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Found 2 papers, 1 papers with code
Learning to Evolve on Dynamic Graphs
In this paper, we propose Learning to Evolve on Dynamic Graphs (LEDG) - a novel algorithm that jointly learns graph information and time information.
Realistic Counterfactual Explanations with Learned Relations
Many existing methods of counterfactual explanations ignore the intrinsic relationships between data attributes and thus fail to generate realistic counterfactuals.
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