Anomaly detection is the process of finding items in a dataset that are different in some way from the majority of the items. For example, you could examine a dataset of credit card transactions to ...

Reference implementation for a variational autoencoder in TensorFlow and PyTorch. I recommend the PyTorch version. It includes an example of a more expressive variational family, the inverse ...

A simple implementation of an Autoencoder Neural Network using PyTorch trained on the MNIST handwritten digit dataset. The project demonstrates how an autoencoder can learn a compressed representation ...

Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...