9 items found

Tags: Explainability

Filter Results
  • JournalArticle

    Machine Learning Explainability Via Microaggregation and Shallow Decision Trees

    Artificial intelligence (AI) is being deployed in missions that are increasingly critical for human life. To build trust in AI and avoid an algorithm-based authoritarian...
    • BibTeX
      The resource: 'BibTeX' is not accessible as guest user. You must login to access it!
    • HTML
      The resource: 'html' is not accessible as guest user. You must login to access it!
  • JournalArticle

    Explanation in artificial intelligence. Insights from the social sciences

    There has been a recent resurgence in the area of explainable artificial intelligence as researchers and practitioners seek to provide more transparency to their algorithms....
    • HTML
      The resource: 'html' is not accessible as guest user. You must login to access it!
    • BibTeX
      The resource: 'BibTeX' is not accessible as guest user. You must login to access it!
  • ConferencePaper

    Predicting and Explaining Privacy Risk Exposure in Mobility Data

    Mobility data is a proxy of different social dynamics and its analysis enables a wide range of user services. Unfortunately, mobility data are very sensitive because the...
  • Method

    GLocalX - Explaining in a Local to Global setting

    GLocalX is a model-agnostic Local to Global explanation algorithm. Given a set of local explanations expressed in the form of decision rules, and a black-box model to explain,...
    • GitHub
      The resource: 'Github page' is not accessible as guest user. You must login to access it!
    • HTML
      The resource: 'Journal article item' is not accessible as guest user. You must login to access it!
  • Method

    XAI Method for explaining time-series

    LASTS is a framework that can explain the decisions of black box models for time series classification. The explanation consists of factual and counterfactual rules revealing...
  • Method

    TriplEx - Explaining with Triples

    TRIPLEX is an explainability package for Transformer-based models fine-tuned on Natural Language Inference, Semantic Text Similarity, or Text Classification tasks. TRIPLEX...
  • BookChapter

    Machine Learning Explainability Through Comprehensible Decision Trees

    The role of decisions made by machine learning algorithms in our lives is ever increasing. In reaction to this phenomenon, the European General Data Protection Regulation...
    • BibTeX
      The resource: 'BibTeX' is not accessible as guest user. You must login to access it!
    • HTML
      The resource: 'html' is not accessible as guest user. You must login to access it!
  • Method

    GLocalX-C

    A Python library to explain machine learning models by hierarchically aggregating single explanations of its predictions. Explanations are provided as decision rules...
  • JournalArticle

    Explaining misclassification and attacks in deep learning via random forests

    Artificial intelligence, and machine learning (ML) in particular, is being used for different purposes that are critical for human life. To avoid an algorithm-based...
    • PDF
      The resource: 'Link to Publication' is not accessible as guest user. You must login to access it!
You can also access this registry using the API (see API Docs).