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Latent Grap Learning - A Potential Open Problem for Everyone
Currently the state of the art in many regards, what we have here is to do a k nearest neighborgraph in the future space. And usually this works quite well for getting interesting answers. But you know, then there that raises the issue of, what if the grap it is a meaningful output of your problem? What if you're a causality researcher that wants to figure out how different parts of information and tract to them? They probably wouldn't be satisfied with a cate nearestNeighborhoodrap as an output of this system. So i feel like there's a lot of work to be done to actually scalebly and usefully do something like this. I think causalities is