2020
Discovering Symbolic Models from Deep Learning with Inductive Biases
NeurIPS 2020poster
We develop a general approach to distill symbolic representations of a learned deep model by introducing strong inductive biases. We focus on Graph Neural Networks (GNNs). The technique works as follows: we first encourage sparse latent representations when we train a GNN in a supervised setting, th…