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πŸ”οΈ Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations
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README.md

Summit

Summit is an interactive system that scalably and systematically summarizes and visualizes what features a deep learning model has learned and how those features interact to make predictions.

πŸ”οΈ Live demo: fredhohman.com/summit
πŸ“˜ Paper: https://fredhohman.com/papers/19-summit-vast.pdf
πŸŽ₯ Video: https://youtu.be/J4GMLvoH1ZU
πŸ’» Code: https://github.com/fredhohman/summit
πŸ“Ί Slides: coming October 2019!

Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations
Fred Hohman, Haekyu Park, Caleb Robinson, Duen Horng (Polo) Chau
IEEE Transactions on Visualization and Computer Graphics (TVCG, Proc. VAST'19). 2020.

Summit overview YouTube video

Live Demo

For a live demo, visit: fredhohman.com/summit.

Other Repositories

For the Summit notebook code, Visualization: summit-notebooks.
For the Summit data, visit: summit-data.

Running Locally

Download or clone this repository:

git clone https://github.com/fredhohman/summit.git

Download the data from summit-data:

git clone https://github.com/fredhohman/summit-data.git

Place summit-data's data folder in the top level of the summit repo. Then, within summit run:

npm install
npm run build
npm run start

Requirements

Summit requires npm to run.

License

MIT License. See LICENSE.md.

Citation

@article{hohman2020summit,
  title={Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations},
  author={Hohman, Fred and Park, Haekyu and Robinson, Caleb and Chau, Duen Horng},
  journal={IEEE Transactions on Visualization and Computer Graphics (TVCG)},
  year={2020},
  publisher={IEEE}
  url={https://fredhohman.com/summit/}
}

Contact

For questions or support open an issue or contact Fred Hohman.

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