How I Understand Diffusion Models
About this lesson
Diffusion models are powerful generative models that enable many successful applications like image, video, and 3D generation from texts. In this tutorial, I share my understanding of the diffusion model basics, including training, guidance, resolution, and speed. Below are some other great resources to learn more about diffusion models. ===== Slides ===== Here are the slides used in this video Training: https://bit.ly/3WudEPH Guidance: https://bit.ly/3wedCky Resolution: https://bit.ly/4bqxHmo Speed: https://bit.ly/4bpJzoJ ===== Tutorials ===== [CVPR 2022 Tutorial] Denoising Diffusion-based Generative Modeling: Foundations and Applications https://cvpr2022-tutorial-diffusion-models.github.io/ [CVPR 2023 Tutorial] Denoising Diffusion Models: A Generative Learning Big Bang https://cvpr2023-tutorial-diffusion-models.github.io/ [A short course by DeepLearning.AI] How Diffusion Models Work https://www.youtube.com/watch?v=obdVesVsGQI ===== Training ===== [Sohl-Dickstein et al. 2015] Deep Unsupervised Learning using Nonequilibrium Thermodynamics https://arxiv.org/abs/1503.03585 [Ho et al. 2020]: Denoising Diffusion Probabilistic Models https://arxiv.org/abs/2006.11239 [Luo 2022] Understanding Diffusion Models: A Unified Perspective https://arxiv.org/abs/2208.11970 [Karras et al. 2022] Elucidating the design space of diffusion-based generative models https://arxiv.org/abs/2206.00364 [Karras et al. 2023] Analyzing and Improving the Training Dynamics of Diffusion Models https://arxiv.org/abs/2312.02696 ===== Guidance ===== [Dhariwal and Nichol 2021] Diffusion Models Beat GANs on Image Synthesis https://arxiv.org/abs/2105.05233 [Ho and Salimans 2022] Classifier-Free Diffusion Guidance https://arxiv.org/abs/2207.12598 [Sander Dieleman 2022] Guidance: a cheat code for diffusion models https://sander.ai/2022/05/26/guidance.html [Sander Dieleman 2023] The geometry of diffusion guidance https://sander.ai/2023/08/28/geometry.html ===== Resolution ===== [Ho et al.
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