5 citations · 9 across the 12 of their papers we have counts for
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stat.ML2024
Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models
Yuchen Wu, Yuxin Chen, Yuting Wei
Diffusion models play a pivotal role in contemporary generative modeling, claiming state-of-the-art performance across various domains. Despite their superior sample quality, mains…
stat.ML2024★ 1 cited
Statistical Inference for Policy Evaluation with Temporal Difference Learning
Weichen Wu, Gen Li, Yuting Wei +1
We investigate the statistical properties of Temporal Difference (TD) learning with Polyak-Ruppert averaging, arguably one of the most widely used algorithms in reinforcement learn…
stat.ML2024★ 1 cited
Towards a mathematical theory for consistency training in diffusion models
Gen Li, Zhihan Huang, Yuting Wei
Consistency models, which were proposed to mitigate the high computational overhead during the sampling phase of diffusion models, facilitate single-step sampling while attaining s…