What are some architectural types of neural networks beyond CNNs and RNNs, and in what scenarios would they be used?

Beyond CNNs and RNNs, key types of neural networks include: 1) **Feedforward Neural Networks (FNNs)** - used for simple tasks like image classification. 2) **Generative Adversarial Networks (GANs)** - employed for generating realistic images or data augmentation. 3) **Autoencoders** - used for unsupervised learning and dimensionality reduction. 4) **Graph Neural Networks (GNNs)** - effective for processing data represented as graphs, such as social networks or molecule structures. Each architecture has particular strengths tailored for specific types of data or tasks.