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

The Viterbi Algorithm is a dynamic programming algorithm used in sequence analysis, such as speech recognition and Natural Language Processing. It finds the most…
Object Recognition is the capability of AI systems to identify and classify objects within images or videos. By utilising advanced algorithms and Neural Networks,…
Deep Reinforcement Learning is a subset of Machine Learning that combines Deep Learning and Reinforcement Learning. It involves training AI models to make decisions…
Robotics Process Automation is an AI technology that automates repetitive and routine tasks in business processes. RPA involves using software robots to emulate human…