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 ...

Generating synthetic data is useful when you have imbalanced training data for a particular class, for example, generating synthetic females in a dataset of employees that has many males but few ...

This repository implements a Variational Autoencoder (VAE) using PyTorch, inspired by the referenced Kaggle project, with the goal of learning a smooth latent representation of images and generating ...

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 ...