Modular Neural Networks are AI models composed of smaller interconnected modules, each responsible for a specific sub-task or component. These modular architectures allow for easier interpretation, flexibility, and scalability. Modular neural networks have applications in areas like computer vision, natural language processing, and robotics.
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…