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Context sequence theory: a common explanation for multiple types of learning

arXiv 2208.04707 ↗First posted 17 Jul 2022q-bio.NC cs.AI cs.LGcited by 0

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Abstract (arXiv)

Although principles of neuroscience like reinforcement learning, visual perception and attention have been applied in machine learning models, there is a huge gap between machine learning and mammalian learning. Based on the advances in neuroscience, we propose the context sequence theory to give a common explanation for multiple types of learning in mammals and hope that can provide a new insight into the construct of machine learning models.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 7 references that are in the map. First posted on arXiv 17 Jul 2022.

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References · 1

  1. 2015LSTM: A Search Space Odysseycited by 316

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