| Title |
A Review of Quantum-Based Diffusion Models in Generative AI / |
| Authors |
Lima, Glauco ; Filatovas, Ernestas ; Marcozzi, Marco ; Paulavičius, Remigijus |
| DOI |
10.15388/LMITT.2025.14 |
| Full Text |
|
| Is Part of |
Lietuvos magistrantų informatikos ir IT tyrimai: konferencijos darbai, 2025 m. gegužės 13 d.. Vilnius : Vilniaus universiteto leidykla. 2025, p. 109-120.. eISSN 2783-784X |
| Keywords [eng] |
quantum machine learning ; quantum diffusion model ; quantum computing ; generative AI |
| Abstract [eng] |
In recent years, the application of generative AI in several areas has been increasing. Concurrently, quantum computing has been advancing at an accelerated pace, unlocking new possibilities across various fields. This article provides an overview of the integration of quantum computing with generative AI, focusing on diffusion model techniques. We explore use cases documented in recent literature, illustrating how quantum computing techniques, when combined with diffusion models, are being leveraged to drive innovation. |
| Published |
Vilnius : Vilniaus universiteto leidykla |
| Type |
Conference paper |
| Language |
English |
| Publication date |
2025 |
| CC license |
|
