|
You are here |
hbiostat.org | ||
| | | | |
deepai.org
|
|
| | | | | Bayesian inference refers to the application of Bayes' Theorem in determining the updated probability of a hypothesis given new information. | |
| | | | |
meassociation.org.uk
|
|
| | | | | The BMJ also reports on mounting pressure for the Lancet to respond to calls for independent reanalysis of the controversial PACE trial. | |
| | | | |
www.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. | |
| | | | |
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. | ||