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.
Neural Networks are a type of Machine Learning model inspired by the human brain. They are composed of interconnected nodes, or “neurons,” that process…