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Quantifying the Intrinsic Usefulness of Attributional Explanations for
  Graph Neural Networks with Artificial Simulatability Studies

Quantifying the Intrinsic Usefulness of Attributional Explanations for Graph Neural Networks with Artificial Simulatability Studies

25 May 2023
Jonas Teufel
Luca Torresi
Pascal Friederich
    FAtt
ArXivPDFHTML

Papers citing "Quantifying the Intrinsic Usefulness of Attributional Explanations for Graph Neural Networks with Artificial Simulatability Studies"

1 / 1 papers shown
Title
Towards A Rigorous Science of Interpretable Machine Learning
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
225
3,658
0
28 Feb 2017
1