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

Fuzzy Logic is a mathematical framework that deals with uncertainty and imprecision. By assigning degrees of truth to statements, Fuzzy Logic allows businesses to…
Speech Recognition enables machines to understand and interpret spoken words. By applying natural language processing techniques and AI models, businesses can develop speech recognition…
Decision networks, also known as Probabilistic Graphical Models, are a type of AI model that represents uncertain knowledge using a graph structure. Decision Networks…
Backpropagation is a technique used in training Artificial Neural Networks. It involves propagating error information backward through the network, allowing adjustments to be made…