"REFTY: Refinement Types for Valid Deep Learning Models."

Yanjie Gao et al. (2022)

> Home

Details and statistics

DOI: 10.1145/3510003.3510077

access: closed

type: Conference or Workshop Paper

metadata version: 2024-10-18

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/icse/GaoLLZWY22
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/icse/GaoLLZWY22
Yanjie Gao, Zhengxian Li, Haoxiang Lin, Hongyu Zhang, Ming Wu, Mao Yang:
REFTY: Refinement Types for Valid Deep Learning Models. ICSE 2022: 1843-1855

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.