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.
Neuroevolution is a type of AI learning that combines neural networks and evolutionary algorithms. Neuroevolution algorithms evolve neural networks over generations, adapting them to…