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

Incremental Learning is an AI technique that allows models to continuously learn from new data without retraining from scratch. Instead of training the model…
Support Vector Machines (SVMs) are Machine Learning algorithms used for classification and regression tasks. SVMs create decision boundaries and maximise the margin between different…
Evolutionary Computation is a branch of AI inspired by biological evolution and natural selection. It involves using algorithms to mimic evolutionary processes such as…
The Zeroth Law of Robotics is a fictional concept introduced by science fiction author Isaac Asimov. It suggests that a robot’s actions should not…