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Aapo Hyvärinen: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Aapo Hyvärinen, Patrik O. Hoyer, Mika Inki
    Topographic ICA as a Model of Natural Image Statistics. [Citation Graph (0, 0)][DBLP]
    Biologically Motivated Computer Vision, 2000, pp:535-544 [Conf]
  2. Aapo Hyvärinen, Timo Honkela
    Emotional Disorders in Autonomous Agents? [Citation Graph (0, 0)][DBLP]
    ECAL, 1999, pp:350-354 [Conf]
  3. Aapo Hyvärinen, Urs Köster
    FastISA: A fast fixed-point algorithm for independent subspace analysis. [Citation Graph (0, 0)][DBLP]
    ESANN, 2006, pp:371-376 [Conf]
  4. Patrik O. Hoyer, Shohei Shimizu, Aapo Hyvärinen, Yutaka Kano, Antti J. Kerminen
    New Permutation Algorithms for Causal Discovery Using ICA. [Citation Graph (0, 0)][DBLP]
    ICA, 2006, pp:115-122 [Conf]
  5. Shohei Shimizu, Aapo Hyvärinen, Yutaka Kano, Patrik O. Hoyer, Antti J. Kerminen
    Testing Significance of Mixing and Demixing Coefficients in ICA. [Citation Graph (0, 0)][DBLP]
    ICA, 2006, pp:901-908 [Conf]
  6. Jarmo Hurri, Aapo Hyvärinen
    Receptive Fields Similar to Simple Cells Maximize Temporal Coherence in Natural Video. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:33-38 [Conf]
  7. Aapo Hyvärinen
    Purely Logical Neural Principal Component and Independent Component Learning. [Citation Graph (0, 0)][DBLP]
    ICANN, 1996, pp:139-144 [Conf]
  8. Aapo Hyvärinen, Shohei Shimizu
    A Quasi-stochastic Gradient Algorithm for Variance-Dependent Component Analysis. [Citation Graph (0, 0)][DBLP]
    ICANN (2), 2006, pp:211-220 [Conf]
  9. Erkki Oja, Juha Karhunen, Aapo Hyvärinen
    From Neural Principal Components to Neural Independent Components. [Citation Graph (0, 0)][DBLP]
    ICANN, 1997, pp:519-528 [Conf]
  10. Jussi T. Lindgren, Aapo Hyvärinen
    Learning High-level Independent Components of Images through a Spectral Representation. [Citation Graph (0, 0)][DBLP]
    ICPR (2), 2004, pp:72-75 [Conf]
  11. Ella Bingham, Aapo Hyvärinen
    ICA of Complex Valued Signals: A Fast and Robust Deflationary Algorithm. [Citation Graph (0, 0)][DBLP]
    IJCNN (3), 2000, pp:357-362 [Conf]
  12. Patrik O. Hoyer, Aapo Hyvärinen
    Feature Extraction from Color and Stereo Images Using ICA. [Citation Graph (0, 0)][DBLP]
    IJCNN (3), 2000, pp:369-376 [Conf]
  13. Aapo Hyvärinen, Patrik O. Hoyer, Mika Inki
    Topographic ICA as a Model of V1 Receptive Fields. [Citation Graph (0, 0)][DBLP]
    IJCNN (4), 2000, pp:83-88 [Conf]
  14. Aapo Hyvärinen
    Fast ICA for noisy data using Gaussian moments. [Citation Graph (0, 0)][DBLP]
    ISCAS (5), 1999, pp:57-61 [Conf]
  15. Patrik O. Hoyer, Aapo Hyvärinen
    Interpreting Neural Response Variability as Monte Carlo Sampling of the Posterior. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:277-284 [Conf]
  16. Jarmo Hurri, Aapo Hyvärinen
    Temporal Coherence, Natural Image Sequences, and the Visual Cortex. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:141-148 [Conf]
  17. Aapo Hyvärinen
    New Approximations of Differential Entropy for Independent Component Analysis and Projection Pursuit. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  18. Aapo Hyvärinen, Patrik O. Hoyer
    Emergence of Topography and Complex Cell Properties from Natural Images using Extensions of ICA. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:827-833 [Conf]
  19. Aapo Hyvärinen, Patrik O. Hoyer, Erkki Oja
    Sparse Code Shrinkage: Denoising by Nonlinear Maximum Likelihood Estimation. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:473-479 [Conf]
  20. Aapo Hyvärinen, Erkki Oja
    One-unit Learning Rules for Independent Component Analysis. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:480-486 [Conf]
  21. Ella Bingham, Aapo Hyvärinen
    A Fast Fixed-Point Algorithm for Independent Component Analysis of Complex Valued Signals. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 2000, v:10, n:1, pp:1-8 [Journal]
  22. Aapo Hyvärinen, Erkki Oja
    Simple Neuron Models for Independent Component Analysis. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 1996, v:7, n:6, pp:671-688 [Journal]
  23. Shun-ichi Amari, Aapo Hyvärinen, Soo-Young Lee, Te-Won Lee, V. David Sánchez A.
    Blind signal separation and independent component analysis. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2002, v:49, n:1-4, pp:1-5 [Journal]
  24. Patrik O. Hoyer, Aapo Hyvärinen
    Sparse coding of natural contours. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2002, v:44, n:, pp:459-466 [Journal]
  25. Jarmo Hurri, Aapo Hyvärinen
    A two-layer temporal generative model of natural video exhibits complex-cell-like pooling of simple cell outputs. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2003, v:52, n:, pp:553-559 [Journal]
  26. Aapo Hyvärinen
    An alternative approach to infomax and independent component analysis. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2002, v:44, n:, pp:1089-1097 [Journal]
  27. Aapo Hyvärinen
    Independent component analysis in the presence of Gaussian noise by maximizing joint likelihood. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 1998, v:22, n:1-3, pp:49-67 [Journal]
  28. Aapo Hyvärinen, Ella Bingham
    Connection between multilayer perceptrons and regression using independent component analysis. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2003, v:50, n:, pp:211-222 [Journal]
  29. Aapo Hyvärinen, Patrik O. Hoyer
    Topographic independent component analysis as a model of V1 organization and receptive fields. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2001, v:38, n:, pp:1307-1315 [Journal]
  30. Aapo Hyvärinen, Karthikesh Raju
    Imposing sparsity on the mixing matrix in independent component analysis. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2002, v:49, n:1-4, pp:151-162 [Journal]
  31. Aapo Hyvärinen
    Estimation of Non-Normalized Statistical Models by Score Matching. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2005, v:6, n:, pp:695-709 [Journal]
  32. Shohei Shimizu, Patrik O. Hoyer, Aapo Hyvärinen, Antti Kerminen
    A Linear Non-Gaussian Acyclic Model for Causal Discovery. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2003-2030 [Journal]
  33. Aapo Hyvärinen
    Realizations of quantum computing using optical manipulations of atoms. [Citation Graph (0, 0)][DBLP]
    Natural Computing, 2002, v:1, n:2-3, pp:199-209 [Journal]
  34. Jarmo Hurri, Aapo Hyvärinen
    Simple-Cell-Like Receptive Fields Maximize Temporal Coherence in Natural Video. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2003, v:15, n:3, pp:663-691 [Journal]
  35. Aapo Hyvärinen
    Complexity Pursuit: Separating Interesting Components from Time Series. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2001, v:13, n:4, pp:883-898 [Journal]
  36. Aapo Hyvärinen
    Consistency of Pseudolikelihood Estimation of Fully Visible Boltzmann Machines. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2006, v:18, n:10, pp:2283-2292 [Journal]
  37. Aapo Hyvärinen
    Sparse Code Shrinkage: Denoising of Nongaussian Data by Maximum Likelihood Estimation. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1999, v:11, n:7, pp:1739-1768 [Journal]
  38. Aapo Hyvärinen, Patrik O. Hoyer
    Emergence of Phase- and Shift-Invariant Features by Decomposition of Natural Images into Independent Feature Subspaces. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:7, pp:1705-1720 [Journal]
  39. Aapo Hyvärinen, Patrik O. Hoyer, Mika Inki
    Topographic Independent Component Analysis. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2001, v:13, n:7, pp:1527-1558 [Journal]
  40. Aapo Hyvärinen, Erkki Oja
    A Fast Fixed-Point Algorithm for Independent Component Analysis. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1997, v:9, n:7, pp:1483-1492 [Journal]
  41. Aapo Hyvärinen, Erkki Oja
    Independent component analysis: algorithms and applications. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2000, v:13, n:4-5, pp:411-430 [Journal]
  42. Aapo Hyvärinen, Petteri Pajunen
    Nonlinear independent component analysis: Existence and uniqueness results. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1999, v:12, n:3, pp:429-439 [Journal]
  43. Aapo Hyvärinen
    The Fixed-Point Algorithm and Maximum Likelihood Estimation for Independent Component Analysis. [Citation Graph (0, 0)][DBLP]
    Neural Processing Letters, 1999, v:10, n:1, pp:1-5 [Journal]
  44. Erkki Oja, Aapo Hyvärinen, Patrik O. Hoyer
    Image Feature Extraction and Denoising by Sparse Coding. [Citation Graph (0, 0)][DBLP]
    Pattern Anal. Appl., 1999, v:2, n:2, pp:104-110 [Journal]
  45. M. Asuncion Vicente, Patrik O. Hoyer, Aapo Hyvärinen
    Equivalence of Some Common Linear Feature Extraction Techniques for Appearance-Based Object Recognition Tasks. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 2007, v:29, n:5, pp:896-900 [Journal]
  46. Aapo Hyvärinen, Jarmo Hurri
    Blind separation of sources that have spatiotemporal variance dependencies. [Citation Graph (0, 0)][DBLP]
    Signal Processing, 2004, v:84, n:2, pp:247-254 [Journal]
  47. Aapo Hyvärinen
    A unifying model for blind separation of independent sources. [Citation Graph (0, 0)][DBLP]
    Signal Processing, 2005, v:85, n:7, pp:1419-1427 [Journal]
  48. Aapo Hyvärinen
    Some extensions of score matching. [Citation Graph (0, 0)][DBLP]
    Computational Statistics & Data Analysis, 2007, v:51, n:5, pp:2499-2512 [Journal]
  49. Shohei Shimizu, Aapo Hyvärinen, Patrik O. Hoyer, Yutaka Kano
    Finding a causal ordering via independent component analysis. [Citation Graph (0, 0)][DBLP]
    Computational Statistics & Data Analysis, 2006, v:50, n:11, pp:3278-3293 [Journal]
  50. Urs Köster, Aapo Hyvärinen
    A Two-Layer ICA-Like Model Estimated by Score Matching. [Citation Graph (0, 0)][DBLP]
    ICANN (2), 2007, pp:798-807 [Conf]
  51. Jussi T. Lindgren, Aapo Hyvärinen
    Emergence of conjunctive visual features by quadratic independent component analysis. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:897-904 [Conf]
  52. Jussi T. Lindgren, Jarmo Hurri, Aapo Hyvärinen
    The Statistical Properties of Local Log-Contrast in Natural Images. [Citation Graph (0, 0)][DBLP]
    SCIA, 2007, pp:354-363 [Conf]
  53. Shohei Shimizu, Aapo Hyvärinen, Yutaka Kano, Patrik O. Hoyer
    Discovery of Non-gaussian Linear Causal Models using ICA. [Citation Graph (0, 0)][DBLP]
    UAI, 2005, pp:525-533 [Conf]

  54. Learning Features by Contrasting Natural Images with Noise. [Citation Graph (, )][DBLP]


  55. Modelling Image Complexity by Independent Component Analysis, with Application to Content-Based Image Retrieval. [Citation Graph (, )][DBLP]


  56. Discovery of Exogenous Variables in Data with More Variables Than Observations. [Citation Graph (, )][DBLP]


  57. Causal modelling combining instantaneous and lagged effects: an identifiable model based on non-Gaussianity. [Citation Graph (, )][DBLP]


  58. Discovery of Linear Non-Gaussian Acyclic Models in the Presence of Latent Classes. [Citation Graph (, )][DBLP]


  59. ICA with Sparse Connections: Revisited. [Citation Graph (, )][DBLP]


  60. Learning Natural Image Structure with a Horizontal Product Model. [Citation Graph (, )][DBLP]


  61. Estimating Markov Random Field Potentials for Natural Images. [Citation Graph (, )][DBLP]


  62. Learning to Segment Any Random Vector. [Citation Graph (, )][DBLP]


  63. Learning encoding and decoding filters for data representation with a spiking neuron. [Citation Graph (, )][DBLP]


  64. On the learning of nonlinear visual features from natural images by optimizing response energies. [Citation Graph (, )][DBLP]


  65. Unsupervised learning of dependencies between local luminance and contrast in natural images. [Citation Graph (, )][DBLP]


  66. Causality Discovery with Additive Disturbances: An Information-Theoretical Perspective. [Citation Graph (, )][DBLP]


  67. Causal discovery of linear acyclic models with arbitrary distributions. [Citation Graph (, )][DBLP]


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