3 citations · 3 across the 1 of their papers we have counts for
2 papers
cs.LG2022★ 3 cited
OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks
Wanyu Lin, Hao Lan, Hao Wang +1
This paper proposes a new eXplanation framework, called OrphicX, for generating causal explanations for any graph neural networks (GNNs) based on learned latent causal factors. Spe…
cs.LG2021
Generative Causal Explanations for Graph Neural Networks
Wanyu Lin, Hao Lan, Baochun Li
This paper presents Gem, a model-agnostic approach for providing interpretable explanations for any GNNs on various graph learning tasks. Specifically, we formulate the problem of…