Vae

A Variational Autoencoder (VAE) is a type of deep learning model that uses probabilistic techniques to learn compact and meaningful representations of complex data, such as images and text. As a powerful tool for unsupervised learning and generative modeling, VAEs have become increasingly relevant in the tech community, enabling applications like image compression, anomaly detection, and data generation, and are being explored in various research areas, including computer vision, natural language processing, and robotics.