Item Infomation

Full metadata record
DC FieldValueLanguage
dc.creatorRangamani, Akshay-
dc.creatorXie, Yi-
dc.date2022-07-06T20:10:50Z-
dc.date2022-07-06T20:10:50Z-
dc.date2022-07-06-
dc.identifierhttps://hdl.handle.net/1721.1/143618-
dc.descriptionIn 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.-
dc.descriptionThis material is based upon work supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF-1231216.-
dc.formatapplication/pdf-
dc.publisherCenter for Brains, Minds and Machines (CBMM)-
dc.relationCBMM Memo;137-
dc.titleUnderstanding the Role of Recurrent Connections in Assembly Calculus-
dc.typeArticle-
dc.typeTechnical Report-
dc.typeWorking Paper-
Appears in CollectionsTài liệu ngoại văn

Files in This Item:
Thumbnail
  • CBMM-Memo-137.pdf
      Restricted Access
    • Size : 1,53 MB

    • Format : Adobe PDF