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

A convolutional neural network is a powerful deep learning model designed for processing and analysing visual data. It excels in tasks such as image…
Instance-Based Learning is an AI approach where models make predictions based on similarity to previously seen examples. Instead of generalising from a predefined set…
Multi-Agent Systems are AI systems where multiple autonomous agents interact and collaborate to accomplish a goal. These agents can be software programs, robots, or…
The Viterbi Algorithm is a dynamic programming algorithm used in sequence analysis, such as speech recognition and Natural Language Processing. It finds the most…