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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.
Beyond imitation: Zero-shot task transfer on robots by learning concepts as cognitive programs
Humans can infer concepts from image pairs and apply those in the physical world in a completely different setting, enabling tasks like IKEA assembly from diagrams.
Cortical Microcircuits from a Generative Vision Model
Understanding the information processing roles of cortical circuits is an outstanding problem in neuroscience and artificial intelligence.
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