/explore

Click through on any links that interest you or select the planets on the right to continue exploring the Outer Web.
You are here

 cgad.ski
Hölder's Inequality and the Evidence Lower Bound
| | jaketae.github.io
From ELBO to DDPM - Jake Tae
4.2 parsecs away

Travel
| | In this short post, we will take a look at variational lower bound, also referred to as the evidence lower bound or ELBO for short. While I have referenced ELBO in a previous blog post on VAEs, the proofs and formulations presented in the post seems somewhat overly convoluted in retrospect. One might consider this a gentler, more refined recap on the topic. For the remainder of this post, I will use the terms "variational lower bound" and "ELBO" interchangeably to refer to the same concept. I was heavily inspired by Hugo Larochelle's excellent lecture on deep belief networks.
| | jxmo.io
Introduction to variational autoencoders - Jack Morris
4.6 parsecs away

Travel
| | A primer on variational autoencoders (VAEs) culminating in a PyTorch implementation of a VAE with discrete latents.
| | www.randomservices.org
Continuous Distributions
5.7 parsecs away

Travel
| | [AI summary] The text covers various topics in probability and statistics, including continuous distributions, empirical density functions, and data analysis. It discusses the uniform distribution, rejection sampling, and the construction of continuous distributions without probability density functions. The text also includes data analysis exercises involving empirical density functions for body weight, body length, and gender-specific body weight.
| | wtfleming.github.io
Cats vs Dogs - Part 2 - 98.6% Accuracy - Binary Image Classification with Keras and Transfer Learning
11.6 parsecs away

Travel
| [AI summary] This article demonstrates how to achieve 98.6% accuracy in binary image classification of cats and dogs using Keras and transfer learning with the VGG16 model.