https://github.com/yeonghyeon/active-learning

PyTorch implementation of "Learning Loss for Active Learning"
https://github.com/yeonghyeon/active-learning

active-learning cifar10 cifar10-classification mnist-classification mnist-dataset pytorch-implementation

Last synced: 7 months ago
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PyTorch implementation of "Learning Loss for Active Learning"

• Host: GitHub
• URL: https://github.com/yeonghyeon/active-learning
• Owner: YeongHyeon
• License: mit
• Created: 2023-12-20T09:31:06.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2023-12-22T02:39:22.000Z (almost 2 years ago)
• Last Synced: 2025-01-08T18:54:25.751Z (9 months ago)
• Topics: active-learning, cifar10, cifar10-classification, mnist-classification, mnist-dataset, pytorch-implementation
• Language: Python
• Homepage:
• Size: 338 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
[PyTorch] Learning Loss for Active Learning

=====

PyTorch implementation of "Learning Loss for Active Learning"

## Concept



      

  
Concept ot the Active Learning [1].



## Results

|MNIST|CIFAR10|

|:---:|:---:|

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## Requirements

* PyTorch 2.0.1

## Reference

[1] Donggeun Yoo, et al. "Learning loss for active learning."  Proceedings of the IEEE/CVF conference on Computer Vision and Pattern Recognition (CVPR). 2019.