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almostsuremath.com | ||
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gregorygundersen.com
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| | | | | [AI summary] The post discusses the simulation of geometric Brownian motion (GBM) using Python, explaining its mathematical foundations and verifying results against theoretical models. | |
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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 ... | |
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destevez.net
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vankessel.io
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| | | A blog for my thoughts. Mostly philosophy, math, and programming. | ||
