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AI based Drug Design using Variational Autoencoder and Weighted Retraining - Preferred Networks Research & Development
| | 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.
| | tiao.io
A Tutorial on Variational Autoencoders with a Concise Keras Implementation | Louis Tiao
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| | An in-depth practical guide to variational encoders from a probabilistic perspective.
| | 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.
| | igorstechnoclub.com
Week 5 in Data Science: Image recognition neural network with 90% accuracy - a trivial task | Igor's Techno Club
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| This week I learned something that finally made "transfer learning" click. I had always heard that you can hit strong accuracy fast by reusing a pretrain...