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alexanderetz.com | ||
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andrewjaffe.net
[AI summary] A technical discussion of Bayesian statistics, specifically debating the limitations of Bayesian model comparison and advocating for generalized frequentist approaches to model checking and falsification. |
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fharrell.com
This is the story of what influenced me to become a Bayesian statistician after being trained as a classical frequentist statistician, and practicing only that mode of statistics for many years. |
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www.quantstart.com
Bayesian Statistics: A Beginner's Guide |
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blog.otoro.net
[AI summary] This text discusses the development of a system for generating large images from latent vectors, combining Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). It explores the use of Conditional Perceptual Neural Networks (CPPNs) to create images with specific characteristics, such as style and orientation, by manipulating latent vectors. The text also covers the ability to perform arithmetic on latent vectors to generate new images and the potential for creating animations by transitioning between different latent states. The author suggests future research directions, including training on more complex datasets and exploring alternative training objectives beyond Maximum Likelihood. |
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