PyKEEN-NSX: A Modular Framework for Static, Dynamic and Schema-Aware Negative Sampling in PyKEEN
The episode discusses a paper introducing PyKEEN-NSX, a modular framework for negative sampling in Knowledge Graph Embedding (KGE) models. The hosts explain how this framework allows researchers to implement static, dynamic, and schema-aware sampling strategies. It provides fine-grained control over data selection to improve AI performance.