https://github.com/agrover112/maximal_correlation_weighting
Science Score: 10.0%
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○CITATION.cff file
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✓Committers with academic emails
1 of 4 committers (25.0%) from academic institutions -
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○Scientific vocabulary similarity
Low similarity (4.7%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: Agrover112
- License: mit
- Language: Python
- Default Branch: master
- Size: 45.5 MB
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- Stars: 0
- Watchers: 0
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Metadata Files
README.md
maximalcorrelationweighting
This is the code for the Maximal Correlation Weighting algorithm.
Note: code for downloading and preparing the Dogs and Tiny ImageNet datasets is not yet available. The preprocessed Cifar-100 dataset files are already included in the "datasets" folder. For the Stanford Dogs and Tiny ImageNet datasets, is suffices to download the datasets and unzip them into the folder labeled "datasets" in the main directory.
nets.py contains the LeNet architecture used for the experiments
datasets.py contains the dataloaders for the datasets
main.py contains the main code for the MCW method. To use, change "mode" on line 4 to the appropriate dataset, and change the number of source samples in line 5 as needed.
PS: Move datasets and save_models outside/ this folder onto the main path
Owner
- Login: Agrover112
- Kind: user
- Repositories: 113
- Profile: https://github.com/Agrover112
Humans trying to understand machines and people.
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| Name | Commits | |
|---|---|---|
| agrover112 | a****2@g****m | 4 |
| Agrover112 | 4****2 | 4 |
| Joshua Lee | j****e@m****u | 1 |
| jklee-mit | 5****t | 1 |
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