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 blog.otoro.net
Generating Large Images from Latent Vectors |
| | jxmo.io
Introduction to variational autoencoders - Jack Morris
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| | A primer on variational autoencoders (VAEs) culminating in a PyTorch implementation of a VAE with discrete latents.
| | dennybritz.com
Deep Learning ideas that have stood the test of time ยท Denny's Blog
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| | Deep Learning is such a fast-moving field and the huge number of research papers and ideas can be overwhelming.
| | blog.keras.io
Building Autoencoders in Keras
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| | [AI summary] The text discusses various types of autoencoders and their applications. It starts with basic autoencoders, then moves to sparse autoencoders, deep autoencoders, and sequence-to-sequence autoencoders. The text also covers variational autoencoders (VAEs), explaining their structure and training process. It includes code examples for each type of autoencoder and mentions the use of tools like TensorBoard for visualization. The VAE section highlights how to generate new data samples and visualize the latent space. The text concludes with references and a note about the potential for further topics.
| | blog.scottlogic.com
The basics of the Layered Neural Network
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| Recently I've been learning about Neural Networks and how they work. In this blog post I write a simple introduction in to some of the core concepts of a basic layered neural network.