What is the shape predicted by compmech under a generation setting, and do you expect it instead of the fractal shape to show up under, say, a GAN loss? If so, and if their shapes are sufficiently distinct from the controls that are run to make sure the fractals aren’t just a visualization artifact, that would be further evidence in favor of the applicability of compmech in this setup.
Cool idea! I don’t know enough about GANs and their loss so I don’t have a prediction to report right now. If it is the case that GAN loss should really give generative and not predictive structure, this would be a super cool experiment.
The structure of generation for this particular process has just 3 points equidistant from eachother, no fractal. But in general the shape of generation is a pretty nuanced issue because it’s nontrivial to know for sure that you have the minimal structure of generation. There’s a lot more to say about this but @Paul Riechers knows these nuances more than I do so I will leave it to him!
What is the shape predicted by compmech under a generation setting, and do you expect it instead of the fractal shape to show up under, say, a GAN loss? If so, and if their shapes are sufficiently distinct from the controls that are run to make sure the fractals aren’t just a visualization artifact, that would be further evidence in favor of the applicability of compmech in this setup.
Cool idea! I don’t know enough about GANs and their loss so I don’t have a prediction to report right now. If it is the case that GAN loss should really give generative and not predictive structure, this would be a super cool experiment.
The structure of generation for this particular process has just 3 points equidistant from eachother, no fractal. But in general the shape of generation is a pretty nuanced issue because it’s nontrivial to know for sure that you have the minimal structure of generation. There’s a lot more to say about this but @Paul Riechers knows these nuances more than I do so I will leave it to him!