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.
Artificial Neural Networks are computational models inspired by the human brain’s structure and function. They consist of interconnected nodes that process and transmit data,…