22 citations · 108 across the 19 of their papers we have counts for
27 papers · 1 filter
Diffusion Models for Adaptive Sequential Data Generation
Haoyang Cao, Minshuo Chen, Yinbin Han +1
Generating realistic synthetic sequential data is critical in real-world applications across operations research, finance, healthcare, energy systems, and scientific computing, whe…
Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data
Hengyu Fu, Zehao Dou, Jiawei Guo +2
Diffusion Transformer, the backbone of Sora for video generation, successfully scales the capacity of diffusion models, pioneering new avenues for high-fidelity sequential data gen…
Provable Statistical Rates for Consistency Diffusion Models
Zehao Dou, Minshuo Chen, Mengdi Wang +1
Diffusion models have revolutionized various application domains, including computer vision and audio generation. Despite the state-of-the-art performance, diffusion models are kno…
An Overview of Diffusion Models: Applications, Guided Generation, Statistical Rates and Optimization
Minshuo Chen, Song Mei, Jianqing Fan +1
Diffusion models, a powerful and universal generative AI technology, have achieved tremendous success in computer vision, audio, reinforcement learning, and computational biology.…
Diffusion Model for Data-Driven Black-Box Optimization
Zihao Li, Hui Yuan, Kaixuan Huang +4
Generative AI has redefined artificial intelligence, enabling the creation of innovative content and customized solutions that drive business practices into a new era of efficiency…
Unveil Conditional Diffusion Models with Classifier-free Guidance: A Sharp Statistical Theory
Hengyu Fu, Zhuoran Yang, Mengdi Wang +1
Conditional diffusion models serve as the foundation of modern image synthesis and find extensive application in fields like computational biology and reinforcement learning. In th…