Introducing MLOps: How to go from Model to Production, Mark Treveil, Nicolas Omont, Aurélien Géron, et al., 2020 (O'Reilly Media) - This comprehensive book covers the MLOps lifecycle, offering a foundation for understanding principles relevant to adapting for diffusion models.
MLflow Documentation: Model Registry, The MLflow Project, 2023 - Official documentation detailing how to version, manage, and track the lifecycle of machine learning models within a model registry, essential for diffusion model checkpoints and reproducibility.
Diffusion Models: A Comprehensive Survey of Methods and Applications, Ling Yang, Zhilong Zhang, Yang Song, Shenda Hong, Runsheng Xu, Yue Zhao, Wentao Zhang, Bin Cui, Ming-Hsuan Yang, 2022ACM Computing Surveys (ACM)DOI: 10.48550/arXiv.2209.00796 - This academic survey reviews diffusion models, including an examination of evaluation metrics and challenges, directly informing quality monitoring in MLOps for these models.