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

Digital assistants, also known as Virtual Assistants or Chatbots, are AI-powered software applications that can engage in conversations and perform tasks on behalf of…
Fuzzy Logic is a mathematical framework that deals with uncertainty and imprecision. By assigning degrees of truth to statements, Fuzzy Logic allows businesses to…
Human-in-the-loop refers to a collaborative approach where humans and AI systems work together to achieve optimal results. It involves combining human expertise, judgement, and…
Multi-Modal learning refers to AI models that learn from multiple sources of data, such as text, images, and audio. By incorporating information from multiple…