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.
Ontologies are a representation of knowledge that defines concepts and the relationships among them. Ontologies enable machines to structure and reason information in a…