[6gvONxR4sf7o]

I use a similar notation, but never quite found a satisfactory notation for elementwise operations (e.g. `-M-a + -b`, especially broadcasted ones which I end up doing as `-A-B- + -c 1-`) or for denoting what derivatives are with respect to. Using differentials gets around some of the latter, but still, I was never quite satisfied. Any chance you've found nice options there?

[thomasahle]

The broadcasting using "1-" (or the order-1 copy/kronecker tensor) is actually pretty nice, I think. It allows a lot of nice manipulations, and make the low rank of the matrices really clear etc.

Addition does feel a bit hacky, but it may just be necessary for any associative notation. At least it means that rules such as distribution works the same as with classical notation.

I also wrote this tensorgrad library to do symbolic calculations using tensor networks: https://github.com/thomasahle/tensorgrad it keeps track of what you are taking derivatives with respect to. But I agree it would be nice to show more explicitly.