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cs.LG2024
CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion
Joshua Kazdan, Hao Sun, Jiaqi Han +2
Diffusion models have a tendency to exactly replicate their training data, especially when trained on small datasets. Most prior work has sought to mitigate this problem by imposin…
cs.CV2024★ 1 cited
On the Scalability of Diffusion-based Text-to-Image Generation
Hao Li, Yang Zou, Ying Wang +7
Scaling up model and data size has been quite successful for the evolution of LLMs. However, the scaling law for the diffusion based text-to-image (T2I) models is not fully explore…
cs.LG2024
Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution
Tailin Wu, Willie Neiswanger, Hongtao Zheng +2
Deep learning-based surrogate models have demonstrated remarkable advantages over classical solvers in terms of speed, often achieving speedups of 10 to 1000 times over traditional…