DenseNet architecture: why it concatenates instead of summing
DenseNet connects every layer to every later layer and stacks channels instead of summing them the way ResNet does. Why that helps with vanishing gradients, how bottleneck blocks and transition layers keep the tensors in check, and where the memory cost shows up in PyTorch.