YangLing0818/Diffusion-Models-Papers-Survey-Taxonomy
A categorized collection of academic papers and survey on diffusion generative models, covering algorithms, sampling methods, and applications across vision, NLP, and temporal data.

This repository aggregates and taxonomizes research papers on diffusion models, structured around a published ACM Computing Surveys survey paper. It organizes the literature across algorithm improvements such as sampling acceleration, likelihood maximization, and multimodel integration with LLMs, as well as application domains including image synthesis, video generation, 3D generation, semantic segmentation, and time-series modeling.