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

Cognitive Robotics involves the integration of AI and robotics to create intelligent machines that can interact and collaborate with humans in a human-like manner….
Cybersecurity in Artificial Intelligence addresses the protection of AI systems from security threats and vulnerabilities. It involves implementing strategies and technologies to safeguard AI…
Decision networks, also known as Probabilistic Graphical Models, are a type of AI model that represents uncertain knowledge using a graph structure. Decision Networks…
Incremental Learning is an AI technique that allows models to continuously learn from new data without retraining from scratch. Instead of training the model…