4 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.CV2025
Breaking the Likelihood-Quality Trade-off in Diffusion Models by Merging Pretrained Experts
Yasin Esfandiari, Stefan Bauer, Sebastian U. Stich +1
Diffusion models for image generation often exhibit a trade-off between perceptual sample quality and data likelihood: training objectives emphasizing high-noise denoising steps yi…
cs.LG2023★ 4 cited
Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity
Bo Li, Yasin Esfandiari, Mikkel N. Schmidt +2
In federated learning, data heterogeneity is a critical challenge. A straightforward solution is to shuffle the clients' data to homogenize the distribution. However, this may viol…