{"id":"arxiv:2112.04035","title":"Relating transformers to models and neural representations of the hippocampal formation","date":"2021-12-07","section":"NeuroAI","quality":0.004184,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/","source_url":"https://arxiv.org/abs/2112.04035","text_available":true,"authors":["James C. R. Whittington","Joseph Warren","Timothy E. J. Behrens"],"outgoing":[],"incoming":[],"text_parts":[{"start":0,"end":15846,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-1.html"},{"start":15846,"end":31289,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-2.html"},{"start":31289,"end":46966,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-3.html"},{"start":46966,"end":54700,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-4.html"}],"contents":[{"title":"Relating transformers to models and neural representations of the hippocampal formation","offset":0,"level":1,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-1.html#text"},{"title":"Abstract","offset":91,"level":6,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-1.html#text"},{"title":"1 Introduction","offset":1122,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-1.html#text"},{"title":"2 Transformers","offset":4365,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-1.html#text"},{"title":"3 Transformers learn entorhinal representations","offset":8903,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-1.html#text"},{"title":"4 TEM","offset":14504,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-1.html#text"},{"title":"5 TEM as a transformer","offset":18747,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-2.html#text"},{"title":"6 Place cells in transformers","offset":24989,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-2.html#text"},{"title":"7 Discussion","offset":30245,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-2.html#text"},{"title":"8 Conclusion","offset":34258,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-3.html#text"},{"title":"Appendix A Appendix","offset":34879,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-3.html#text"},{"title":"A.1 The maths using elements","offset":34903,"level":3,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-3.html#text"},{"title":"A.2 Details of implementation","offset":38196,"level":3,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-3.html#text"},{"title":"A.3 Additional details of the spatial task","offset":45474,"level":3,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-3.html#text"},{"title":"A.4 Additional details of TEM","offset":48128,"level":3,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-4.html#text"},{"title":"A.5 Related work","offset":50563,"level":3,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-4.html#text"},{"title":"A.6 Further learned cell representations","offset":53690,"level":3,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-4.html#text"},{"title":"Instructions for reporting errors","offset":53736,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/part-4.html#text"}],"text_code_points":54700,"source_markdown":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bfa03c56afb2b9dcd29555345740d1383a9cbeb8cef0af5139256e398066fb47/source.md"}