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You are here		github.com GitHub - yang-song/score_sde: Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral) · GitHub
|	|	yang-song.net Generative Modeling by Estimating Gradients of the Data Distribution | Yang Song	0.7 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 ...
|	|	sander.ai The geometry of diffusion guidance Sander Dieleman	4.2 parsecs away Travel
|	|	More thoughts on diffusion guidance, with a focus on its geometry in the input space.
|	|	christopher-beckham.github.io Techniques for label conditioning in Gaussian denoising diffusion models | Christopher Beckham, PhD	3.9 parsecs away Travel
|	|	Techniques for label conditioning in Gaussian denoising diffusion models
|	|	bdtechtalks.com A simple guide to gradient descent in machine learning - TechTalks	23.6 parsecs away Travel
|		Gradient descent is the main technique for training machine learning and deep learning models. Read all about it.

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