Conor Heins
publications / projects
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Projects
  • AXIOM
    Object-centric world models that learn to play games in minutes by expanding their structure online.
  • CAVI-CMN: Gradient-Free Variational Learning
    Closed-form coordinate-ascent variational inference for conditional mixture networks — fast, exact updates, no gradients.
  • Collective Behavior from Surprise Minimization
    The first active inference model of collective motion — surprise-minimizing agents reproduce real-world flocking patterns.
  • pymdp
    A Python library for active inference in discrete state-spaces. 680+ GitHub stars.
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