3 citations · 4 across the 9 of their papers we have counts for
9 papers
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…
Transformers Meet In-Context Learning: A Universal Approximation Theory
Gen Li, Yuchen Jiao, Yu Huang +2
Large language models are capable of in-context learning, the ability to perform new tasks at test time using a handful of input-output examples, without parameter updates. We deve…
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…
Minimax-Optimal Multi-Agent Robust Reinforcement Learning
Yuchen Jiao, Gen Li
Multi-agent robust reinforcement learning, also known as multi-player robust Markov games (RMGs), is a crucial framework for modeling competitive interactions under environmental u…
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…
Compressed Subspace Learning Based on Canonical Angle Preserving Property
Yuchen Jiao, Gen Li, Yuantao Gu
Union of Subspaces (UoS) is a popular model to describe the underlying low-dimensional structure of data. The fine details of UoS structure can be described in terms of canonical a…
Linear Convergence of An Iterative Phase Retrieval Algorithm with Data Reuse
Gen Li, Yuchen Jiao, Yuantao Gu
Phase retrieval has been an attractive but difficult problem rising from physical science, and there has been a gap between state-of-the-art theoretical convergence analyses and th…