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dc.contributor.authorRangamani, Akshay
dc.contributor.authorXie, Yi
dc.date.accessioned2022-07-06T20:10:50Z
dc.date.available2022-07-06T20:10:50Z
dc.date.issued2022-07-06
dc.identifier.urihttps://hdl.handle.net/1721.1/143618
dc.description.abstractIn this note, we explore the role of recurrent connections in Assembly Calculus through a number of experiments conducted on models with and without recurrent connections. We observe that as- semblies can be formed even in the absence of recurrent connections, but also find that models with recurrent connections are more robust to noisy inputs. We also investigate the spectral structure of the synaptic weights and find intriguing similarities between models of neural assemblies and associative memories.en_US
dc.description.sponsorshipThis material is based upon work supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF-1231216.en_US
dc.publisherCenter for Brains, Minds and Machines (CBMM)en_US
dc.relation.ispartofseriesCBMM Memo;137
dc.titleUnderstanding the Role of Recurrent Connections in Assembly Calculusen_US
dc.typeArticleen_US
dc.typeTechnical Reporten_US
dc.typeWorking Paperen_US


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