BibSonomy

The blue social bookmark and publication sharing system.

( en | de | ru )

 

group
  • tag
  • user
  • group
  • author
  • concept
  • BibTeX key
  • search
test_group
  • sign in
  • register
  • groups
  • genealogy
  • popular 
    • posts
    • tags
    • authors
    • concepts
    • discussions
  • sign in
  • register

Login

Log in with your username.

@

I've lost my password.


Log in with your OpenID-Provider.

  • Other OpenID-Provider
  1. group
  2. test_group
  3. interpretation interpretability

Publication title

bookmarks  (hide)1
  • display
  • all
  • bookmarks only
  • bookmarks per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • sort by
  • added at
  • title
  • RSS
  • BibTeX
  • XML

  •  

     
    2slundberg/shap: A unified approach to explain the output of any machine learning model.
     

    https://github.com/slundberg/shap
    7 years ago by @becker
    show all tags
    • code
    • implementation
    • python
    • explainability
    • neural
    • learning
    • explainable
    • network
    • shaply
    • shap
    • machine
    • interpretability
    • interpretation
    • ml
    • nn
     
      codeimplementationpythonexplainabilityneurallearningexplainablenetworkshaplyshapmachineinterpretabilityinterpretationmlnn
      copydelete
      • community post
      • history of this post
       
       
    • ⟨⟨
    • ⟨
    • 1
    • ⟩
    • ⟩⟩

    publications  (hide)2  
    • display
    • all
    • publications only
    • publications per page
    • 5
    • 10
    • 20
    • 50
    • 100
    • sort by
    • added at
    • title
    • author
    • publication date
    • entry type
    • help for advanced sorting...
    • RSS
    • BibTeX
    • RDF
    • more...

    •  

       
      3Improving Interpretability of Deep Neural Networks with Semantic Information
       

      Y. Dong, H. Su, J. Zhu, and B. Zhang. arXiv preprint arXiv:1703.04096, (2017)
      8 years ago by @becker
      show all tags
      • toread
      • neural
      • citedby:scholar:count:3
      • citedby:scholar:timestamp:2017-10-13
      • interpretability
      • interpretation
      • semantics
      • network
      • information
      • nn
       
        toreadneuralcitedby:scholar:count:3citedby:scholar:timestamp:2017-10-13interpretabilityinterpretationsemanticsnetworkinformationnn
        copydeleteadd this publication to your clipboard
        • community post
        • history of this post
        • URL
        • DOI
        • BibTeX
        • EndNote
        • APA
        • Chicago
        • DIN 1505
        • Harvard
        • MSOffice XML
         
         
      •  

         
        1Proceedings of the 2016 ICML Workshop on Human Interpretability in Machine Learning (WHI 2016)
         

        B. Kim, D. Malioutov, and K. Varshney. (2016)cite arxiv:1607.02531.
        8 years ago by @becker
        show all tags
        • bmbf
        • neural
        • pv
        • interpretability
        • interpretation
        • networks
         
          bmbfneuralpvinterpretabilityinterpretationnetworks
          copydeleteadd this publication to your clipboard
          • community post
          • history of this post
          • URL
          • DOI
          • BibTeX
          • EndNote
          • APA
          • Chicago
          • DIN 1505
          • Harvard
          • MSOffice XML
           
           
        • ⟨⟨
        • ⟨
        • 1
        • ⟩
        • ⟩⟩

        test_group

        @test_group

        Testing group for various plug-in development projects

        CVexplore
        join

        browse

        • interpretation interpretability as tag from all users

        related tags

        • + | neural
        • + | network
        • + | nn
        • + | bmbf
        • + | toread
        • + | pv
        • + | citedby:scholar:count:3
        • + | citedby:scholar:timestamp:2017-10-13
        • + | semantics
        • + | networks
        • + | information
        • + | python
        • + | code
        • + | explainability
        • + | implementation
        • + | learning
        • + | explainable
        • + | shap
        • + | shaply
        • + | machine

        tags

        • inthesis
        • diss
        • spatial
        • geo
        • mobility
        • mining
        • web
        • pattern
        • navigation
        • uw_ws17_ml
        • human
        • markov
        • citedby:scholar:timestamp:2017-9-29
        • data
        • twitter
        • citedby:scholar:timestamp:2017-4-20
        • imported
        • noise
        • dataset
        • widenoise
        • subgroup
        • chain
        • recommendation
        • thema
        • model
        • network
        • R
        • spring
        • wikipedia
        • access
        • flickr
        • folktrails
        • semantics
        • weather
        • analysis
        • sound
        • meter
        • pressure
        • android
        • everyaware
        • predicition
        • information
        • sequential
        • imported-verified
        • semantic
        • activity
        • microtrails
        • map
        • comparison
        What is BibSonomy?
        Getting Started
        Browser Buttons
        Help
        Developer
        Overview
        API Documentation
        Contact & Privacy
        Contact
        Privacy & Terms of Use
        Cookies
        Report Issues
        BibSonomy Wiki
        Integration
        PUMA
        TYPO3 Extension
        WordPress Plugin
        Java REST Client
        Supported Sites
        more
        About BibSonomy
        Team
        Blog
        Mailing List
        Social Media
         Follow us on Twitter

        BibSonomy is offered by the Data Science Chair of the University of Würzburg, the Information Processing and Analytics Group of the Humboldt-Unversität zu Berlin, the KDE Group of the University of Kassel, and the L3S Research Center.