Variational Autoencoders explained from scratch

AI • Machine Learning • Tech on Instagram: "A variational autoencoder (VAE) is a generative model that learns to represent data not as fixed points, but as probability distributions in a hidden space. Like other neural networks, it uses large matrices with tunable parameters to process the input, but instead of producing a single compressed vector, it outputs a mean and variance that define a distribution the input could come from. During training, the model samples from this distribution and tr

画像のためのディープラーニング（深層学習） ～ CNN/R-CNN による物体の認識と検出 ～

Deep Learning Toolbox Model Compression Library

Deep Learning for Engineers, Part 5: Deploying Deep Learning Models