BayesianSVD

所属分类:人工智能/神经网络/深度学习
开发工具:Julia
文件大小:0KB
下载次数:0
上传日期:2023-07-28 19:36:38
上 传 者sh-1993
说明:  贝叶斯SVD.jl,,
(BayesianSVD.jl,,)

文件列表:
.DS_Store (12292, 2023-11-28)
LICENSE (1108, 2023-11-28)
NERSC/ (0, 2023-11-28)
NERSC/PDO.jl (6105, 2023-11-28)
NERSC/PDO.sh (1380, 2023-11-28)
NERSC/PDOcontinue.jl (999, 2023-11-28)
NERSC/simulationStudy.jl (4579, 2023-11-28)
NERSC/simulationStudy.sh (1224, 2023-11-28)
Project.toml (955, 2023-11-28)
docs/ (0, 2023-11-28)
docs/.DS_Store (6148, 2023-11-28)
docs/Manifest.toml (36346, 2023-11-28)
docs/Project.toml (645, 2023-11-28)
docs/make.jl (1160, 2023-11-28)
docs/src/ (0, 2023-11-28)
docs/src/api.md (105, 2023-11-28)
docs/src/assets/ (0, 2023-11-28)
docs/src/assets/Ubasis.png (112867, 2023-11-28)
docs/src/assets/Vbasis.png (81512, 2023-11-28)
docs/src/assets/surfaceEstimate.png (617610, 2023-11-28)
docs/src/example.md (5036, 2023-11-28)
docs/src/index.md (2158, 2023-11-28)
docs/src/simulateData.md (1820, 2023-11-28)
examples/ (0, 2023-11-28)
examples/.DS_Store (6148, 2023-11-28)
examples/1DExample.jl (23772, 2023-11-28)
examples/1DLinearTrendExample.jl (14694, 2023-11-28)
examples/1DPointsExample.jl (15517, 2023-11-28)
examples/2DExample.jl (20585, 2023-11-28)
examples/ComplexCovariates.jl (16232, 2023-11-28)
examples/ProcessPDO.jl (30588, 2023-11-28)
... ...

# BayesianSVD.jl [![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://jsnowynorth.github.io/BayesianSVD.jl/stable/) [![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://jsnowynorth.github.io/BayesianSVD.jl/dev/) [![Build Status](https://github.com/jsnowynorth/BayesianSVD.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/jsnowynorth/BayesianSVD.jl/actions/workflows/CI.yml?query=branch%3Amain) [![codecov.io](http://codecov.io/github/jsnowynorth/BayesianSVD.jl/coverage.svg?branch=main)](http://codecov.io/github/jsnowynorth/BayesianSVD.jl?branch=main) A package for implimenting the Bayesian SVD model from ``A flexible class of priors for conducting posterior inference on structured orthonormal matrices'', which can be found at https://arxiv.org/abs/2307.13627. To install the package, clone the repository from GitHub and place it in your `/.julia/dev/` folder, navigate to the folder, and run ``` julia> ] dev . ``` This will make the package callable via the `using BayesianSVD` command. drawing

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