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IEEE TVCG Visual Analytics in Deep Learning Survey

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

License: MIT License

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

visual-analytics-in-deep-learning's Introduction

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
Fred Hohman, Minsuk Kahng, Robert Pienta, Duen Horng Chau.
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 by appending a new work to the very bottom of the file. Use the following work as a template for adding the new work:
- 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

BibTeX

@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 by John Otander.

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