Knowledge graph embeddings based on variational quantum algorithms

Authors

Keywords:

knowledge graphs, embeddings, variational quantum algorithms

Abstract

A hybrid quantum–classical framework is proposed to generate embeddings in knowledge graphs using variational quantum algorithms (VQAs). The model optimizes quantum representations of entities and relations via parameterized circuits, combining quantum processing (state preparation and measurement) with classical optimization. Various quantum circuit architectures are analyzed, establishing a unified framework.

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Published

2025-10-15

How to Cite

Santesteban, M., Bruno, P., Cifuentes, S., Bellomo, G., & Bosyk, G. M. (2025). Knowledge graph embeddings based on variational quantum algorithms. JAIIO, Jornadas Argentinas De Informática, 11(4), 53-57. https://revistas.unlp.edu.ar/JAIIO/article/view/19794