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Appendix S1 - A Projection and Density Estimation Method for Knowledge Discovery

Figshare2015-12-02 更新2026-04-29 收录

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https://figshare.com/articles/dataset/A_Projection_and_Density_Estimation_Method_for_Knowledge_Discovery/119549 数据链接链接失效反馈

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The appendix consists of three sections covering: 1d-density estimation, runtime remarks, and model selection. (DOC)

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创建时间：

2015-12-02

密度估计

变分自编码器

该数据集是一个为密度估计生成的双月数据集，包含了在二维潜在空间中的500个点。这些数据被用于比较不同VAE模型在KL散度方面的性能。具体任务包括利用VAE、Comb-VAE和Qr-VAE进行方差估计。规模上，数据集包含了500个点。

arXiv150

Density Deconvolution with Additive Measurement Errors using Quadratic Programming (revision)

密度估计

二次规划

Distribution estimation for noisy data via density deconvolution is a notoriously difficult problem, especially for typical noise distributions like Gaussian. We develop a density deconvolution estima

DataCite Commons2020-08-26 更新90

SHAPES

机器学习

密度估计

该数据集是一个用于概念验证实验的低维数据集，它展示了将两个连续协变量与一个分类类别标签结合的方法。边界并不总是清晰，这表明通过增加树的数量或扩大训练集，还有改进的空间。该数据集包含了2000个样本，其任务是进行密度估计和生成建模。

arXiv70

Partition Weighted Approach for Estimating the Marginal Posterior Density with Applications

贝叶斯分析

密度估计

The computation of marginal posterior density in Bayesian analysis is essential in that it can provide complete information about parameters of interest. Furthermore, the marginal posterior density ca

tandf.figshare.com2023-05-31 更新110

Covariate Information Matrix for Sufficient Dimension Reduction

充分降维

密度估计

Building upon recent research on the applications of the density information matrix, we develop a tool for sufficient dimension reduction (SDR) in regression problems called covariate information matr

DataCite Commons2022-02-10 更新80

Appendix S1 - A Projection and Density Estimation Method for Knowledge Discovery

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