{"id":1169,"slug":"vae","name":"VAE","short_description":"A variational autoencoder (VAE) is a generative model that learns compact latent representations using Bayesian inference.","url":"https://github.com/topics/vae","github_count":1110,"created_by":null,"logo_url":null,"released":null,"wikipedia_url":"https://en.wikipedia.org/wiki/Variational_autoencoder","related_topics":[],"aliases":["variational-autoencoder"],"github_url":null,"content":"\u003cp\u003eA variational autoencoder (VAE) is a generative model that combines deep learning with Bayesian inference to learn compact latent representations of data. VAEs are widely used for image generation, anomaly detection, and data augmentation.\u003c/p\u003e\n","created_at":"2026-03-11T00:24:22.027Z","updated_at":"2026-06-13T00:29:33.376Z","topic_url":"https://awesome.ecosyste.ms/api/v1/topics/vae","html_url":"https://awesome.ecosyste.ms/topics/vae","projects_url":"https://awesome.ecosyste.ms/api/v1/projects?keyword=vae","lists_url":"https://awesome.ecosyste.ms/api/v1/lists?topic=vae"}