×9 +457.8%
3University of Hong KongChina 64.918.0%4.7×23 +18.5%
4Hong Kong Polytechnic UniversityChina 64.317.9%4.7×21 -1.3%
5Southwest UniversityChina 63.919.1%10.1×28 +50.8%
6University of Electronic Science and Technology of ChinaChina 62.312.4%19.0×111 -12.6%
7Northwestern Polytechnical UniversityChina 60.823.2%6.5×38 -17.0%
8Southeast UniversityChina 60.215.4%4.9×37 +35.5%
9Southwest Jiaotong UniversityChina 59.622.7%4.4×18 +109.4%
10Xidian UniversityChina 59.414.2%22.0×83 -15.4%

Universities only. The score blends 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 Sparse and Compressive Sensing Techniques, country by country

Is Sparse and Compressive Sensing Techniques research growing?

Output in 2022-2025 was 13% lower than in 2018-2021, peaking in 2018.

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 Sparse and Compressive Sensing Techniques as a percentage of every work published that year, 0.020% in 2024.

still counting0.020%0.040%0.060%Sparse and Compressive Sensing Techniques0.022% in 202519801990200020102020

Fractional works of Sparse and Compressive Sensing Techniques 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%Sparse and Compressive Sensing Techniques9.7% 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.

Discussion

Ask a question or share a note about Sparse and Compressive Sensing Techniques. Posts are plain text and can be reported.