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

Automation involves the use of technology, including AI, to perform tasks and processes with minimal human intervention. By automating repetitive or time-consuming tasks, businesses…
Clustering in AI refers to the process of grouping similar data points together based on their inherent characteristics or attributes. By identifying patterns or…
OpenAI is a research organisation dedicated to advancing AI in a safe and beneficial way. They develop cutting-edge AI technology while prioritising ethical considerations…
Autonomous agents are AI systems that can perform actions and make decisions independently, guided by predefined goals or learning processes. Businesses leverage autonomous agents…