References for theory behind Geometric Deep Learning

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I'm currently reading a blog post on "Geometric Deep Learning," which I find fascinating yet challenging to comprehend without a solid mathematical background. I am halfway through my bachelor's degree in mathematics. Groups have been covered in my Linear Algebra course, but geometry has not been part of the curriculum thus far. In my search for resources on the internet, I've noticed that most sources either dive directly into topics such as (Non)-Euclidean geometry or hyperbolic geometry without defining what geometry is, a gap that the blog post successfully fills.

The closest resource I could find was a forum post, which, unfortunately, lacks any references. Consequently, my question is as follows:

Does anyone know of a reference that discusses geometry in an abstract manner, similar to what is done in the forum post and the blog post?