this post was submitted on 09 Nov 2023
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Machine Learning
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Gonna toot my own research direction: artificial intelligence x complex systems. I’m talking differentiable self-organization (e.g., neural cellular automata), interacting particle systems (e.g., particle Lenia), and other neural dynamical systems where emergent behaviour and self-organization are key characteristics.
Other than Alex Mordvintsev and his co-authors, Sebastian Risi and his co-authors, and I suppose David Ha with his new company, I don’t see much work in this intersection of fields.
I think there’s a lot to unlock here, particularly if the task at hand benefits greatly from a decentralized and/or a compute-adaptive approach, with robustness requirements. Swarm Learning already comes to mind. Or generative modelling with/of complex systems, like decentralized flow (or Schrödinger) matching for modelling interacting particle systems (e.g., fluids, gasses, pedestrian traffic).
Could you please point to a few recent research papers in this area?
I think this is the most important topic in this thread so far.
Why is that? You've got me curious
Last year when I heard from one of my friends, who is a medical data researcher from Harvard, that he and his colleagues were doing researches related to federated learning, I knew this topic gotta be trendy for the recent years