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 kyunghyuncho.me
Stochastic variational inference for low-rank stochastic block models, or how i re-discovered SBM unnecessarily - Kyunghyun Cho
| | tiao.io
A Tutorial on Variational Autoencoders with a Concise Keras Implementation | Louis Tiao
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| | An in-depth practical guide to variational encoders from a probabilistic perspective.
| | www.depthfirstlearning.com
Variational Inference with Normalizing Flows ยท Depth First Learning
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| | [AI summary] The user has provided a detailed and complex set of questions and reading materials related to normalizing flows, variational inference, and generative models. The content covers topics such as the use of normalizing flows to enhance variational posteriors, the inference gap, and the implementation of models like NICE and RealNVP. The user is likely seeking guidance on how to approach these questions, possibly for academic or research purposes.
| | lilianweng.github.io
What are Diffusion Models? | Lil'Log
3.7 parsecs away

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| | [Updated on 2021-09-19: Highly recommend this blog post on score-based generative modeling by Yang Song (author of several key papers in the references)]. [Updated on 2022-08-27: Added classifier-free guidance, GLIDE, unCLIP and Imagen. [Updated on 2022-08-31: Added latent diffusion model. [Updated on 2024-04-13: Added progressive distillation, consistency models, and the Model Architecture section.
| | squidarth.com
Teaching Stable Diffusion about Myself
23.3 parsecs away

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| [scroll down if you just want to get to the images]