1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2024★ 1 cited
Quantum Diffusion Models for Few-Shot Learning
Ruhan Wang, Ye Wang, Jing Liu +1
Modern quantum machine learning (QML) methods involve the variational optimization of parameterized quantum circuits on training datasets, followed by predictions on testing datase…
cs.CV2024★ 1 cited
Diffusion Feedback Helps CLIP See Better
Wenxuan Wang, Quan Sun, Fan Zhang +3
Contrastive Language-Image Pre-training (CLIP), which excels at abstracting open-world representations across domains and modalities, has become a foundation for a variety of visio…
cs.LG2024
Efficient Differentially Private Fine-Tuning of Diffusion Models
Jing Liu, Andrew Lowy, Toshiaki Koike-Akino +2
The recent developments of Diffusion Models (DMs) enable generation of astonishingly high-quality synthetic samples. Recent work showed that the synthetic samples generated by the…