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.
Evolutionary Computation is a branch of AI inspired by biological evolution and natural selection. It involves using algorithms to mimic evolutionary processes such as…