2 papers
cs.LG2025
Elastic Weight Consolidation for Knowledge Graph Continual Learning: An Empirical Evaluation
Gaganpreet Jhajj, Fuhua Lin
Knowledge graphs (KGs) require continual updates as new information emerges, but neural embedding models suffer from catastrophic forgetting when learning new tasks sequentially. W…
cs.AI2025
Graph Distance as Surprise: Free Energy Minimization in Knowledge Graph Reasoning
Gaganpreet Jhajj, Fuhua Lin
In this work, we propose that reasoning in knowledge graph (KG) networks can be guided by surprise minimization. Entities that are close in graph distance will have lower surprise…