1. Denoising diffusion probabilistic models
    Ho, Jonathan and Jain, Ajay and Abbeel, Pieter
    Advances in neural information processing systems, 2020

  2. Deep unsupervised learning using nonequilibrium thermodynamics
    Sohl-Dickstein, Jascha and Weiss, Eric and Maheswaranathan, Niru and Ganguli, Surya
    International conference on machine learning, 2015

  3. Generative Modeling by Estimating Gradients of the Data Distribution
    Song, Yang
    https://yang-song.net/blog/2021/score/

  4. Improved techniques for training score-based generative models
    Song, Yang and Ermon, Stefano
    Advances in neural information processing systems, 2020

  5. Score-based generative modeling through stochastic differential equations
    Song, Yang and Sohl-Dickstein, Jascha and Kingma, Diederik P and Kumar, Abhishek and Ermon, Stefano and Poole, Ben
    arXiv preprint arXiv:2011.13456, 2020

  6. Diffusion models: A comprehensive survey of methods and applications
    Yang, Ling and Zhang, Zhilong and Song, Yang and Hong, Shenda and Xu, Runsheng and Zhao, Yue and Zhang, Wentao and Cui, Bin and Yang, Ming-Hsuan
    ACM Computing Surveys, 2023

  7. Diffusion models in vision: A survey
    Croitoru, Florinel-Alin and Hondru, Vlad and Ionescu, Radu Tudor and Shah, Mubarak
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023

  8. Simple diffusion: End-to-end diffusion for high resolution images
    Hoogeboom, Emiel and Heek, Jonathan and Salimans, Tim
    International Conference on Machine Learning, 2023

  9. On the importance of noise scheduling for diffusion models
    Chen, Ting
    arXiv preprint arXiv:2301.10972, 2023

  10. Elucidating the design space of diffusion-based generative models
    Karras, Tero and Aittala, Miika and Aila, Timo and Laine, Samuli
    Advances in Neural Information Processing Systems, 2022

  11. Denoising diffusion implicit models
    Song, Jiaming and Meng, Chenlin and Ermon, Stefano
    arXiv preprint arXiv:2010.02502, 2020

  12. Improved denoising diffusion probabilistic models
    Nichol, Alexander Quinn and Dhariwal, Prafulla
    International conference on machine learning, 2021

  13. Brownian motion and Dyson Brownian motion
    Tao, Terence
    https://terrytao.wordpress.com/2010/01/18/254a-notes-3b-brownian-motion-and-dyson-brownian-motion

  14. Nonlinear dispersive equations: local and global analysis
    Tao, Terence
    American Mathematical Soc., 2006

  15. Consistency models
    Song, Yang and Dhariwal, Prafulla and Chen, Mark and Sutskever, Ilya
    arXiv preprint arXiv:2303.01469, 2023

  16. Musings on typicality
    Dieleman, Sander
    https://benanne.github.io/2020/09/01/typicality.html

  17. Continuous diffusion for categorical data
    Dieleman, Sander and Sartran, Laurent and Roshannai, Arman and Savinov, Nikolay and Ganin, Yaroslav and Richemond, Pierre H and Doucet, Arnaud and Strudel, Robin and Dyer, Chris and Durkan, Conor and others
    arXiv preprint arXiv:2211.15089, 2022

  18. Noise schedules considered harmful
    Dieleman, Sander
    https://sander.ai/2024/06/14/noise-schedules.html

  19. Flow straight and fast: Learning to generate and transfer data with rectified flow
    Liu, Xingchao and Gong, Chengyue and Liu, Qiang
    arXiv preprint arXiv:2209.03003, 2022

  20. Flow matching for generative modeling
    Lipman, Yaron and Chen, Ricky TQ and Ben-Hamu, Heli and Nickel, Maximilian and Le, Matt
    arXiv preprint arXiv:2210.02747, 2022

  21. A kernel test of goodness of fit
    Chwialkowski, Kacper and Strathmann, Heiko and Gretton, Arthur
    International conference on machine learning, 2016

  22. A kernelized Stein discrepancy for goodness-of-fit tests
    Liu, Qiang and Lee, Jason and Jordan, Michael
    International conference on machine learning, 2016

  23. How to train your energy-based models
    Song, Yang and Kingma, Diederik P
    arXiv preprint arXiv:2101.03288, 2021

  24. Estimation of non-normalized statistical models by score matching.
    Hyvärinen, Aapo and Dayan, Peter
    Journal of Machine Learning Research, 2005

  25. A connection between score matching and denoising autoencoders
    Vincent, Pascal
    Neural computation, 2011