H-CMR is a concept-based classifier whose concept and task predictions are made by attention-selected logic rules over a learned acyclic concept graph.
Towards robust interpretability with self-explaining neural networks.Advances in neural information processing systems, 31, 2018
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Interpretable Hierarchical Concept Reasoning through Attention-Guided Graph Learning
H-CMR is a concept-based classifier whose concept and task predictions are made by attention-selected logic rules over a learned acyclic concept graph.