hello, this lead to confusion, what is the insight behind using a dropout, or dropconnect, based neural network, or even pruning/sparse neural network, does this have to do with, several neurons staying in an inactive state, when we carry a particular task, that is of all the neurons in our brains, only a few of them are involved, when we carry a particular task, rest are idle. And then there are these different techniques to model the same concept mathematically? Plus is there a technique that does not use a hyperparameter to drop elements, like in dropout we need to specify dropout rate manually, but a technique that works without any manual hyperparameter input?