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 ...

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 ...

This repository contains a PyTorch implementation of an autoencoder designed to perform anomaly detection on the dSprites dataset. The model learns a compact latent ...

This repository contains a Jupyter Notebook (Variational_autoencoder.ipynb) that implements a Variational Autoencoder (VAE) from scratch using PyTorch. The model is trained on the MNIST dataset to ...