Hybrid Quantum-Classical Style Transfer (Student Abstract)

Authors

  • Emily Jimin Roh Korea University
  • Joo Yong Shim Korea University
  • Soohyun Park Sookmyung Women's University
  • Joongheon Kim Korea University

DOI:

https://doi.org/10.1609/aaai.v39i28.35295

Abstract

This paper proposes a novel quantum style transfer (QST) in hybrid quantum-classical computing. QST leverages quantum computing's ability to process high-dimensional data efficiently. Our approach aims to decrease both inference time and complexity while maintaining performance, presenting a viable solution that enhances the scalability and efficiency of image generation technologies.
AAAI-25 / IAAI-25 / EAAI-25 Proceedings Cover

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Published

2025-04-11

How to Cite

Roh, E. J., Shim, J. Y., Park, S., & Kim, J. (2025). Hybrid Quantum-Classical Style Transfer (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 39(28), 29480–29481. https://doi.org/10.1609/aaai.v39i28.35295

Issue

Vol. 39 No. 28: IAAI-25, EAAI-25, AAAI-25 Student Abstracts, Undergraduate Consortium and Demonstrations

Section

AAAI Student Abstract and Poster Program