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