Juha Karhunen

9.7k total citations · 1 hit paper
104 papers, 6.0k citations indexed

About

Juha Karhunen is a scholar working on Signal Processing, Artificial Intelligence and Analytical Chemistry. According to data from OpenAlex, Juha Karhunen has authored 104 papers receiving a total of 6.0k indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Signal Processing, 60 papers in Artificial Intelligence and 26 papers in Analytical Chemistry. Recurrent topics in Juha Karhunen's work include Blind Source Separation Techniques (67 papers), Neural Networks and Applications (48 papers) and Spectroscopy and Chemometric Analyses (26 papers). Juha Karhunen is often cited by papers focused on Blind Source Separation Techniques (67 papers), Neural Networks and Applications (48 papers) and Spectroscopy and Chemometric Analyses (26 papers). Juha Karhunen collaborates with scholars based in Finland, Switzerland and Japan. Juha Karhunen's co-authors include Erkki Oja, Aapo Hyvärinen, J. Joutsensalo, Harri Valpola, Ricardo Vigário, P. Pajunen, Christian Jutten, Tapani Raiko, Tapani Ristaniemi and Antti Honkela and has published in prestigious journals such as IEEE Transactions on Signal Processing, IEEE Transactions on Wireless Communications and Neural Computation.

In The Last Decade

Juha Karhunen

100 papers receiving 5.6k citations

Hit Papers

Independent Component Analysis 2001 2026 2009 2017 2001 1000 2.0k 3.0k

Peers

Juha Karhunen
Comparison fields: 5 of 153
  • Signal Processing 3.9k
  • Artificial Intelligence 2.0k
  • Analytical Chemistry 1.4k
  • Cognitive Neuroscience 1.0k
  • Computer Vision and Pattern Recognition 982
Replace Christian Jutten with:
Christian Jutten France
Pierre Comon France
J.-F. Cardoso France
Patrik O. Hoyer Finland
Lieven De Lathauwer Belgium
Barak A. Pearlmutter United States
Karim Abed‐Meraim France
C.L. Nikias United States
Michael E. Tipping United Kingdom
Howard H. Yang China
Christian Jutten France View profile →
Citations per field, relative to Juha Karhunen
Juha Karhunen · 1×
Citations per year, relative to Juha Karhunen
Juha Karhunen · 1×

Countries citing papers authored by Juha Karhunen

Since Specialization
Citations

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

Fields of papers citing papers by Juha Karhunen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Juha Karhunen

This figure shows the co-authorship network connecting the top 25 collaborators of Juha Karhunen. A scholar is included among the top collaborators of Juha Karhunen 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 Juha Karhunen. Juha Karhunen 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 31
2
Bidirectional recurrent neural networks as generative models
65
3 10
4
Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes
48
5
Building Blocks for Variational Bayesian Learning of Latent Variable Models
15
6 32
7 16
8 49
9
Independent Component Analysis breakdown →
3247
10
An Ensemble Learning Approach to Nonlinear Independent Component Analysis
1
11
Blind separation of convolved mixtures for CDMA systems
11
12 5
13
Blind separation from ε-contaminated mixtures
2
14 280
15
Neural approaches to independent component analysis and source separation.
81
16 4
17
Neural Estimation of Basis Vectors in Independent Component Analysis
13
18 21
19 340
20
Recursive estimation of eigenvectors of correlation type matrices for signal processing applications
9

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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