# \[ANN\] TensorAlgebra.jl: Taking covariance seriously

**URL:** <https://discourse.julialang.org/t/ann-tensoralgebra-jl-taking-covariance-seriously/43587>\
**Category:** Package Announcements\
**Tags:** package, announcement, algebra, tensors\
**Created:** [July 23, 2020, 9:26pm UTC](https://discourse.julialang.org/t/ann-tensoralgebra-jl-taking-covariance-seriously/43587 "2020-07-23T21:26:16Z")\
**Posts on this page:** 1\
**Showing post:** 11

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**Author:** ![thisrod](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/thisrod/32/10642_2.png) [@thisrod](https://discourse.julialang.org/u/thisrod)\
**Post date:** [July 28, 2020, 8:40am UTC](https://discourse.julialang.org/t/ann-tensoralgebra-jl-taking-covariance-seriously/43587/11 "2020-07-28T08:40:14Z")

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Here’s my attempt at the same problem: [ANN: Tensars.jl: Tensors as linear mappings of multidimensional arrays](https://discourse.julialang.org/t/ann-tensars-jl-tensors-as-linear-mappings-of-multidimensional-arrays/36576)

I think we have approached this from opposite sides. You’re looking for the closest thing to a mathematical tensor that will fit into a programing language, while I’m looking for the smallest and simplest extension of Julia that can calculate with tensors. Both approaches are worth pursuing.

I’m currently stuck on the suggestion from @mcabbot about identifying tensors with matrices. That led me down a rabbit hole of annotated arrays, broadcasting, matmul and structured matrix types. I should take some time off from that to do an MVP, and to implement the suggestions from @ChrisRackauckas on what’s required for tensors to work efficiently in Julia.

Good to see who else is working on it!

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