50 items found

Groups: Social Impact of AI and explainable ML

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  • 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
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    • HTML
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  • 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

    LORE

    The recent years have witnessed the rise of accurate but obscure decision systems which hide the logic of their internal decision processes to the users. The lack of...
    • python
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  • Method

    MARLENA

    MARLENA is novel technique able to explain the reasons behind any black-box multi-label classifier decision. It will generate an explanation in the form of a decision rule....
    • python
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  • 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...
  • Method

    Reducing Graph Structural Bias by Adding shortcut edges

    Algorithms that tackle the problem of minimizing average/maximum hitting time (BMAH/BMMH) between different social network groups, given fixed shortcut edges. The...
    • Data
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  • Method

    Geolet

    Geolet is a Python library that offers an interpretable transformation and classification approach for trajectory data. Geolet first partitions trajectories into multiple...
  • Method

    Visualizing the Results of Biclustering and Boolean Matrix Factorization Algo...

    This archive contains the code to visualize biclusters from the paper "Visualizing Overlapping Biclusterings and Boolean Matrix Factorizations" by Thibault Marette, Pauli...
  • Dataset

    Interaction bias. Experiments dataset

    Artificial Intelligence (AI) is increasingly used to build Decision Support Systems (DSS) across many domains. In our work, we conducted a series of experiments designed to...
    • JSON
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  • 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...
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