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4426-structural-equations-and-divisive-normalization-for-energy-dependent-component-analysis.pdf
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🔗 Source: papers.nips.cc
📊 Size: 6.42 MB
👤 Author: Jun-ichiro Hirayama, Aapo Hyvärinen
⬇️ Downloads: 82

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Jun-ichiro Hirayama and Aapo Hyvärinen propose a probabilistic model for energy-dependent component analysis, incorporating a linear mixing of latent signals and a structural equation model (SEM) to account for energy-correlations between latent variables. Their two-stage model enables estimation of both linear mixing and energy-correlations without approximations or non-principled approaches. The model is related to divisive normalization, which reduces energy-correlations in natural signals, and is demonstrated with synthetic data, natural images, and brain signals.

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Jun-ichiro Hirayama and Aapo Hyvärinen propose a probabilistic model for energy-dependent component analysis, incorporating a linear mixing of latent signals...

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  • File Format: PDF
  • File Size: 6.42 MB
  • Pages: 9
  • Language: EN
  • Author: Jun-ichiro Hirayama, Aapo Hyvärinen
  • Total Downloads: 82
  • Last Updated: 10 hours ago

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