2 citations · 3 across the 7 of their papers we have counts for
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stat.ML2025
Computationally efficient goodness-of-fit tests through kernelized Stein discrepancy
Zhihan Huang, Ziang Niu
Models with intractable normalizing constants are widely used in statistics and machine learning. Assessing the adequacy of such models poses significant challenges: obtaining samp…
stat.ML2025
Low-dimensional adaptation of diffusion models: Convergence in total variation
Jiadong Liang, Zhihan Huang, Yuxin Chen
This paper investigates how diffusion generative models leverage (unknown) low-dimensional structure to accelerate sampling. Focusing on two mainstream samplers -- the denoising di…
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…