| Unfortunately, I don’t know of much — the convolution thing is from a whitepaper I’m currently working on, the third in a series. The first two look at implementing shapes as diagrams as digital images: https://www.zmgsabstract.com/whitepapers/shapes-as-digital-i... https://www.zmgsabstract.com/whitepapers/shapes-have-operati... You can get a sense of the convolution idea from thinking about how you’d detect the encoded square is an interval of intervals, via detecting a pattern along the diagonal and the connective blocks. I also have a few notes on connecting the concept to Curry-Howard: https://zmichaelgehlke.com/journals/2021-06-14-curry-howard-... And some (messy) notes about general research direction: https://zmichaelgehlke.com/journals/2021-01-30-intro-to-effe... The idea of connecting a geometric and algebraic representation is based on work by Michael Shulman — and the internal languages of toposes. And work on the ML side such as covering based models. (Having trouble finding references on my phone; sorry.) |