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

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…
Knowledge Graphs are a structured representation of knowledge that captures relationships between entities. They organise information in a way that allows machines to understand…
Genetic Algorithms are optimisation techniques inspired by the principles of evolution. By mimicking natural selection, Genetic Algorithms explore a large search space and find…
Support Vector Machines (SVMs) are Machine Learning algorithms used for classification and regression tasks. SVMs create decision boundaries and maximise the margin between different…