"A scalable implementation of the recursive least-squares algorithm for ..."

Arthur J. Benjamin et al. (2023)

> Home

Details and statistics

DOI: 10.3389/FNINF.2023.1099510

access: open

type: Journal Article

metadata version: 2023-08-16

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - journals/fini/BenjaminKCPD23
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/fini/BenjaminKCPD23
Arthur J. Benjamin, Christopher M. Kim, Susu Chen, Stephan Preibisch, Ran Darshan:
A scalable implementation of the recursive least-squares algorithm for training spiking neural networks. Frontiers Neuroinformatics 17 (2023)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.