Denoising Diffusion Probabilistic Models, Jonathan Ho, Ajay Jain, Pieter Abbeel, 2020Advances in Neural Information Processing Systems (NeurIPS)DOI: 10.48550/arXiv.2006.11239 - The original paper introducing Denoising Diffusion Probabilistic Models, describing the foundational iterative sampling process.
Denoising Diffusion Implicit Models, Jiaming Song, Chenlin Meng, Stefano Ermon, 2020International Conference on Learning Representations (ICLR)DOI: 10.48550/arXiv.2010.02502 - Introduces a deterministic sampling method by reframing the generative process as solving an ODE, enabling faster inference with fewer steps.