introduction for our geometric-convolution paper

My loyal reader knows that Soledad Villar (JHU) and I are working on a replacement for convolutional neural networks, that preserves convolutional structure, but enforces important physical symmetries (most importantly coordinate-freedom, or what I call coordinate-freedom). Today I deleted the introduction to our paper and re-wrote it from scratch.

When we last wrote the introduction, we thought we were writing code for cosmology. Now we think we are doing something way more general. In writing this, I realized that we need a figure that shows some kind of gallery or set of examples of the kinds of data we are talking about, which are images or grids of scalars, vectors, and tensors.