https://github.com/laura-rieger/deep-explanation-penalization

Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584
https://github.com/laura-rieger/deep-explanation-penalization

ai artificial-intelligence cdep convolutional-neural-network data-science deep-learning explainability explainable-ai fairness fairness-ml feature-importance interpretability interpretable-deep-learning jupyter-notebook machine-learning ml neural-network python pytorch recurrent-neural-network

Last synced: 3 months ago
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Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584

• Host: GitHub
• URL: https://github.com/laura-rieger/deep-explanation-penalization
• Owner: laura-rieger
• License: mit
• Created: 2019-02-12T21:26:08.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2021-03-22T02:10:12.000Z (almost 4 years ago)
• Last Synced: 2024-08-04T03:08:25.081Z (6 months ago)
• Topics: ai, artificial-intelligence, cdep, convolutional-neural-network, data-science, deep-learning, explainability, explainable-ai, fairness, fairness-ml, feature-importance, interpretability, interpretable-deep-learning, jupyter-notebook, machine-learning, ml, neural-network, python, pytorch, recurrent-neural-network
• Language: Jupyter Notebook
• Homepage:
• Size: 248 MB
• Stars: 124
• Watchers: 9
• Forks: 13
• Open Issues: 1
• Metadata Files:
  • Readme: readme.md
  • License: LICENSE

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