NVAE: A Deep Hierarchical Variational Autoencoder Demo Brief

Unsupervised Anomaly Video Detection via a Double-Flow ConvLSTM Variational Autoencoder

Error-resilient Hierarchical Autoencoders for High Dimensional Data Compression in Wireless Networks | ACM Transactions on Sensor Networks

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

Variational Autoencoders explained from scratch