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Found 3 papers, 1 papers with code
Inferring Inference
Given a time series of neural activity during a perceptual inference task, our framework finds (i) the neural representation of relevant latent variables, (ii) interactions between these variables that define the brain's internal model of the world, and (iii) message-functions specifying the inference algorithm.
Graph schemas as abstractions for transfer learning, inference, and planning
We propose schemas as a model for abstractions that can be used for rapid transfer learning, inference, and planning.
Space is a latent sequence: Structured sequence learning as a unified theory of representation in the hippocampus
Fascinating and puzzling phenomena, such as landmark vector cells, splitter cells, and event-specific representations to name a few, are regularly discovered in the hippocampus.
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