Search Results for author:
Found 2 papers, 2 papers with code
GUIDE: Guidance-based Incremental Learning with Diffusion Models
We introduce GUIDE, a novel continual learning approach that directs diffusion models to rehearse samples at risk of being forgotten.
Adapt & Align: Continual Learning with Generative Models Latent Space Alignment
In this work, we introduce Adapt & Align, a method for continual learning of neural networks by aligning latent representations in generative models.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
