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[ascl:2110.015] Flux: Julia machine learning library

Flux provides an elegant approach to machine learning. Written in Julia, it provides lightweight abstractions on top of Julia's native GPU and AD support. It has many useful tools built in, but also lets you use the full power of the Julia language where you need it. Flux has relatively few explicit APIs for features like regularization or embeddings; instead, writing down the mathematical form works and is fast. The package works well with Julia libraries from data frames and images to differential equation solvers, so building complex data processing pipelines that integrate Flux models is straightforward.

Code site:
https://fluxml.ai/ https://github.com/FluxML/Flux.jl
Used in:
https://ui.adsabs.harvard.edu/abs/2020MNRAS.492.3217C
Described in:
https://ui.adsabs.harvard.edu/abs/2018arXiv181101457I https://ui.adsabs.harvard.edu/abs/2018JOSS....3..602I
Bibcode:
2021ascl.soft10015I
Preferred citation method:

Please see citation information here: https://github.com/FluxML/Flux.jl/blob/master/CITATION.bib


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ascl:2110.015
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