My Account
Forward Thinking Logo

What is Variational Autoencoders (VAE)?

Skill Level:

Variational Autoencoders are a type of generative model used in unsupervised learning. VAEs learn a low-dimensional representation of input data and can generate new data samples similar to the training data. They have applications in tasks such as image generation, anomaly detection, and data compression.

Other Definitions

Knowledge Graphs

Knowledge Graphs are a structured representation of knowledge that captures relationships between entities. They organise information in a way that allows machines to understand…

Federated Learning

Federated Learning is a privacy-preserving technique where AI models are trained across multiple decentralised devices or systems without sharing raw data. Instead, only aggregated…

Quantum Computing

Quantum Computing and AI are two fields that can complement and enhance each other. Quantum Computing can perform calculations faster and more efficiently than…

Object Detection

Object Detection is an AI technique that identifies and localises objects within an image or video. It involves analysing the visual data and assigning…
Back to Glossary