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.
Genetic Algorithms are optimisation techniques inspired by the principles of evolution. By mimicking natural selection, Genetic Algorithms explore a large search space and find…