{"type":"ScholarlyArticle","title":"Inductive Knowledge Graph Wave Networks","authors":[{"name":"Giuseppe Pirrò","slug":"giuseppe-pirro","given":"Giuseppe","family":"Pirrò","affiliation":""}],"abstract":"Inductive knowledge graph reasoning (IKGR) requires generalization to entities and relation types not seen during training. We introduce Knowledge Graph Wave Networks (KGWN), an IKGR approach that learns adaptive per-relation wave operators to control relation-dependent propagation, along with velocity normalization ensuring stability at any propagation depth. Experiments demonstrate state-of-the-art results on inductive benchmarks and competitive transductive performance.","doi":"10.24963/ijcai.2026/329","url":"https://ijcai.org/proceedings/2026/329","pdf":"https://ijcai.org/proceedings/2026/0329.pdf","markdown":"https://ijcai.org/proceedings/2026/329.md","bibtex":"https://ijcai.org/proceedings/2026/bibtex/329","volume":{"slug":"2026","title":"Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2026","url":"https://ijcai.org/proceedings/2026/","year":2026,"location":"Bremen, Germany","dates":"15-21 August 2026","editors":"Diego Calvanese","isbn":"978-1-956792-09-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2026"},"section":"Data Mining","track":"Main Track","number":329,"pages":{"first":2960,"last":2968},"keywords":["Machine Learning: Representation learning","Data Mining: Knowledge graphs and knowledge base completion","Knowledge Representation and Reasoning: Semantic Web"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}