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

Object Detection is an AI technique that identifies and localises objects within an image or video. It involves analysing the visual data and assigning…
Graph Neural Networks are machine learning models designed to handle data structured as graphs. They can capture relationships and dependencies between entities and perform…
Game Theory is a mathematical framework used to study and analyse strategic decision-making in situations involving multiple actors or players. It helps businesses understand…
Quantum Computing and AI are two fields that can complement and enhance each other. Quantum Computing can perform calculations faster and more efficiently than…