|
You are here |
colinraffel.com | ||
| | | | |
blog.evjang.com
|
|
| | | | | This is a tutorial on common practices in training generative models that optimize likelihood directly, such as autoregressive models and ... | |
| | | | |
www.hongliangjie.com
|
|
| | | | | ||
| | | | |
yang-song.net
|
|
| | | | | 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 ... | |
| | | | |
abnormalsecurity.com
|
|
| | | Explore five key insights from Osterman Research on how AI-driven tools are revolutionizing defensive cybersecurity by enhancing threat detection,... | ||