Explore >> Select a destination

You are here

 tiao.io
Density Ratio Estimation for KL Divergence Minimization between Implicit Distributions | Louis Tiao
| | jxmo.io
Introduction to variational autoencoders - Jack Morris
1.9 parsecs away

Travel
| | A primer on variational autoencoders (VAEs) culminating in a PyTorch implementation of a VAE with discrete latents.
| | www.depthfirstlearning.com
Variational Inference with Normalizing Flows ยท Depth First Learning
2.5 parsecs away

Travel
| | [AI summary] The user has provided a detailed and complex set of questions and reading materials related to normalizing flows, variational inference, and generative models. The content covers topics such as the use of normalizing flows to enhance variational posteriors, the inference gap, and the implementation of models like NICE and RealNVP. The user is likely seeking guidance on how to approach these questions, possibly for academic or research purposes.
| | blog.evjang.com
Eric Jang: Tips for Training Likelihood Models
2.3 parsecs away

Travel
| | This is a tutorial on common practices in training generative models that optimize likelihood directly, such as autoregressive models and ...
| | programminghistorian.org
Creating Deep Convolutional Neural Networks for Image Classification | Programming Historian
21.3 parsecs away

Travel
| [AI summary] The text provides an in-depth explanation of using neural networks for image classification, focusing on the Teachable Machine and ml5.js tools. It walks through creating a model, testing it with an image, and displaying results on a canvas. The text also discusses the limitations of the model, the importance of training data, and suggests further resources for learning machine learning.