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文件名称:gpldecha-e-pca-d542a9b
介绍说明－－下载内容来自于网络，使用问题请自行百度
PCA是一种非线性降维方法特别适合于概率分布，得到了指数族PCA的POMDPs压缩。(Matlab implementation of E-PCA which is a non-linear dimensionality reduction method particularly suited for probability distributions, see the paper Exponential Family PCA for Belief Compression in POMDPs.)
相关搜索： E-PCA
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下载文件列表
gpldecha-e-pca-d542a9b
gpldecha-e-pca-d542a9b\Example1.m
gpldecha-e-pca-d542a9b\Example2.m
gpldecha-e-pca-d542a9b\LICENSE.md
gpldecha-e-pca-d542a9b\README.md
gpldecha-e-pca-d542a9b\docs
gpldecha-e-pca-d542a9b\docs\EPCA_proj5.png
gpldecha-e-pca-d542a9b\docs\EPCA_proj5.svg
gpldecha-e-pca-d542a9b\docs\PCA_EPCA.png
gpldecha-e-pca-d542a9b\docs\PCA_EPCA.svg
gpldecha-e-pca-d542a9b\docs\PCA_proj_5.png
gpldecha-e-pca-d542a9b\docs\PCA_proj_5.svg
gpldecha-e-pca-d542a9b\docs\example2.png
gpldecha-e-pca-d542a9b\docs\original_belief.gif
gpldecha-e-pca-d542a9b\docs\original_pdf_20.png
gpldecha-e-pca-d542a9b\docs\reconstructed_belief.gif
gpldecha-e-pca-d542a9b\docs\reconstructed_pdf_20.png
gpldecha-e-pca-d542a9b\epca
gpldecha-e-pca-d542a9b\epca\epca.m
gpldecha-e-pca-d542a9b\epca\epca_lw.m
gpldecha-e-pca-d542a9b\epca\eval_epca.m
gpldecha-e-pca-d542a9b\epca\eval_pca.m
gpldecha-e-pca-d542a9b\epca\init_epca_U_B.m
gpldecha-e-pca-d542a9b\epca\lepca.m
gpldecha-e-pca-d542a9b\epca\lpca.m
gpldecha-e-pca-d542a9b\extra
gpldecha-e-pca-d542a9b\extra\gauss
gpldecha-e-pca-d542a9b\extra\gauss\gaussPDF.m
gpldecha-e-pca-d542a9b\extra\gauss\gmm_pdf.m
gpldecha-e-pca-d542a9b\extra\kl_divergence.m
gpldecha-e-pca-d542a9b\extra\rescale.m
gpldecha-e-pca-d542a9b\parameters
gpldecha-e-pca-d542a9b\parameters\B.mat
gpldecha-e-pca-d542a9b\parameters\U.mat
gpldecha-e-pca-d542a9b\parameters\hB.mat
gpldecha-e-pca-d542a9b\Example1.m
gpldecha-e-pca-d542a9b\Example2.m
gpldecha-e-pca-d542a9b\LICENSE.md
gpldecha-e-pca-d542a9b\README.md
gpldecha-e-pca-d542a9b\docs
gpldecha-e-pca-d542a9b\docs\EPCA_proj5.png
gpldecha-e-pca-d542a9b\docs\EPCA_proj5.svg
gpldecha-e-pca-d542a9b\docs\PCA_EPCA.png
gpldecha-e-pca-d542a9b\docs\PCA_EPCA.svg
gpldecha-e-pca-d542a9b\docs\PCA_proj_5.png
gpldecha-e-pca-d542a9b\docs\PCA_proj_5.svg
gpldecha-e-pca-d542a9b\docs\example2.png
gpldecha-e-pca-d542a9b\docs\original_belief.gif
gpldecha-e-pca-d542a9b\docs\original_pdf_20.png
gpldecha-e-pca-d542a9b\docs\reconstructed_belief.gif
gpldecha-e-pca-d542a9b\docs\reconstructed_pdf_20.png
gpldecha-e-pca-d542a9b\epca
gpldecha-e-pca-d542a9b\epca\epca.m
gpldecha-e-pca-d542a9b\epca\epca_lw.m
gpldecha-e-pca-d542a9b\epca\eval_epca.m
gpldecha-e-pca-d542a9b\epca\eval_pca.m
gpldecha-e-pca-d542a9b\epca\init_epca_U_B.m
gpldecha-e-pca-d542a9b\epca\lepca.m
gpldecha-e-pca-d542a9b\epca\lpca.m
gpldecha-e-pca-d542a9b\extra
gpldecha-e-pca-d542a9b\extra\gauss
gpldecha-e-pca-d542a9b\extra\gauss\gaussPDF.m
gpldecha-e-pca-d542a9b\extra\gauss\gmm_pdf.m
gpldecha-e-pca-d542a9b\extra\kl_divergence.m
gpldecha-e-pca-d542a9b\extra\rescale.m
gpldecha-e-pca-d542a9b\parameters
gpldecha-e-pca-d542a9b\parameters\B.mat
gpldecha-e-pca-d542a9b\parameters\U.mat
gpldecha-e-pca-d542a9b\parameters\hB.mat
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