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You are here		sander.ai Diffusion models are autoencoders Sander Dieleman
|	|	tiao.io A Tutorial on Variational Autoencoders with a Concise Keras Implementation | Louis Tiao	1.4 parsecs away Travel
|	|	An in-depth practical guide to variational encoders from a probabilistic perspective.
|	|	yang-song.net Generative Modeling by Estimating Gradients of the Data Distribution | Yang Song	0.5 parsecs away Travel
|	|	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 ...
|	|	angusturner.github.io Diffusion Models as a kind of VAE | Angus Turner	1.3 parsecs away Travel
|	|	Machine Learning and Data Science.
|	|	www.jerpint.io Teaching ChatGPT about the birds and the bees - jerpint	15.1 parsecs away Travel
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