"Enabling High-Quality Uncertainty Quantification in a PIM Designed for ..."

Xingchen Li et al. (2022)

> Home

Details and statistics

DOI: 10.1109/HPCA53966.2022.00080

access: closed

type: Conference or Workshop Paper

metadata version: 2024-10-06

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/hpca/LiWSZYWHNZLZCGS22
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/hpca/LiWSZYWHNZLZCGS22
Xingchen Li, Bingzhe Wu, Guangyu Sun, Zhe Zhang, Zhihang Yuan, Runsheng Wang, Ru Huang, Dimin Niu, Hongzhong Zheng, Zhichao Lu, Liang Zhao, Meng-Fan Marvin Chang, Tianchan Guan, Xin Si:
Enabling High-Quality Uncertainty Quantification in a PIM Designed for Bayesian Neural Network. HPCA 2022: 1043-1055

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.