I'm trying to understand how training neural networks using batches work. I've referred to posts like this thread this and this but they don't fully answer my question.
When you send in a single example, the errors at the output layer are calculated and used to adjust the weights based on backpropagation. But if you send in multiple examples at once, what happens? Are the errors averaged, such that one round of backpropagation is performed for each batch?