| Independent component analysis, adaptive and learning systems for signal processing, communications, and control A Hyvärinen, J Karhunen, E Oja John Wiley & Sons, Inc 1, 11-14, 2001 | 781* | 2001 |
| On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix E Oja, J Karhunen Journal of mathematical analysis and applications 106 (1), 69-84, 1985 | 744 | 1985 |
| A class of neural networks for independent component analysis J Karhunen, E Oja, L Wang, R Vigario, J Joutsensalo IEEE Transactions on neural networks 8 (3), 486-504, 1997 | 646 | 1997 |
| Representation and separation of signals using nonlinear PCA type learning J Karhunen, J Joutsensalo Neural networks 7 (1), 113-127, 1994 | 551 | 1994 |
| Generalizations of principal component analysis, optimization problems, and neural networks J Karhunen, J Joutsensalo Neural Networks 8 (4), 549-562, 1995 | 422 | 1995 |
| Advances in blind source separation (BSS) and independent component analysis (ICA) for nonlinear mixtures C Jutten, J Karhunen International journal of neural systems 14 (05), 267-292, 2004 | 382 | 2004 |
| Neural approaches to independent component analysis and source separation. J Karhunen ESANN 96, 249-266, 1996 | 214 | 1996 |
| Nonlinear blind source separation by self-organizing maps P Pajunen ICONIP 96 2, 1207-1210, 1996 | 210 | 1996 |
| An unsupervised ensemble learning method for nonlinear dynamic state-space models H Valpola, J Karhunen Neural computation 14 (11), 2647-2692, 2002 | 179 | 2002 |
| The nonlinear PCA criterion in blind source separation: Relations with other approaches J Karhunen, P Pajunen, E Oja Neurocomputing 22 (1-3), 5-20, 1998 | 165 | 1998 |
| Applications of neural blind separation to signal and image processing J Karhunen, A Hyvarinen, R Vigário, J Hurri, E Oja 1997 IEEE International Conference on Acoustics, Speech, and Signal …, 1997 | 161 | 1997 |
| Bidirectional recurrent neural networks as generative models M Berglund, T Raiko, M Honkala, L Kärkkäinen, A Vetek, JT Karhunen Advances in neural information processing systems 28, 2015 | 133 | 2015 |
| Approximate Riemannian conjugate gradient learning for fixed-form variational Bayes A Honkela, T Raiko, M Kuusela, M Tornio, J Karhunen The Journal of Machine Learning Research 11, 3235-3268, 2010 | 131 | 2010 |
| Neural networks for blind separation with unknown number of sources A Cichocki, J Karhunen, W Kasprzak, R Vigario Neurocomputing 24 (1-3), 55-93, 1999 | 129 | 1999 |
| Plasma–wall interaction studies within the EUROfusion consortium: progress on plasma-facing components development and qualification S Brezinsek, JW Coenen, T Schwarz-Selinger, K Schmid, A Kirschner, ... Nuclear fusion 57 (11), 116041, 2017 | 125 | 2017 |
| Signal separation by nonlinear Hebbian learning E Oja, J Karhunen Computational intelligence: A dynamic system perspective, 83-97, 1995 | 112 | 1995 |
| An experimental comparison of neural algorithms for independent component analysis and blind separation X Giannakopoulos, J Karhunen, E Oja International journal of neural systems 9 (02), 99-114, 1999 | 110 | 1999 |
| Principal component analysis for large scale problems with lots of missing values T Raiko, A Ilin, J Karhunen European Conference on Machine Learning, 691-698, 2007 | 105 | 2007 |
| Unsupervised deep learning: A short review J Karhunen, T Raiko, KH Cho Advances in independent component analysis and learning machines, 125-142, 2015 | 92 | 2015 |
| Image feature extraction using independent component analysis J Hurri Proceedings of the 1996 IEEE Nordic Signal Processing Symposium, NORSIG'96 …, 1996 | 92 | 1996 |
