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

arXiv: https://arxiv.org/abs/2208.04707 · HTML: https://mlsanity.com/paper/2208.04707/

## 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.

## Builds on (most cited first, 1 of 1)

- [LSTM: A Search Space Odyssey](https://mlsanity.com/paper/1503.04069/) (2015)

## 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.