https://github.com/fredhohman/visual-analytics-in-deep-learning

IEEE TVCG Visual Analytics in Deep Learning Survey
https://github.com/fredhohman/visual-analytics-in-deep-learning

data-visualization deep-learning interpretability machine-learning neural-network survey visual-analytics

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IEEE TVCG Visual Analytics in Deep Learning Survey

• Host: GitHub
• URL: https://github.com/fredhohman/visual-analytics-in-deep-learning
• Owner: fredhohman
• License: mit
• Created: 2018-04-23T18:23:53.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2021-02-11T19:49:20.000Z (over 3 years ago)
• Last Synced: 2023-05-05T21:31:02.275Z (over 1 year ago)
• Topics: data-visualization, deep-learning, interpretability, machine-learning, neural-network, survey, visual-analytics
• Language: CSS
• Homepage: https://fredhohman.com/visual-analytics-in-deep-learning
• Size: 7.25 MB
• Stars: 14
• Watchers: 5
• Forks: 6
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

Awesome Lists containing this project

README

        
# Visual Analytics in Deep Learning

*An Interrogative Survey for the Next Frontiers*

This is the repository for the website of the TVCG 2018 survey paper on visual analytics in deep learning, presented at IEEE VIS 2018. 

**[Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers][site]**  

[Fred Hohman][fred], [Minsuk Kahng][minsuk], [Robert Pienta][robert], [Duen Horng Chau][polo].  

*IEEE Transactions on Visualization and Computer Graphics (TVCG). 2018.*  

## Add a new work

To add a new work to the table:

* Fork this repository.

* Edit the data file [`_data/works.yml`][works] by appending a new work to the very bottom of the file.

Use the following work as a template for adding the new work:

```yaml

- paper: kahng2018activis                  # lastname2018keyword

  url: http://minsuk.com/research/activis/ # project or paper link

  author: Kahng, et al.                    # abbreviated author list

  year: 2018                               # publication year

  # mark an `x` if a work belongs to a category and `o` if it doesn't

  why:

    - interpretability: x

      debugging: x

      comparing: o

      education: o

  who: 

    - model-developers: x

      model-users: x

      non-experts: o

  what:

    - graph: x

      learned: o

      units: x

      neurons: x

      aggregated: x

      node-link: x

  how: 

    - scatter: x

      line: o

      instance-based: x

      interactive-experimentation: o

      algorithms: o

  when:

    - during: o

      after: x

  where:

    - venue: TVCG                          # abbreviated publication venue

```

* Submit a [pull request][pull] with the newly added work.

## BibTeX

```latex

@article{hohman2018visual,

  title={Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers},

  author={Hohman, Fred and Kahng, Minsuk and Pienta, Robert and Chau, Duen Horng},

  journal={IEEE Transactions on Visualization and Computer Graphics},

  year={2018},

  publisher={IEEE}

}

```

## Credits

[Jekyll theme](http://www.pixyll.com) by [John Otander](http://johnotander.com).

[site]: https://fredhohman.com/visual-analytics-in-deep-learning

[fred]: https://fredhohman.com "Fred Hohman."

[minsuk]: http://minsuk.com/ "Minsuk Kahng."

[robert]: http://spicy.bike/ "Robert Pienta."

[polo]: https://www.cc.gatech.edu/~dchau/ "Polo Chau."

[works]: https://github.com/fredhohman/visual-analytics-in-deep-learning/blob/master/_data/works.yml "Works."

[pull]: https://github.com/fredhohman/visual-analytics-in-deep-learning/pulls "Make a new pull request."