Seeds for research

I adopted the concept of seeds from the book, the creative act by Rick Rubin here to document all interesting ideas that I want to pursue scientifically: (they will be organized into blog posts)

  • Inductive bias
  • -> Causality
  • OOD generalization (related to Causality)
  • Separating the world model from the inference machine
    • How does GFlowNet achieve this?
    • “Inference” here is an abstract concept. ML/DL is a method to achieve it but there are others.
  • Modularity and reusability of knowledge
  • Abstraction
  • Uncertainty in world model
  • -> Emergence and complexity
  • Consciousness
  • Multimodal distribution over inference results
  • Stepping as a way to represent arbitrarily rich distributions

Most seeds above come from https://yoshuabengio.org/2023/03/21/scaling-in-the-service-of-reasoning-model-based-ml/

-> GFlowNet is a manifestation of all these ideas.

More seeds

  • Counterfactuals
  • Understanding and Explanations

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