Nicole and I discuss how a signature for visual memory can be coded among the same population of neurons known to encode object identity, how the same coding scheme arises in convolutional neural networks trained to identify objects, and how neuroscience and machine learning (reinforcement learning) can join forces to understand how curiosity and novelty drive efficient learning.
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Jay's homepage at Stanford.Implementing mathematical reasoning in machines:The video lecture.The paper.Parallel Distributed Processing by Rumelhart and McClelland.Complimentary Learning Systems Theory and Its Recent Update.Episode...
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