3 citations · 4 across the 9 of their papers we have counts for
5 papers · 1 filter
Towards a unified framework for guided diffusion models
Yuchen Jiao, Yuxin Chen, Gen Li
Guided or controlled data generation with diffusion models\blfootnote{Partial preliminary results of this work appeared in International Conference on Machine Learning 2025 \citep{…
Optimal Convergence Analysis of DDPM for General Distributions
Yuchen Jiao, Yuchen Zhou, Gen Li
Score-based diffusion models have achieved remarkable empirical success in generating high-quality samples from target data distributions. Among them, the Denoising Diffusion Proba…
Connections between reinforcement learning with feedback,test-time scaling, and diffusion guidance: An anthology
Yuchen Jiao, Yuxin Chen, Gen Li
In this note, we reflect on several fundamental connections among widely used post-training techniques. We clarify some intimate connections and equivalences between reinforcement…
Provable Efficiency of Guidance in Diffusion Models for General Data Distribution
Gen Li, Yuchen Jiao
Diffusion models have emerged as a powerful framework for generative modeling, with guidance techniques playing a crucial role in enhancing sample quality. Despite their empirical…
Instance-dependent Convergence Theory for Diffusion Models
Yuchen Jiao, Gen Li
Score-based diffusion models have demonstrated outstanding empirical performance in machine learning and artificial intelligence, particularly in generating high-quality new sample…