Skip propagation

Skip propagation is a technique used in artificial neural networks to help the model learn more efficiently. Normally, information flows step-by-step through layers, but skip propagation allows data to "jump" over some intermediate layers and connect directly to later layers. This helps the network capture both local and global patterns in the data more effectively, reducing training time and improving performance. Think of it like taking shortcuts in a route, enabling faster and more direct communication within the network to better understand complex information.