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 liorsinai.github.io
Image generation with MNIST - Lior Sinai
| | christopher-beckham.github.io
Techniques for label conditioning in Gaussian denoising diffusion models | Christopher Beckham, PhD
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| | Techniques for label conditioning in Gaussian denoising diffusion models
| | yang-song.net
Generative Modeling by Estimating Gradients of the Data Distribution | Yang Song
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| | This blog post focuses on a promising new direction for generative modeling. We can learn score functions (gradients of log probability density functions) on a large number of noise-perturbed data distributions, then generate samples with Langevin-type sampling. The resulting generative models, often called score-based generative models, has several important advantages over existing model families: GAN-level sample quality without adversarial training, flexible model architectures, exact log-likelihood ...
| | lilianweng.github.io
What are Diffusion Models? | Lil'Log
4.4 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.
| | dennybritz.com
Deep Learning ideas that have stood the test of time ยท Denny's Blog
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| Deep Learning is such a fast-moving field and the huge number of research papers and ideas can be overwhelming.