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Found 2 papers, 2 papers with code
Augment to Interpret: Unsupervised and Inherently Interpretable Graph Embeddings
Unsupervised learning allows us to leverage unlabelled data, which has become abundantly available, and to create embeddings that are usable on a variety of downstream tasks.
Calibrate to Interpret
In this paper we show a first link between uncertainty and explainability, by studying the relation between calibration and interpretation.
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