"Scalable Bayesian GPFA with automatic relevance determination and discrete ..."

Kristopher T. Jensen et al. (2021)

> Home

Details and statistics

DOI: —

access: open

type: Conference or Workshop Paper

metadata version: 2022-05-03

- view
  - electronic edition @ neurips.cc (open access)
- export record
  dblp key:
  - conf/nips/JensenKSH21
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/nips/JensenKSH21
Kristopher T. Jensen, Ta-Chu Kao, Jasmine Stone, Guillaume Hennequin:
Scalable Bayesian GPFA with automatic relevance determination and discrete noise models. NeurIPS 2021: 10613-10626

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.