Deep graph representation learning

A system comprising:

• a memory;
• and
• a processing device, operatively coupled to the memory, to:
• calculate a plurality of base features from a graph;
• add the plurality of base features to a feature matrix;
• (i) generate a current feature layer from the feature matrix and a set of relational feature operators, wherein the current feature layer corresponds to a set of current features;
• (ii) evaluate feature pairs associated with the current feature layer;
• (iii) select a subset of features from the set of current features based on the evaluated feature pairs;
• and
• (iv) add the subset of features to the feature matrix to generate an updated feature matrix.

A non-transitory computer-readable storage medium having instructions stored thereon that, when executed by a processing device, cause the processing device to:

• calculate a plurality of base features from a graph;
• add the plurality of base features to a feature matrix;
• (i) generate, by the processing device, a current feature layer from the feature matrix and a set of relational feature operators, wherein the current feature layer corresponds to a set of current features;
• (ii) evaluate feature pairs associated with the current feature layer;
• (iii) select a subset of features from the set of current features based on the evaluated feature pairs;
• and
• (iv) add the subset of features to the feature matrix to generate an updated feature matrix.