https://github.com/mirkobunse/cherenkovdeconvolution.jl

Deconvolution algorithms popular in Cherenkov astronomy
https://github.com/mirkobunse/cherenkovdeconvolution.jl

astroparticle-physics classification julia-language machine-learning unfolding

Last synced: 6 days ago
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Deconvolution algorithms popular in Cherenkov astronomy

• Host: GitHub
• URL: https://github.com/mirkobunse/cherenkovdeconvolution.jl
• Owner: mirkobunse
• License: other
• Created: 2018-05-28T10:05:14.000Z (over 6 years ago)
• Default Branch: main
• Last Pushed: 2023-01-25T19:24:06.000Z (over 1 year ago)
• Last Synced: 2024-09-27T23:06:48.641Z (6 days ago)
• Topics: astroparticle-physics, classification, julia-language, machine-learning, unfolding
• Language: Julia
• Homepage: https://sfb876.tu-dortmund.de/deconvolution
• Size: 525 KB
• Stars: 7
• Watchers: 4
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

        
[![](https://img.shields.io/badge/docs-dev-blue.svg)](https://mirkobunse.github.io/CherenkovDeconvolution.jl/dev)

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# CherenkovDeconvolution.jl

Deconvolution problems arise when the probability density function of a quantity is estimated even though this quantity cannot be measured directly. In this scenario, the density has to be inferred from related quantities which are measured instead.

Please read [the documentation](https://mirkobunse.github.io/CherenkovDeconvolution.jl/dev) and [visit our website](https://sfb876.tu-dortmund.de/deconvolution).

You can install this package with the Julia package manager (Julia-0.7 and above):

```julia

] add CherenkovDeconvolution

```