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

Artificial General Intelligence refers to AI systems capable of understanding, learning, and performing any intellectual task as humans do. Although AGI remains aspirational, it…
Support Vector Machines (SVMs) are Machine Learning algorithms used for classification and regression tasks. SVMs create decision boundaries and maximise the margin between different…
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…
Big Data refers to large, complex datasets that cannot be easily managed or analysed with traditional data processing methods. AI techniques, such as Machine…