https://github.com/chenchengliang/suprise-adequacy-implementation
https://github.com/chenchengliang/suprise-adequacy-implementation
Science Score: 10.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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○DOI references
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✓Academic publication links
Links to: arxiv.org -
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (3.5%) to scientific vocabulary
Last synced: 10 months ago
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Repository
Basic Info
- Host: GitHub
- Owner: ChenchengLiang
- Language: Python
- Default Branch: master
- Size: 19.5 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Created over 7 years ago
· Last pushed over 7 years ago
https://github.com/ChenchengLiang/Suprise-Adequacy-Implementation/blob/master/
Implementation of Guilding Deep Learning System Testing Using Suprise Adequacy https://arxiv.org/abs/1808.08444 In folder TEST, LSA,DSAand SC can be run in a very small dataset of MNIST (100 training data and one new input). In folder SA, I will try to modulize the codes and expand one new input to multiple new input. TO DO: SA/LSA.py Fix the glitch when compute KDE in TEST/MNIST-LSA-TEST.py
Owner
- Name: Chencehng Liang
- Login: ChenchengLiang
- Kind: user
- Location: Sweden
- Company: Uppsala University
- Repositories: 4
- Profile: https://github.com/ChenchengLiang
PhD student in Uppsala University